Miracle-dz/UniFAR-FTUs huggingface dataset:
Development of a New 5 DoF Robotic Assistant System for Neurosurgery

Craniotomy and Brain Tumor Biopsy are sorts of neurosurgeries related to the brain. A craniotomy is a bone flap removal from the skull surface which is an essential procedure in open skull surgeries. A craniotomy can be a time-consuming process, and the large forces needed for the cutting process make surgeons exhausted before operating the critical brain tissue. As a result, the probability of further errors increases. On the other hand, Brain Tumor Biopsy is a high accuracy surgery that involves a needle insertion to the tumor through a specific pre-planned trajectory. Surgeons still use a stereotactic frame as needle guidance. This frame is a half-century technology that can involve human errors during measurement and mounting processes. Nowadays, High stiffness robotic systems can achieve precise positioning and guidance without frames, save time and effort, and enhance safety. This paper presents a new 5 DoF robotic-assistant system that can be used in both Surgeries. This system can reach any point on the surface of the patient's skull with different orientation angles within the proposed system workspace. Based on motion requirements and skull shape, decoupled remote center-of-motion (RCM) mechanisms are selected for this system. The proposed system illustrates a high stiffness under the maximum bone drilling forces with a position error below 230 μm.
Source Routing Protocol Based on Bayesian Network for Wireless Sensor Networks

Multi-path routing is always the focus in wireless sensor networks. Either energy efficiency or QoS is taken into account in the existing multi-path routing, which makes the protocol not realize in both requirements. In this paper, the paths selection approach based on Bayesian network are introduced into the multi-path routing establishment, while two phase path selection mechanism according to Path ID and Path Ability respectively, are applied into the protocol. The simulation shows that BNSR is better than the other protocols on longivity and transmission delay.
Optimal Energy Management of Isolated Micro-Grid Including Solar and Diesel Power with Pumped Storage

Recently, pumped storage hydropower is used in the agricultural industry and isolated rural micro-grid. On the other side, a diesel generator usually does not operate in optimum point in isolated power supply. Therefore, it can be used in joint with other energy sources such as photovoltaic and energy storage system which develop an ideal option for autonomous power generation in islanded mode. Hence, this paper intends to present an optimal operation and energy management method for a hybrid micro-grid with study on day-ahead scheduling. In this paper, optimal operation of hybrid micro-grid including of photovoltaic, pump as turbine system, and diesel generator are considered. The optimal energy management minimize the fuel cost of diesel generator, annual operating cost as well as the balance between generation and load in different seasons. Aiming to this purpose, three famous optimization algorithms, namely artificial bee colony (ABC), particle swarm optimization (PSO) and imperialist competitive algorithm (ICA), are used to determine the optimal diesel generator generation, pumped storage operating mode, pumping and turbine real power in order to minimize the total operating cost for a day-ahead.
A Study on Dynamic Charging Using Off-Resonant Coil Array With Receiver-side Compensation

This paper proposes a dynamic charging system for moving receiver by using an array of small off-resonant coils in a combination with receiver-side compensation circuit. Compared to the size of receiving coil, transmitting coils are small enough to make the coupling coefficient stable when the receiver moves along the transmit coil array. The compensation circuit at the receiver will be designed to approximately cancel out all the reactive components in the coupling link between the receiving coil and the nearby transmitting coils. As a result, the load will be seen almost directly from the source, and thus, stable output voltage can be achieved even if the receiver moves and/or if the load resistance varies. Experimental results confirm effectiveness of the proposed system.
Color outdoor image enhancement by V-NIR fusion and weighted luminance

Outdoor color images are often degraded due to uncontrolled conditions such as lighting, pollution, fog, shadows or haze. Those conditions cause loss of contrast and detail as the scattering has attenuation and smoothing effect. Considering Near Infrared (NIR) light is lower scatters than visible light due to its long wavelength, the NIR is spread through the fog. NIR images usually contain important information that can complement the visible image (V) in the same scene. In this work, we propose to fused V and NIR images, of the same scene, by pixel weight assignation of the luminance. The results show that color images are capable to enhance certain features not visible at the input V image. Moreover, the proposed fusion method provides relevant information from the NIR image while preserves the V information. The main characteristic of our approach to fusing is that only the relevant information is fused and the resulting colors are consistent with the scene.
Experimental Characterization of Narrowband Power Optimized Waveforms

Low power devices driven by energy harvesting are limited in working range by transmit power restrictions. Power optimized waveforms (POWs) have been proposed as a way to achieve a longer working range without increasing average transmit power. In the ultra high frequency (UHF) band, bandwidth occupancy needs to be small enough to satisfy relevant regulations: thus the wideband POWs explored in some prior work may be less practical than narrowband POWs. This paper experimentally evaluates the performance of narrowband multi-sine based POWs, varying number of sines from 2 to 20 and occupied bandwidth of 10 kHz, 100 kHz, and 1 MHz-all narrowband from a regulatory perspective. Our key result is that additional sine waves improve voltage sensitivity, but not Power Conversion Efficiency. In our experiments, we observed the voltage sensitivity benefits of the multi-sine POWs to be most pronounced at a power level of -13 dBm; at signal levels significantly below (-30 dBm) or above (0 dBm) this level, their benefits diminish. Finally, we also observe that in a real system (the WISP 5.1, which includes a rectifier and DC-DC converter), voltage sensitivity is a much more complex function of waveform and signal power than in simpler idealized rectifiers. The sensitivity is a non-monotonic and complex function of the number of sines, occupied bandwidth, and signal strength.
A Novel Simultaneous Wireless Information and Power Transfer System

Communication between primary and secondary side controllers is essential in practical applications of inductive power transfer (IPT) systems, which is generally realized by specific modules. However, such additional components increases the cost and the volume of the receiver. Therefore, this paper develops a novel simultaneous wireless information and power transfer (SWIPT) technique through a single-switch active receiver. The desired output voltage can be obtained by regulating the duty ratio of secondary side switch, and the information can be transmitted to the primary side by controlling the frequency of that switch. The proposed receiver advances in cost reduction, simple design, and easy realization of information exchange and power regulation. Experimental results are added to verify the proposed system.
Study on Natural Smoke Exhaust Characteristics of Railway Passenger Station under the Influence of Environmental Wind

In order to study the influence of environmental wind on natural smoke exhaust characteristics, a railway passenger station is selected to study the smoke exhaust effect under windowing modes M1 which to open the windward side window and M2 which to open the leeward side window with the wind speeds of 0 m/s, 3.4 m/s and 10 m/s by FDS software. The laws of smoke movement, temperature field changes and the impact on personnel safety evacuation are compared and analyzed in the station with different working conditions. The results show that when the wind speed is 0 m/s, both windowing modes M1 and M2 can effectively discharge the smoke out of the station. When the wind speed is 3.4 m/s, the windowing mode M1 exhaust time is delayed, the environment wind suppresses the natural smoke exhaust while the windowing mode M2 exhaust time is advanced, and the environment wind promotes the natural smoke exhaust. When the wind speed is 10 m/s strong wind, both of the windowing modes M1 and M2 natural smoke exhaust are invalid. The smoke layer height drops below 2 m from the ground after 600 s, and the visibility decreases to less than 10 m after 800 s, which seriously affects the personnel safety evacuation. Therefore, for the station, the windward exhaust window should be closed and the leeward exhaust window should be opened according to the wind direction to exhaust smoke in case of fire. For strong winds, due to the failure of natural smoke exhaust in both windowing modes M1 and M2, other measures should be taken to exhaust smoke.
A 55nm 1-to-8 bit Configurable 6T SRAM based Computing-in-Memory Unit-Macro for CNN-based AI Edge Processors

This work presents a 1-to-8 bit configurable SRAM CIM unit-macro using (1) a hybrid structure combining 6T-SRAM in-memory binary product-sum (IMBPS) with digital near-memory-computing multi-bit-PS accumulation (DNMPSA) to achieve high read accuracy and compact area, (2) a column-based place-value-grouped weight mapping (CPVGWM) and serial-bit input mapping (SBIN) scheme to facilitate reconfiguration and increase array efficiency for various input/weight precision. A 4Kb configurable 6T-SRAM CIM unit-macro was fabricated using a 55nm CMOS process and foundry 6T cells. The resulting macro achieved 3.5ns access time with 3b PS outputs and gained a 3.91-50x improvement in figure-of-merit, compared to previous SRAM-CIMs.
Study of Energy Behavior and Mathematical Modeling of the Didactic Plant Lab Volt 46801-32

The generation and supply of electricity has become indispensable in the development of society. The population is constantly growing and energy demand is increasing. Distributed generation and smart power grids are presented as an alternative to conventional forms of generation considering the increase in the electricity needs of its customers. The use of unconventional renewable energies such as solar, wind, biomass among others; in conjunction with energy storage systems, they can mitigate the growing electricity demand and reduce the use of fossil fuels. This research allows to model the electrical behavior of the different subsystems of the microgrid of electricity generation in different conditions and their results in order to know their dynamics, contribution and use as an optimal way of management electrical energy.
Outage Analysis of mmWave Integrated Device-to-Device Communication System under Nakagami Fading Channel

Millimeter-wave (mmWave) communication has emerged as a promising candidate to meet the capacity demand in highly dense indoor environments for the next-generation cellular networks. Utilization of directional mmWave for Device to Device (D2D) communication systems provides low powered, high data rate transmission with manageable interference. In this paper, the rate and outage probability for mmWave integrated D2D communication system under Nakagami-m fading channel are derived. The performance of the model is analyzed by obtaining the closed-form expressions for the outage probability of a D2D user, wherein multiple cellular or D2D users are interfering with a mmWave integrated D2D transmission. The impact of various system parameters such as sectored beamforming gain probabilities and distance from interfering nodes on D2D outage probability are also investigated. Results show that the D2D outage probability decreases with an increase in main lobe gain, whereas increases with an increase in side lobe gain.
VANET-Assisted Interference Mitigation for Millimeter-Wave Automotive Radar Sensors

As key sensors of the ADAS, mmWave radars have been widely used for fulfilling tasks including adaptive cruise control, lane-changing assistance and collision avoidance. However, the interference generated by mmWave radars mounted on close-by vehicles, if not managed well, could seriously degrade the radars’ performance, giving rise to a safety hazard. In this work, we study interference mitigation for the off-the-shelf 77 GHz FMCW mmWave radars. We review several state-of-the-art ideas for suppressing co-channel interference, based on which we introduce a VANET-assisted radar interference mitigation scheme, which is shown to be effective in an environment with dense traffic. Specifically, a TDMA based MAC protocol is devised that enables the coordination among vehicles on efficient multiple access of radar spectrum. Numerical results corroborate the performance gain of the proposed approach compared to the existing random frequency hopping approaches.
Hardware in the Loop Simulation for Sliding Mode Control Schemes for Deadtime Systems

This document presents the simulation for sliding mode control schemes for dead-time systems using the hardware in the loop technique. The control is applied to the temperature of a heating tank with continuous agitation. MATLAB is used as a simulation tool for the aforementioned plant, which is emulated inside a computer and receives the control actions from the Arduino microcontroller using serial communication employing the described hardware in the loop technique. The implementation specifications of the chosen controllers are also detailed
Multivariate Regression-Based Convolutional Neural Network Model for Fundus Image Quality Assessment

Objectively assessing the perceptual quality of an ocular fundus image is essential for the reliable diagnosis of various ocular diseases. A fair amount of work has been done in this field to date. However, the generalizability of the current work is limited, as the existing quality models were developed and evaluated with data-sets built with limited subjective inputs. This paper aims at addressing this limitation with the following two contributions. First, a new fundus image quality assessment (FIQuA) data-set is presented, containing 1500 fundus images with three classes of quality: Good, Fair, and Poor. Also, for each image, subjective scores (in the range [0-10]) were collected for six quality parameters, including structural and generic properties of the fundus images. Second, a new multivariate regression based convolutional neural network (CNN) model is proposed to predict the fundus image quality. The proposed model consists of two individually trained blocks. The first block consists of four pre-trained models, trained against the subjective scores for the six quality parameters, and aims at deriving the optimized features for classification. Next, the optimized features from each of the four models are ensembled together and transferred to the second block for final classification. The proposed model achieves a strong correlation with the subjective scores, with the values 0.941, 0.954, 0.853, and 0.401 obtained for SROCC, LCC, KCC, and RMSE respectively. Its classification accuracy is 95.66% over the FIQuA data-set, and 98.96% and 88.43% respectively over the two publicly available data-sets DRIMDB and EyeQ.
A 1.2V 86dB SNDR 500kHz BW Linear-Exponential Multi-Bit Incremental ADC Using Positive Feedback in 65nm CMOS

This paper presents a linear-exponential two-phase multi-bit incremental ADC (IADC). The exponential integration in the proposed IADC is generated by positively feedback the integrator output to the input, which can accumulate the signals stably due to the reset operation in IADC. To avoid the nonlinearity due to the signal-dependent charge injected from the reference, this work separates the sampling capacitor and the DAC capacitor. It will relax the requirement of reference buffer for fast-settling under a high sample rate. Then, we reconfigure the DAC capacitor to directly offer the exponential integration, resulting in saving in the usage of integration capacitor with a compact implementation. The linear-exponential two-phase scheme provides data-weighted-averaging-friendly weighting function to suppress the multi-bit DAC mismatch error. Fabricated in a 65nm CMOS under 1.2 V supply and clocked at 128MHz, the ADC achieves an SNDR/DR/SFDR of 86.02/94.6/103.03dB with 500kHz BW, 20mW & 0.26mm2, resulting in FoMs of 168.57dB.
Highly Sensitive and Stable Pressure Sensor Based on Polymer-Mxene Composite Nanofiber Mat for Wearable Health Monitoring

In this paper, we report an efficient and facile fabrication method of a highly sensitive, stable and flexible capacitive pressure sensor by sandwiching the MXene-Poly(vinylidene fluoride-trifluoroethylene) (PVDF-TrFE) composite nanofiber mat as a dielectric layer in between poly (3, 4-ethylenedioxythiophene) polystyrene sulfonate (PEDOT:PSS) flexible electrodes. The fabricated sensor exhibited superior performance, including a high sensitivity of 0.51 kPa−1, wide pressure ranges up to 300 kPa, an ultra-low detection limit of 1.5 Pa and excellent stability (>10000 cycles). Based on its outstanding performance, real-time monitoring of human physiological signals obtained from a wrist was successfully demonstrated for wearable healthcare applications.
Transdermal Drug Delivery Based on Liquid Needles Generated by Hypersonic Systems

Conventional drug delivery relies on oral uptake and injection, which may be painful and cause side effects to the patients. To overcome these drawbacks, transdermal delivery based on micro/nanoscale devices has been proposed. Here, we developed a new transdermal delivery approach using MEMS fabricated hypersonic system. The GHz resonator could locally generate high acoustic pressure in liquids and further induces ‘liquid needles’ to enhance the drug permeation to the skin. Dextran was used as the drug models for in vitro delivery through semipermeable membrane and excised rat skin. The influence of delivery time, applied power and molecular weight of drugs were investigated. The results show a good controllability and easy to operate. With the advantages of low energy consumption and miniaturization, this approach demonstrates a good alternative for current transdermal delivery system.
A Method for Eliminating False Detection Results in FM-radio-based Passive Bistatic Radar

When estimating the position and velocity of a target using an FM-radio-based passive bistatic radar (PBR). , false detection results caused by sidelobes may appear due to the structure of the FM radio signal. Since such false detections can degrade the target detection performance of PBR, a sidelobe mitigation method is required. In this paper, we analyze the sidelobe generation pattern using the main channel of the FM radio signal and then propose an algorithm to remove the false detection results on the FDOA axis. Through the simulations, we verify the effectiveness of the proposed method.
Modelling and Simulation of a Solar PV System: A Comprehensive Study

PV modules are used to directly convert solar energy into electrical energy. The essential input variables required for these modules are weather data such as solar irradiance and temperature. Output generated may be in the form of voltage, current or power which are necessary to plot and study the (P-V & I-V) characteristics of the PV modules. The outputs are immediately affected by any variation in the input variables and it is necessary to study the impacts of variation in physical data (input variables) on the power generated by the PV modules. Therefore, an accurate design of PV module is required before implementation in solar PVS. This paper presents a step-by-step designing of a PV module in detail. The configuration of PV cells considered in the design is single diode model-based consisting of series as well as parallel resistor for better accuracy. The model is step-by-step simulated and tested in MATLAB/Simulink. Behaviour of module in variable weather conditions such as solar irradiance and temperature has been studied and value of series and parallel resistance for optimum output have also been approximated.
A Mutation Framework for Evaluating Security Analysis Tools in IoT Applications

In this paper, we present an automated framework to evaluate taint flow analysis tools in the domain of IoT (Internet of things) apps. First, we propose a set of mutational operators tailored to evaluate flow-sensitive analysis tools. Then we developed mutators to automatically generate mutants for this type of sensitivity analysis. We demonstrated the framework on flow- sensitivity mutational operators to evaluate two taint flow analyzers, SaINT and Taint-Things. To the best of our knowledge, our framework is the first framework to address the need for evaluating taint flow analysis tools specifically developed for IoT SmartThings apps.
HRRP Target Recognition With Deep Transfer Learning

Recently, radar high-resolution range profile (HRRP) recognition based on convolutional neural networks (CNNs) has received considerable attention due to its robustness to translation and amplitude changes. Most of the existing methods require that sufficient labeled data with complete aspect angles be used as training data, which is a difficult task in practice. In addition, HRRP signals have a high sensitivity to the aspect angle. Therefore, the representative and discriminative powers of the features extracted from typical CNN models are reduced due to incomplete aspect angles in the training data, which significantly limit the recognition performance. This paper first considers the problem of HRRP recognition with incomplete aspect angle training data and addresses the problem by a deep transfer learning framework. Specifically, the two proposed methods enhance the recognition performance by exploring the discriminative power and the intraclass consistency with auxiliary data, which have HRRP signals with complete aspect angles. This paper generates a simulated HRRP dataset from public data to validate the proposed work. The comparisons of the recognition results demonstrate that the proposed framework outperforms the latest CNN-based models.
Model Based Trajectory Tracking Control of Nonholonomic Mobile Robots

A new trajectory tracking control scheme is proposed aiming at the problem of model parameters uncertainty and poor environmental adaptability in non-holonomic mobile robot control. Dynamic characteristics of mobile robots are considered in problem formulation. The control objective is to make the robot move along an expected trajectory with low tracking error while fulfilling its physical constraints. The proposed control scheme is implemented by a combined use of MPC algorithm and grey-box identification. Simulation results show the benefits of the systematic control methodology employed.
Controller Design and Validation for an Extended Step-Down Conversion Ratio DC-DC Converter

In this paper, the controller for an extended step-down conversion ratio converter is designed and experimentally validated through a laboratory prototype. The converter that is considered is formed by a conventional buck converter to which an array of capacitors and diodes is added at the input that allows extending the step-down conversion ratio. The objective of the controller is to provide closed-loop stability and assure the regulation of the output voltage. Its design is based on the averaged converter model and consists of two control loops, one voltage and one current. Closed-loop experimental results are presented.