Miracle-dz/UniFAR-FTUs huggingface dataset:
High Frequency Soft Switching Control Method for SiC Buck-Boost Converter in Dual Source Application

Buck-boost SiC converters are widely used in special vehicle to supply stable electrical power for weapon system from power batteries. In order to improve the dynamic performance of short term large power demand, DC converter are often used in parallel with super capacitor at output terminal. In such dual source (power battery and super capacitor) application scenario, the conventional soft-switching control method for converter may cause oscillation during the startup process. In addition, the conventional current sampling and discrete control strategies is no longer applicable for the high-frequency control of SiC power switches. In order to solve the above problems, a new soft-switching control method is proposed in this paper. By adjusting the duty ratio limitation based on the voltages of input and output terminals before starting operation, the DC converter can start output stably and smoothly in the dual source scenario, and the interconnection of switching period and discrete control strategy can be decoupled while ensuring the sampling accuracy and control performance. This method has been verified by simulation and experiment.
Study on Sensitivity Parameters of Staggered Heterojunction Gate Stack Tunnel FET Biosensor

In this study, we suggest a label-free, low-power biosensor based on a staggered heterojunction gate stack tunnel field-effect transistor (SHGS TFET). A SHGS TFET-based biosensor has not yet been experimentally developed, although a FET-based biosensor with a nanogap cavity already devloped. As a result, an analytical and simulation-based study presents an idea for a SHGS TFET-based sensor. Comparing with conventional TFET-based biosensor, the results show improved responsiveness to two different properties (dielectric constant and charge of biomolecules). TFET is a desirable different design for CMOS-built sensor uses due to its compatibility with CMOS, low leakage, sharp subthreshold slope, and other benefits. Even while FET-based biosensors have many benefits, their short channel effects (SCEs) and theoretically-restricted subthreshold swing (SS > 60 mv/dec) limit the device’s sensitivity and increase power dissipation because of thermionic electron emission. Researchers concentrate on SHGS TFET-based biosensors, which have superior features and low power consumption because of band-to-band carrier tunnelling and steep subthreshold swing. The device performances like the analog as well as sensitivity characteristics is evaluated by taking into consideration biomolecules like protein (K=2.5), aptes (K=3.56), as biomolecules in the cavity and using silicon as the channel material. For simulating persistence the 2D Sentaraus TCAD simulator has been used. In-depth information about Staggered Heterojunction Gate Stack Tunnel FET based biosensors is covered in this report. This information includes qualitative and quantitative parameter analysis studies like sensitivity parameters and various factors affecting sensitivity by comparing various structures and the mechanisms at play. The report also includes a synopsis of several sensitivity criteria.
Phase‐transition studies of Ba0.90Ca0.10(Ti1−xZrx)O3 ferroelectric ceramic compounds

Perovskite‐structured Ba0.90Ca0. 10(Ti1−xZrx)O3 ceramics were prepared in this work and subsequently studied in terms of composition‐dependent dielectric and high‐resolution long‐range order structural properties from 30 to 450 K. The dielectric response of these materials was measured at several frequencies in the range from 1 kHz to 1 MHz. Combining both techniques, including Rietveld refinement of the X‐ray diffraction data, allowed observing that, when increasing Zr4+ content, the materials change from conventional to diffuse and relaxor ferroelectric compounds, the transition occurring spontaneously at the x = 0.18 composition. Interestingly, this spontaneous transition turned out to be prevented for a further increase of Zr4+. On the basis of all the dielectric and structural results processed, a phase diagram of this system is presented.
SimplestNet-Drone: An efficient and Accurate Object Detection Algorithm for Drone Aerial Image Analytics

Images captured by drones are extremely difficult to detect due to varying camera angles, distances, sizes, and environmental conditions, making it challenging to accurately detect an object from a height. Nonetheless, object detection plays a crucial role in computer vision and has made significant improvements to images captured by drones. We apply the YOLOv5 framework with modified feature extraction and focus detection. The problem with aerial images is object size and viewing angle from a high altitude, so we proposed a single-stage object detection model called “SimplestNet-Drone”. We included a fourth prediction head to improve the object detection on the smallest objects and improve the detection speed. The algorithm's prediction accuracy is improved by adding an attention model mechanism, which detects attention regions in environments and suppresses unnecessary information. The model was trained and tested on the VisDorne dataset and compared with other object detection models. The model shows great improvement, with a mean average precision of 63.72%, and has improved the Yolo architecture. A real-time implementation of our model can be watched in the following YouTube video: https://youtu.be/De8t4tjtb6w
Control Design of Quadcopter using Output Feedback Control Pole Placement

A Quadcopter is an UAV or unmanned aircraft with four rotors in a square formation that may be operated remotely, necessitating a control system. The Quadcopter mathematical model used is linear and the Quadcopter can move both rotationally and translationally. In this research, system analysis and control design were carried out using the Output Feedback Control Pole Placement method to control the roll angle and pitch angle, to maintain stability by increasing the performance of the Quadcopter system. The Quadcopter dynamic system analysis results are stable, controllable, and observable. The control design is carried out using three feedback gain scenarios $(K_{1},K_{2}$, and $K_{3})$ to adjust the eigenvalues so that they are stable. Based on the simulation results of roll and pitch angles, it is concluded that the third scenario $(K_{3})$ with the fastest stable time, and the first scenario $(K_{1})$ with the lowest overshoot value.
Migrant Work Inclusion: Designing Research on Entrepreneurship Support

This paper proposes a novel research design for analyzing how Entrepreneurial Support (ES) can impact Entrepreneurial Activity (EA) in general and activities carried out by migrant entrepreneurs specifically. It develops a case study based on a Norwegian migrant entrepreneurship research project, comparing three ES programs for migrants with three ES programs for non-migrants and two mixed programs over a three-year period. The key features of the new design set out in this paper are 1) the usage of a Systemic Entrepreneurship Activity Method (S-E-A-M) and digital platform for the ES referred to as Entrepreneurship Management System (EMS), 2) a digital observation method collecting mixed methods data via the EMS, 3) the comparative and longitudinal nature of the study analyzing different groups of entrepreneurs over three years and 4) the co-creative nature of the study involving the entrepreneurs in the ES design.
Assessment of Blood Donor Information Using Kernel Density Maps: A Case Study at Gangtok District, Sikkim and Modeling of a Web Application.

Acquiring blood donor information is a very time-consuming process and may put the patient’s health at risk. Finding blood donor data is essential for receiving the correct type of blood as quickly as possible. This study aims to develop a web application to alleviate the hassles faced by critical patients. We acquire sample data from CRH hospital in Gangtok, Sikkim. We assess data from blood donors using ArcGIS platforms. Further, we generate a region-wise heat map. We include 391 blood donor records of which 165 are A+ Ve, 94 are B+ Ve, 43 are AB+ Ve, 3 are B- Ve, and 86 were O+ Ve. Through the modeled application users can locate blood donor information near them and communicate with the blood donor by direct phone call using the assessed heatmaps. Users can also register themselves by providing information such as their personal information, blood type, etc., which will be displayed on the heatmap for future use. Through the modeled application blood banks in that area can Figure out which locations have a higher volume of a specific blood type that they require, and then set up a camp or encourage volunteers to donate blood to help.
Investigation of Novel Z-shaped Gate TFET with Improved Device Characteristics

This paper proposes a novel Z-shaped gate TFET (ZG-TFET) to enhance the device switching characteristics. The gate terminal is elevated above the N+ pocket region to amplify the electric filed at source-pocket interface. In addition to this, the elevated gate terminal initiates the line tunneling to be occurred in both vertical and lateral direction of the source-pocket interface, which eventually improves the BTBT rate of charges into the channel region of ZG-TFET. The proper optimization of doping concentration and thickness of N+ pocket reduces the tunneling barrier-width at source/channel interface and thereby, increases ION (1.19×10-6A/µm at Vgs=1.2V). As per the obtained TCAD simulation results, the proposed device achieves approximately one order increment in ION, two order increment ION /IOFF ratio and twenty percent improvement in SS as compared to conventional L-shaped TFET. Hence, improvement in switching characteristics helps the proposed ZG-TFET to become more suitable for digital circuit applications.
Hybrid Energy Efficient Fuzzy C-Means with Bear Smell Search Algorithm in Wireless Sensor Networks

Energy efficiency is one of the primary deficiencies in wireless sensor networks. The sensor nodes present in the networks contain small battery, which cannot be changed or recharged again. Hence, the use of energy must be carefully monitored and preserved in these battery-operated networks. Energy optimization is recently the popular technique incluster-based routing protocols. The clustering methodology works under the act of group of sensor nodes where each group selects one head member called cluster head. To enhance the lifespan of the network with high energy efficiency, a Fuzzy C-means algorithm is offered in this articlefor clustering the sensor nodes. The cluster head is selected by using particle swarm optimization- Leven berg Marquardt (PSO-LM) algorithm to maximize the energy efficiency and diminish the quantity of dead sensor nodes in the network. Finally, a shortest path is selected via bear smell search algorithm to transmit the data to the sink node. The proposed method is experimentally evaluated and the results are compared in terms of packet delivery ratio and energy efficiency. The experimental outcome revealed that the proposed technique out performs other optimization algorithms and produced better results.
A super Threshold Compact Silicon Neuron Circuit for Different Neuron Dynamics Suitable for Spiking Neural Network

In this work we have designed and simulated a compact accelerated time silicon neuron circuit in super threshold to achieve proper neural dynamics. With this circuit we have accurately modeled regular spiking (RS), fast spiking (FS), chattering (CH) and intrinsic bursting (IB). The functionality of this circuit is verified with extreme simulation in 32nm, 45nm and 22nm FinFET technology. For this circuits we have analyzed different comparator circuits to meet the required dynamics and concluded that threshold modified comparator serves our purpose best.
Digital Fit(ness) - is ‘being in a fit with’ enough?

Researchers struggle to understand the nature of digital transformation and approach the conceptualization from various research perspectives. Concurringly, digital transformation is seen as an evolutionary change process with an increasing digitalization at its heart. Although a process requires a target state, a target state for digital transformation has not been discussed satisfactorily so far. Consequently, it is difficult for managers to steer with an eye on the goals in this change process. To provide guidance in this change endeavor for managers, researchers have developed different digital transformation maturity models. These models typically suggest a linear development for organizations but neglect idiosyncratic development paths for digital transformation. They combine aspects of matching current stakeholder demands with being prepared for future demands regarding digitalization. However, they typically design an end state or a best stage, which seems to be contradicting as digital transformation as an evolution has no target or end. To address this challenge of evolutionary change, a concept of digital fitness is introduced in this contribution, which reflects the ability of organizations to cope with current and future expectations of external stakeholders. A digital fitness model is presented that claims to conceptualize how a responsible management - focusing on the Chief Digital Officer and the Chief Information Officer - can decide for an appropriate level of digital fitness according to present and future external expectations. Building on that, a digital fitness matrix with implications for management strategies is presented.
Comparative study of Compound Semiconductors/ Silicon- based Cylindrical Surrounding Dual-Metal Gate Junctionless Accumulation-Mode (CS-DMG-JAM) MOSFET for High Frequency and Switching Applications

This paper introduces a comparison between compound semiconductors (GaN, GaAs, InP) and silicon- based Cylindrical Surrounding Dual- Metal Gate Junctionless Accumulation Mode (CS-DMG-JAM) MOSFET for high frequency and high switching applications. Several parameters including drain current, transconductance, output conductance, Maximum Transducer Power Gain (MTPG), current gain, cutoff frequency, subthreshold slope, Ion/Ioff ratio have been analysed for the considered device. Results indicate better performance of GaN- based device and thereby proves to be more applicable for industrial and aeronautical applications requiring high frequency. All the simulations are performed using ATLAS 3-D device simulator.
An energy-efficient AkidaNet for morphologically similar weeds and crops recognition at the Edge

There are a myriad of factors that influence on modern agriculture including water scarcity [1], climate change [2], biodiversity loss [3], pollutants [4], etc. Weed invasion is one of the greatest environmental threats to the productivity of agriculture. A threatening invasive species in Western Australia [5], and in many regions of the world [6] is wild radish (Raphanus raphanistrum). It has detrimental impacts on production costs, crop yield reduction (from 10% to 90% [7]), and quality of crops due to its capacity to compete with crops for nutrients, light and water [8], [9]. Particularly, the influence of wild radish on the quality and yield of canola has always been a concern in weed control [10]. Canola is known to be one of the world's healthiest vegetable oils, can be grown in winter or spring, and is an environmentally friendly biofuel [11]. The production of canola has a market value of AU$2.2 billion and has increased significantly to over four million tonnes in Australia from 2012 to 2013 [12]. With more than two million tonnes of canola seed exported by Australia every year, Australia has become the world's second largest exporter of canola [13]. However, the challenges in spraying herbicides on only targeted weeds has arisen from the high visual similarity between canola and wild radish species.
Is Positive Confirmation relevant for game theory?: An Experimental Test

Previous experimental work has found that Positive Confirmation is a significant factor in learning. However, to date, there has been no attempt to test this phenomenon in a gametheoretic setting. An experiment is undertaken which tests positive confirmation in a game against nature. It is found that positive confirmation does occur in this setting and results in behaviour that cannot be explained by current theories of choice. This suggests that current theories are incomplete and new approaches need to be developed to take account of positive confirmation.
Feature Representation for Network Intrusion Detection System Trough Embedding Neural Network

Computer network technology is growing rapidly, but cyberattacks are also increasing in number and variants that occur every year. Anomaly-based network intrusion detection system (NIDS) is still vulnerable to false positive rates even though it has used a machine learning approach to detect zero-day attacks on network traffic. Deep learning can provide advanced solutions to this problem. However, deep learning requires special handling to process tabular NIDS datasets with highly sparse categorical and numerical data. To overcome this, we propose a new embedding method implemented by embedding not only categorical data but also numerical data to provide the best representation features for deep learning models. The proposed method was evaluated with other deep learning and machine learning models with results outperforming all models based on the f1-score macro using the CSE-CIC-IDS-2018 dataset.
Interlayer twist angle-dependent electronic structure and optical properties of InSe/WTe2 van der Waals heterostructure

In this paper, we have studied the interlayer twist angle-dependent electronic structure and optical properties of InSe/WTe2 van der Waals (vdW) heterostructure by density functional theory (DFT)-PBE calculations. The variation of electronic band structure and optical spectra of InSe/WTe2 vdW heterostructure at various interlayer twist angles i.e. 0°, 13.90°, 19.11°, and 30° have been studied in detail. It is observed that InSe/WTe2 heterostructure has an indirect bandgap of 0.22 eV with type-II band alignment at a 0° angle. The band alignment transitions remain type II under all twist angles. However, the bandgap type changes from indirect to direct bandgap for different twisted angles. Among all the twisted angles, 30° has the smallest no of atoms and lattice mismatch with the highest absorption in the visible region for various optoelectronic applications.
A High-Precision Hall High-Current Sensor Detection Source

There is no unified standard for the measurement and detection of Hall current sensors at presently. Manufacturer makes equipment for measurement and detection according to their own verification scheme. The High current detection standard device is the key device to verify the Hall current sensor, and its output current accuracy directly determines the measurement accuracy of the high-current Hall sensor. Therefore, a Hall high current sensor detection device scheme is proposed in this paper. The main circuit adopts a multi-phase Buck converter interleaved and parallel topology, which can not only reduce the total output current ripple, improve the output precision, but also reduce the current stress of each phase Buck converter. Aiming at the problem of current imbalance caused by parameter differences between components, the master-slave current sharing method is used to perform closed-loop feedback control to achieve current sharing between modules. Finally, the simulation results in PSIM show that the total output current of the four-phase Buck converter is 100A, and the output current ripple ratio is 0.1%.
IRS Backscatter Based Hybrid Confidential Information and AN for Secrecy Transmission

Due to broadcast nature of electromagnetic waves, wireless communications are inherently vulnerable to the eavesdropping threat. To secure the air interface, this letter proposes a secrecy transmission strategy based on intelligent reflecting surface (IRS) backscatter. To be specific, the source (Alice) sends its confidential information to the legitimate user (Bob) with multiple passive eavesdroppers (Eves). To enhance the reception at Bob while deteriorating those at Eves, an IRS is deployed to convert the signal from Alice to a hybrid one consisting of confidential information and artificial noise through backscatter techniques. Based on this strategy, this letter minimises the transmit power at Alice, by optimising active and passive beamforming vectors under the constraints of the signal-to-interference-plus-noise ratios at Bob and Eve. To solve this problem, an alternative optimisation method is developed. The simulation results verify that the proposed strategy can achieve a secrecy performance gain.
Identifying Distant AGNs

Abstract The Baldwin, Phillips, and Terlevich emission-line ratio diagnostic ([OIII]/Hβ versus [NII]/Hα, hereafter BPT diagram) efficiently separates galaxies whose signal is dominated by star formation (BPT-SF) from those dominated by AGN activity (BPT-AGN). Yet the BPT diagram is limited to z<0.5, the redshift at which [NII]λ6584 leaves the optical spectral window. Using the Sloan Digital Sky Survey (SDSS), we construct a new diagnostic, or TBT diagram, that is based on rest-frame g−z color, [NeIII]λ3869, and [OII]λλ3726+3729 and can be used for galaxies out to z<1.4. The TBT diagram identifies 98.7% of the SDSS BPT-AGN as TBT-AGN and 97% of the SDSS BPT-SF as TBT-SF. Furthermore, it identifies 97% of the OPTX Chandra X-ray selected AGNs as TBT-AGN. This is in contrast to the BPT diagram, which misidentifies 20% of X-ray selected AGNs as BPT-SF.
Design of Vacuum Monitoring System Based on EPICS for HIRFL

To solve the problems of the original vacuum monitoring system, the function of remote control and monitoring of vacuum equipment is realized. According to the characteristics of the Heavy Ion Research Facility in Lanzhou (HIRFL), such as large number, wide distribution, and complex types of vacuum equipment, this paper researches and designs a remote real-time vacuum monitoring system, including underlying hardware design, IOC software, and interface design. The system adopts Experimental Physics and Industrial Control System (EPICS) architecture design. The Programmable Logic Controller (PLC) is used to receive and process data from the underlying hardware devices and controllers, and upload the data to the EPICS IOC system by the network. The vacuum data is displayed in the User interface and remote controlling commands are issued. The system is currently running normally, and the design has been proved to meet the expected functions.