Miracle-dz/UniFAR-FTUs huggingface dataset:
Deep Learning Assisted Rate Adaptation in Spatial Modulation Links

The adaptation of Spatial Modulation based links to the channel conditions is challenged by the complicated dependence between performance (either error rate metrics or theoretically achievable rates) and the multiple antenna channel description. In this paper a coding rate selection mechanism is presented based on a carefully selected set of channel features and the proper training of a deep neural network, which all together can satisfy a given error rate bound.
M-Net: A Novel U-Net With Multi-Stream Feature Fusion and Multi-Scale Dilated Convolutions for Bile Ducts and Hepatolith Segmentation

Automatically segmenting bile ducts and hepatolith in abdominal CT scans is helpful to assist hepatobiliary surgeons for minimally invasive surgery. High-deformation characteristics of bile ducts and small-size characteristics of hepatolith make this segmentation task challenging. To the best of our knowledge, we make the first attempt to simultaneously segment bile ducts and hepatolith in this paper. Inspired by U-Net, a novel two-dimensional end-to-end fully convolutional network named M-Net is designed to implement this segmentation task. The M-Net is composed of four streams involving two encoder-decoder processes. Multi-scale dilated convolutions are designed to extract abundant semantic features and multi-scale context information at different scales. To make full advantages of multi-scale feature maps, a multi-stream feature fusion strategy is proposed to transfer the most abundant semantic features produced in the first stream to the other streams. To further improve the segmentation performance, a novel loss function is defined to focus the M-Net on hard pixels (difficultly distinguished) in the edges of bile ducts and hepatolith, which is based on the online bootstrapped method and cross entropy. By discarding pixels (easy to distinguish) with higher probability of class, the decline of loss is focused on hard pixels so that the training become more efficient and directional. Experimental results indicate that our proposed M-Net is superior to the state-of-the-art deep-learning methods for simultaneously segmenting bile ducts and hepatolith in the abdominal CT scans. The M-Net can simultaneously segment bile ducts and hepatolith in abdominal CT scans at a high performance with 98.678% Recall, 84.427% Precision, 89.831% DICE and 90.998% F1-score for bile ducts, and 99.894% Recall, 55.132% Precision, 71.248% DICE and 71.051% F1-score for hepatolith.
A Multivariate Correlation Assessment of Chess Proficiency Using Brain Signals

Chess game has attracted the interest of many academic works with several experiments carried out to address the differences in brain activation on proficients and non-proficients chess players. However, none of these works takes into account explicitly the cognitive patterns of the chess players to rank and classify them. In our work, we aim to present a cognitive model, using EEG and multivariate statistical methods, to assess chess volunteers and compare their performance to the traditional metric based on accuracy and response time. In total, 32 volunteers have participated in this study based on visual stimuli computationally generated. Our main results show that it is important not only to top rank the volunteers with high accuracy and low response time, but also understand how the main brain processes occur to a chess expert to achieve such top performance.
Palladium Hydrogen Sensor with Perfectly Aligned and Highly Uniform Nanogap Arrays

This paper reports a Pd hydrogen gas sensor that uses perfectly aligned uniform nanogap arrays. Depending on the nanogap size, the sensor can differentiate hydrogen concentration thanks to the volume expansion of Pd. The fabrication method of the sensor is based on conventional semiconductor processes; thus, perfectly aligned uniform nanogap arrays can be easily obtained. The standard deviation of the measured nanogap widths was less than 5 nm, and this level of uniformity has not been previously demonstrated in Pd-switching-type sensors. The fabricated sensors with the uniform nanogap array showed abrupt switching characteristics when they were exposed to H2 concentrations over a certain threshold level. Furthermore, based on the unprecedented high uniformity of the nanogap widths, a fine modulation of the threshold level of the H2 concentrations was firstly demonstrated.
Using the Embedded Ceramic Dielectric Cylinders to Improve the Signal Integrity of Via Transition

High dielectric constant (high K) ceramic material are widely used in the multilayer PCB (printed circuit board) to enhance the capacitance of inner layers to achieve the purpose of high frequency decoupling or mitigating SSN (simultaneous switch noise). In this paper, the influences of high K material on the signal integrity of via transition were researched. First of all, The S-parameters of via transition passing through a pair of power/ground planes sandwiched with high K substrate were analyzed by numerical simulation method. Then two improved method using one or more high K ceramic cylinders were proposed and investigated. The obtained results demonstrated that the high K substrate between power/ground planes will cause serious resonant phenomenon and SI issue; the methods of embedding one or more ceramic cylinders surrounding a via can efficiently improve the SI performance when the dielectric constant of cylinder is high enough.
Is South Africa ready for a national Electronic Health Record(EHR)

2 Chapter 1 . 5 Problem Statement . 8 Objectives . 8 Importance of the study . 8 Overview . 9 Chapter 2 . 10 Introduction . 10 What are the benefits of implementing an EHR? 11 What are the barriers of implementing an EHR? 12 Cost of implementing an EHR . 14 Patient Identifier . 17 Medical Records . 19 Privacy and confidentiality . 26 Resistance . 28 Chapter 3 . 3
3D Printable Vacuum-Powered Soft Linear Actuators

Soft robots which are made of highly deformable materials are ideal to operate in unstructured environments and to interact safely with humans. This work presents directly 3D printed linear soft vacuum actuators (LSOVA), that are manufactured in a single step without requiring any post-processing and support material, using a low-cost and open-source fused deposition modeling 3D printer. LSOVA have multiple advantages such as high bandwidths (~6.49Hz), high output forces (~27N) and long lifetimes (~21,500 cycles). Finite element models and analytical models are developed to accurately predict the performance of LSOVA in terms of blocked force and linear stroke. The LSOVAs can be directly used in diverse soft robotic applications such as soft artificial muscles, soft prosthetic fingers for prosthetic hands and soft adaptive grippers for gripping applications.
Wide Bandwidth Dual Port, Dual Sense Circular Polarization Antenna for Satellite Applications

This paper presents a large bandwidth dual-sense-of circular polarization (CP) patch antenna working at X-band. The radiating element is suspended in air by three pins that are sequentially-fed to provide robust CP. The antenna feed network can switch from left-handed CP (LHCP) to right-handed CP (RHCP) on the base on the connected port and, being compact, can be placed at the back of the antenna ground plane. Furthermore, to minimize the cross-polarization at low elevation angles, the so called “monopole fence”, positioned around the metallic patch element, was proposed and designed to improve cross-polarization and to reduce the on axis gain for a wide beam-width.
A Super-Flexible and High-Sensitive Epidermal sEMG Electrode Patch for Silent Speech Recognition

Surface electromyography (sEMG) signals generated by the muscles of the lower jaw contain corresponding voice information when talking. However, it's very hard to collect sEMG signals from the jaw because of not only the weakness of the signals but also the sharp skin curvature of this area. This paper reports a super-flexible and high-sensitive epidermal sEMG electrode patch to measure sEMG signals of the jaw from which the voice information can be extracted for speech recognition. This epidermal sEMG patch can be effectively attached to the jaw and the interconnection wire in the form of double wave can stretch more than 100%. From the characteristic of envelopes of the signals, it shows good consistency when the tester speak the same word and obvious difference can be detected when the tester speak different words. Four-layer wavelet decomposition is used to reduce noise in sMEG records and the eigenvectors are extracted from wavelet coefficients to characterize each trial. The experimental result shows that the average accuracy of the three pronunciations is about 71.7%. The accuracy of “hello” reaches up to 91%. In the future his epidermal sEMG electrode patch has great potential for the application of silent speech recognition.
Planar Transitions from Substrate Integrated Coaxial Line to Single-Layer Transmission Lines and Waveguides

This paper presents inline transitions from substrate integrated coaxial line (SICL) to microstrip line, coplanar waveguide (CPW), as well as substrate integrated waveguide (SIW). A common property is the conversion of transmission medium from double to single substrate layer of PCB. The first two of described transitions can be used from DC up to the presence of higher order modes if the characteristic impedances of two meeting transmission lines are matched. The transition to substrate integrated waveguide is of higher complexity, yet compact. Both sides of the SICL-SIW transition are strongly coupled to resonant cavity, and return loss greater than 20 dB is achieved in fractional bandwidth of 10.91 %. Improvements compared to the existing solutions have been made in designs of all three transitions.
Defect creation and Diffusion under electric fields from first-principles: the prototypical case of silicon dioxide

In this paper we study the effect on the electric fields on the formation of bulk Frenkal Pairs and on the migration of oxygen interstitials, IO, and oxygen vacancies, VO, within the framework of Density Functional Theory and Modern Theory of Polarization. At typical OXRRAM field conditions, We show that a significant effect of the electric field is observed only for charged defect. Analyzing the polarization work, we found anomalously high polarization work, for the case of $\mathbf{I}_{\mathcal{O}}^{-2}$, with respect to the classical picture of the electric work of an isolated point charge. This large difference has to be ascribed to collective contributions coming from the environment.
Backward Stochastic Differential Equations on Markov Chains with Non-Lipschitz Coefficients

In this paper, we study the well-posedness of stochastic systems whose state processes are governed by a class of backward stochastic differential equations related to finite state, continuous time Markov chains. We establish the existence, uniqueness of solutions for these equations under non-Lipschitz conditions. The results play a crucial role in optimal stochastic control in random environment and also can expand the applications.
Unmanned Aerial Vehicle Meets Vehicle-to-Everything in Secure Communications

Enabling vehicles to communicate with other vehicles, infrastructure, pedestrians, and everything for use cases such as road safety, automatic driving, and infotainment is important for the future cellular networks. However, some vehicle-to-everything (V2X) services need secure transmissions and should be prevented from eavesdropping. Physical layer security, an information- theoretical framework, utilizes the randomness of underlying channels to ensure secrecy in the physical layer. Different from ground communications, unmanned aerial vehicles (UAVs) create line-of-sight connections to vehicles and mobile users making them an ideal platform to conduct physical layer security strategies. In this article, we embrace UAV to V2X communications to enhance the V2X security from the physical layer security's perspective. To be specific, we present security problems in V2X systems, highlight security threats in V2X networks, and illustrate some potential applications of UAVs in V2X security. Open problems for UAV-assisted V2X secure communications are also discussed.
Learning Objects and Experiments for Active Disturbance Rejection Control

The paper introduces examples of learning objects dealing with introductory design of controllers with integral action based on disturbance observer. This state-space based approach is presented in forms denoted as conventional state-observer based reconstruction and compensation, or newer Active Disturbance Rejection Control. Both they use the so called Extended State Observer established by extending the plant state by a new state corresponding to an equivalent disturbance. This learning objects offer students development and mastery of the relevant terminology and competencies from the related areas of modeling (including use of Matlab/Simulink), control design, observer design, initial verification by appropriate hands on experiment and possibility of an extended work supported by a remote access to processes.
On-Chip Dynamic Mechanical Measurement

In this paper, we proposed a novel method of dynamic mechanical measurement of a red blood cell (RBC) in a microfluidic channel. Although dynamic mechanical measurement in a macroscopic scale provides rich information of frequency-dependent viscoelasticity, the methods for on-chip and thus high-throughput measurement in a microscopic scale have never been established. Here, using our on-chip precise position control system for a microscopic target object, we realized periodic cell motion with a specified amplitude and frequency in the microchannel, which provided the amplitude and phase difference in periodic changes of stress and deformed shape under shear flow. Through the measurements with various frequency and amplitude, we succeeded in the evaluation of RBC viscoelasticity that depends on stress frequency and amplitude.
New network-based leader-following consensus criteria for nonlinear multi-agent systems

This paper concerns with the network-based leader-following consensus problem for nonlinear multi-agent systems. First, by thinking of network-induced delay and a consensus control protocol, a nonlinear system with sampled data is modeled. Then, a novel Lyapunov-Krasovskii functional is designed to develop the consensus criterion by applying the Wirtinger-based inequality, the method of reciprocally convex combination and the free-weighting matrix technique. Finally, an example is given to verify the theoretical results.
Design of S Band Low Noise Amplifier with on chip Spiral inductors using Indigenous 180nm Digital CMOS process

This paper presents, design and development of CMOS LNA using on chip passive spiral inductors to demonstrate the capability of Indigenous CMOS foundry for designing RF CMOS circuits for various future requirements. Fully integrated S Band LNA designed using cascode source degeneration topology in standard Logic 180 nm CMOS process to achieve optimum noise figure and gain at 2492±9 MHz band. The on wafer test has been carried out and measured results are shown in the final section.
Template Selection and Update for Biometric Recognition Systems With Nearest Neighbor Classifier

Template selection is a fundamental problem in biometric recognition systems using prototype and nearest neighbor classifier. The problem is challenging because such a small number of templates must be representative of a large amount of intra-class variations such as posture changes and lighting conditions. In addition, the templates are expected to be adaptive to small gradual or sudden changes like aging and scars. To this end, existing techniques propose to perform template update by periodically selecting new representative templates. However, they are either ineffective because selected templates are less representative, or prone to selection errors due to the presence of outliers. In this paper, we propose a novel template update framework and a robust template selection method. We use sample pass table and template pass table to accumulate information for outlier removal and representative templates selection, and further propose a novel criterion to select the optimal template set according to current templates and similarity threshold. In order to confirm the effectiveness of our method, we have carried out a number of experiments on synthetic and real datasets. The results on synthetic dataset show that our template update framework is more robust than existing ones, and at the same time, achieves a higher accuracy according to the specified performance indicator. The results on real palmprint dataset also demonstrate the superiority of our method to random selection.
A Dynamic Bayesian Recovery Algorithm for Time Series Signals from Compressive Measurements

In this paper, a dynamic sparse Bayesian learning algorithm is proposed for reconstruction of time series signals from compressive measurements. The proposed algorithm introduces correlation matrix to protect the inner correlation among signals, and recursively estimate interested parameters via online learning, which further introduces correlation between adjacent measurements batches. Experimental results showed that the proposed algorithm has much higher success rates and signal-to-error ratio than that of the traditional sparse Bayesian learning algorithm and Block-sparse Bayesian learning algorithm.
Milliwatt-Class MHz Repetition-Rate THz Source Driven by a sub-100 fs High Power Thin-Disk Laser

We demonstrate optical rectification in GaP crystals driven by a 100 W-class thin-disk oscillator, nonlinearly compressed to sub-100 fs in a multi-pass cell. In optimized conditions, we obtain a power of 1.35 mW, which is the highest average power achieved in GaP so far. Additionally, we explore the effect of temperature of the crystal down to 77 K, showing that controlling the temperature of the crystal could be a key aspect for further power scaling and for handling thermal effects that become important at such high driving powers.
Farklı Sensörlerle Yanıcı Gazların Ölçülmesi ve Dinamik Modellenmesi

In this study, lighter gases was measured with different sensors. Measurements were performed under the normal room condition according to different sampling intervals. Data sets were modeled with Matlab system identification toolbox. Generated nonlinear dynamic model was used for making prediction for gas evolution. With this study, early warning system can be proposed by generating gas evaluation models were used for some dangerous gases such as butane, methane.
Interaction's Simulation Modeling of Electric Rolling Stock and Electric Traction System

The railway transport has a significant increase potential of the transportation process energy efficiency at the realization of a variety of events for energy saving. This is due to the possibility of the efficiency's increase of the regenerative braking use on the electric rolling stock by using the perspective energy storage systems. In this article the authors provide simulation modeling results of the interaction of the electric rolling stock and the electric traction system, which were received with the help of the proposed calculation's order. The given results allow performing the analysis of the variety factors' influence, such as regenerative braking, speed of movement, train's weight on the overall energy efficiency of the transportation process, as well as in the condition of the energy storage units' use. The presented model was developed in the matrix system Matlab and was verified by the operational date about the electric rolling stock operation.
Terahertz Helical Antenna Based on Celery Stalks

Cellulose-based helices retrieved from the plant celery with a conductive poly(4-(2,3-dihydrothieno [3,4-b]-[1,4]dioxin-2-yl-methoxy)-1-butanesulfonate (PEDOT-S). A resonance close to 1 THz and a broad shoulder that extends to 3.5 THz was obtained, consistent with electromagnetic models. As helical antennas, it was shown that both axial and normal modes are present, which are correlated to the orientation and antenna electrical lengths of the coated helices. This work opens the possibility of designing tunable terahertz antennas through simple control of their dimensions and orientation.
Real-time Active Control of a Lower Limb Exoskeleton Based on sEMG

With the development of robotics, lower limb exoskeleton robots have broad application prospects in helping patients with rehabilitation. However, the current operating modes of the commercial lower limb exoskeleton robots are mostly driving the lower limb dysfunction patients for rehabilitation walking training. In this case, the patients are only passively involved, lacking voluntary participation. In this paper, by collecting the sEMG signal of the lower extremity of the exoskeleton wearer and applying deep backpropagation (BP) neural network to predict the knee and hip joint angles in real time based on the root mean square (RMS) feature of the sEMG signal, the motion intention of the wearer can be detected to control the exoskeleton. The experimental results show that the method has satisfactory real-time performance and accuracy, and can effectively improve the voluntary participation of the wearer and enhance the synergy performance of the humanexoskeleton system.
Subclavian and Vertebral Artery Angioplasty - Vertebro-Basilar Insufficiency: Clinical Aspects and Diagnosis

ABSTRA C T BACKGROUND: Percutaneous transluminal angioplasty (PTA) for significant stenosis involving the origin of the vertebral artery is now a well established treatment for selected patients when posterior cerebral arterial circulation is compromised. We demonstrate from our short and long-term results, after transluminal treatment of subclavian and vertebral artery stenosis, the feasibility and safety of treatment with balloon angioplasty and stenting. PATIENTS AND METHODS: A total of 181 patients underwent endovascular treatment and were divided into two groups. In group A, we treated patients with chronic vertebrobasilar insufficient. In this group, 21 patients with severe vertebral artery stenosis had also concomitant severe stenosis in other supra aortic arteries. In group B we treated patients with subclavian steal syndrome. In this group 21 patients presented with coexistence of severe stenosis in other supra aortic arteries. Stent patency of subclavian and vertebral artery during follow up was assessed by duplex scan and physical examination, with comparison of brachial blood pressure of both arms especially in patients with subclavian stenosis. Digital angiography was performed in available patients. Cerebral oximetry and intracranial Doppler were used to determine the group of patients that we had to treat with balloon angioplasty and stenting. RESULTS: Successful stenting was achieved in all cases. There were no complications. The primary stenting patency during follow-up (mean 8.6 months) was 98.6%. With use of intracranial Doppler we found 31 patients with higher blood flow in the basilar artery after stenting and 24 patients were found with increased brain regional oxygen saturation in the anterior cerebral artery. CONCLUSION: Endovascular treatment of subclavian and vertebral arteries with balloon angioplasty and stenting was found to be necessary in certain cases and a less invasive alternative to surgical repair. Long-term results must still be confirmed in further studies.
Terahertz generation in gallium nitride quantum wells

Terahertz emission spectroscopy was used to characterize InGaN/GaN and GaN/AlGaN quantum well structures grown along the polar $c$-axis and investigate the role of the built-in electrostatic fields in the generation of terahertz radiation. The fields were first calculated using a self-consistent $k ^{*} p$solver and compared to the magnitudes of the transient electric fields generated when the structures were excited in reflection geometry with femtosecond laser pulses.