Miracle-dz/UniFAR-FTUs huggingface dataset:
Evaluation of the Thermal Response of Liver Tissue Undergoing Microwave Treatment by Means of Fiber Bragg Grating Sensors

Thermal ablation procedures are gaining ever-growing acceptance in the treatment of hepatic tumors. In this context, the use of microwave ablation (MWA) has been firmly consolidated during the last decades. Being able to monitor the temperature increment within tissues undergoing MWA can be beneficial for improving the treatment outcome, especially for liver tissue which is notoriously not homogeneous and reports the presence of large vessels.In this work a multi-point temperature monitoring was performed on ex vivo liver tissue undergoing MWA. The aim was to investigate the transient phase of the tissue temperature in terms of the constant time (τ). The influence on τ of the following two aspects has been assessed: i) the blood perfusion due to the presence of a blood vessel and ii) the distance between the heat source (i.e., antenna) and the site where the temperature was measured. A power of 50 W was delivered for a treatment time of 480 s by means of a MW system. An aluminum duct providing a flowrate of 0.8 L•min-1 of water at 37 °C was inserted to mimic the presence of a blood vessel. A multi-point temperature measurement was carried out by using three fiber optics, each embedding an array of 10 fiber Bragg Grating (FBGs) sensors. The fibers were placed into the tissue sample at different distances from both the antenna and the blood vessel. The temperature variations (ΔT) recorded by the FBGs were then plotted, and τ values were calculated. The high dependence of the temperature transient dynamics on both the abovementioned distance and the presence of the vessel was found.
Determinants of Continuance Use Intention of Mobile-based Electronic Ticketing

The Mobile application provides several services in it to make it easier for users to carry out various financial transactions such as purchasing tickets, top-ups, payments, and others. However, in its application, there are still some shortcomings and problems, such as not being able to log in, crash, not update, errors that result in the low level of use of mobile applications. Seeing the existing problems, therefore, it is necessary to research to find out what factors influence reuse. The model used in this research is the extended Expectation Confirmation Model (ECM) with three added variables, which expectedly can figure out whether the use of a mobile application is following the user expectations in using a system or application is supported. This study uses a quantitative approach using SEM analysis, with 400 respondents data collected. The majority of the hypotheses in this study are stated to be significant and correlated with Satisfaction and Perceived Value as the variables that most significantly influence the reuse of mobile applications in Indonesia. The outcomes of the study are expected to drive a contributory effect on future studies.
Evaluation Index System for Autonomous Capability of the Ground-attack UAV

The evaluation of autonomous capability for ground-attack unmanned aerial vehicle (UAV) comes from the demand of troops. The level of autonomous capability determines the operational use of man-machine authority, such as allocation time, allocation content and allocation amount. Constructing a scientific evaluation index system is the first task to evaluate autonomous capability. Based on the analysis of airborne equipment system, 31 airborne equipment parameters are selected as the underlying indicators for autonomous capability evaluation from four aspects of observation capability, decision capability, action capability and security capability(ODAS),which provide the standard for the effective man-machine authority division.
Random Forest Classification of Finger Movements using Electromyogram (EMG) Signals

One of the fundamental problems in the development of prosthetic fingers is the recognition of finger movements using surface electrocardiogram (EMG) data. Most of the previous studies have proposed the classification of EMG signals using features curated using expert knowledge. We here consider automatic generation and selection of EMG signal features without relying on domain knowledge. We then develop a classification method based on random forests. Our results show that the proposed method achieves 97.5% accuracy. We also present a discussion of the features which are important in distinguishing finger movements.
Smart Nanoscopy: A Review of Computational Approaches to Achieve Super-Resolved Optical Microscopy

The field of optical nanoscopy, a paradigm referring to the recent cutting-edge developments aimed at surpassing the widely acknowledged 200nm-diffraction limit in traditional optical microscopy, has gained recent prominence & traction in the $21^{\mathrm {st}}$ century. Numerous optical implementations allowing for a new frontier in traditional confocal laser scanning fluorescence microscopy to be explored (termed super-resolution fluorescence microscopy) have been realized through the development of techniques such as stimulated emission and depletion (STED) microscopy, photoactivated localization microscopy (PALM) and stochastic optical reconstruction microscopy (STORM), amongst others. Nonetheless, it would be apt to mention at this juncture that optical nanoscopy has been explored since the mid-late $20^{\mathrm {th}}$ century, through several computational techniques such as deblurring and deconvolution algorithms. In this review, we take a step back in the field, evaluating the various in silico methods used to achieve optical nanoscopy today, ranging from traditional deconvolution algorithms (such as the Nearest Neighbors algorithm) to the latest developments in the field of computational nanoscopy, founded on artificial intelligence (AI). An insight is provided into some of the commercial applications of AI-based super-resolution imaging, prior to delving into the potentially promising future implications of computational nanoscopy. This is facilitated by recent advancements in the field of AI, deep learning (DL) and convolutional neural network (CNN) architectures, coupled with the growing size of data sources and rapid improvements in computing hardware, such as multi-core CPUs & GPUs, low-latency RAM and hard-drive capacities.
Classification of the Mask Augsburg Speech Corpus (MASC) Using the Consistency Learning Method

This paper presents the details of our solution for the mask sub-task of the INTERSPEECH 2020 Computational Para-linguistics Challenge (ComParE). The speech production can be significantly affected when the speaker wears a face mask. The task evaluates the systems for the classification of speech recordings with and without a surgical mask. A student-teacher deep-learning neural network is proposed inspired by the wellperformed consistency learning method on a lot of classification problems. In particular, the consistency regularization term is designed between out-puts of the student model and the guided teacher model. Different level Gaussian noises are respectively added into the inputs of the teacher model as model perturbations to optimize the system robustness. To take further advantage of the consistency learning, a small number of unlabeled evaluation data is utilized to be combined with the labeled data for the system training in a semi-supervised learning manner. Finally, the proposed system achieves an unweighted average recall up to 72.50% on the official evaluation dataset, increasing by 10% compared with the baseline result of 62.60%.
Laser ReSeal – Combination of Accelerometer and Gyroscope Sensors in a Single MEMS Chip Silicon Wafer Processing Technology for Six Degrees of Freedom in Inertial Sensors

"Laser ReSeal", a novel innovative combination of laser and semiconductor technology for Micro Electro Mechanical Systems (MEMS) allows the cost efficient fabrication of small, high performance and low power inertial measurement units (combined accelerometers and gyroscopes). The new process solves the intrinsic challenge since these two sensor types require two different operating pressures within one wafer. The laser hermetically seals the sensor cavity of the gyroscope, thus enabling a precise subsequent adjustment of the optimum operating pressure.
Tough biodegradable chitosan–gelatin hydrogels via in situ precipitation for potential cartilage tissue engineering

Tough porous chitosan–gelatin (CG) hydrogels have been prepared through in situ precipitation with tunable porosity and degradation rates by adjusting the preparation formulations. Compression tests showed a Young's modulus of 3.25 MPa and a compressive strength of 2.15 MPa for the optimized C4G4 hydrogels, which are similar to or higher than those for human cartilage. Cyclic compression tests showed overlapping hysteresis loops for several cycles, with a compressive toughness of about 75.8 J m−2. In vitro enzymatic degradation results showed a degradation of 65.9% in 70 days, comparable to the regeneration rate of engineered cartilage reported in literature. Moreover, in vitro cell culture experiments showed excellent adhesion and proliferation of human thyroid cartilage cells on these hydrogels, where the chondrocytes function to secrete ECM. These tough and biodegradable hydrogels may have potential applications for cartilage tissue engineering.
Stationary LIDAR Sensors for Indoor Quadcopter Localization

Mobile robots need autonomous navigation, which cannot be fulfilled without proper localization. Today, there are various techniques for map creation and localization. However, most of them are not adequate for smaller devices, like quad-copters. In this paper, lightweight, small, and efficient stationary lidar sensors are proposed for localization. Through measurements and simulations, different sensor setups are investigated in the view of map creation quality and localization accuracy. Finally, the optimal sensor setup is presented with a minimal set of sensors, while the performance is still adequate.
Titania solid solution nanoparticles co-doped with niobium and gallium

Anatase-type titania nanoparticles co-doped with niobium and gallium (GaXTi1−2XNbXO2 solid solutions in the range of X = 0–0.20) were formed from precursor solutions of TiOSO4, NbCl5, and Ga(NO3)3 under hydrothermal conditions at 180°C for 5 h using the hydrolysis of urea. The effect of dopant materials on the structure, crystallite growth, photocatalytic activity, and phase stability of anatase-type TiO2 was investigated. The lattice parameters a0 and c0 of anatase slightly and gradually increased with increase in niobium and gallium content doped into TiO2. The anatase solid solutions doped with niobium and gallium (X = 0.10–0.15) showed good photocatalytic activity. Co-doping niobium and gallium into TiO2 shifted the anatase-to-rutile phase transformation to lower temperature. The temperature range of the anatase-to-rutile phase transformation for the GaXTi1−2XNbXO2 solid solutions became narrower than that for pure TiO2. The rutile-type GaXTi1−2XNbXO2 solid solutions were formed via the phase transformation.
Practical Diversity Design for PCB IoT Terminals

Mobile or nomadic diversity antennas feature a variety of element types and layouts, mostly PCB-based, reflecting complex design trade-offs between their performance and the required compactness. The design stage is electromagnetic-based but must include several signal-based diversity metrics, and there is a shortfall of information about their assumptions and the impact of their violation. The evaluation stage normally includes simulation, with physical measurements being the bottom line. Pattern measurement is particularly challenging, but accurately measured patterns are critical parameters, enabling the calculation of mean gains and correlations, and the impact of different propagation scenarios. For developers, the complex set of processes for design and evaluation make it difficult to have confidence with their in-house procedures without access to independent results for a variety of antenna types. For the design stage, we review and clarify the diversity metrics, and for evaluation, a set of typical and new diversity designs implemented on printed circuit board (PCB) are also presented. The methods cover lossy antennas and the expected performance in a directional propagation scenario. This information helps designers and developers to better understand the design process and to check their evaluation procedures.
An Airplane Stabilization Control by H-Inf Approach

The article considers a problem of stabilization of the aircraft, which can be solved by finding a $H^{\infty}$ output control. Sufficient conditions for $H^{\infty}$ - output control for linear dynamic systems are obtained. Two approximate methods of estimating the quality of closed-loop systems are proposed. The first one is based on finding a pseudo-inverse matrix of the linear measuring system model. The second one is to synthesize an asymptotic observer, which enables formulating an estimate of a state vector, allowing further use of the obtained estimate in finding the control. The paper contains a step-by-step algorithm of finding a $H^{\infty}$ -control of a closed-loop system. It is shown that both of the proposed methods allow to ensure the desired quality of transient processes and asymptotic stability of a control system. Suggested approximate methods can be applied to aircraft control problems as well as autopilot design problems.
Generalized Benford’s Law for Fake Fingerprint Detection

Human fingerprints are considered to be the most extensively used modality in state-of-the-art biometric based security systems. A newly developed potential threat occurs in the form of specialized fake fingerprint, known as the double-identity fingerprint which is created by careful alignment of two genuine fingerprints to ensure smooth ridges at the intersection points and with high chance of being matched by the criminal as well as accomplice. In this paper, we propose a countermeasure to resolve this problem with generalized Benford’s law in conjunction with support vector machine classification. The generalized Benford’s law is found to validate the probability distribution of first nonzero digits from block-DCT coefficients of genuine fingerprint images. The experimental results support that the synthesized fake double-identity fingerprints do not inherently follow the generalized Benford’s law and hence the proposed method can be effective to discriminate from the genuine class with high accuracy.
Spaceborne Atmospheric Radar Technology Development

Spaceborne atmospheric radar technologies have been developed at the NASA Goddard Space Flight Center (GSFC) in collaboration with Northrop Grumman Corporation (NGC). This paper gives an overview of future spaceborne radar concepts and key technologies targeted for large satellite platforms, the International Space Station (ISS), and SmallSat applications.
A Beamforming Signal-Based Verification Scheme for Data Sharing in 5G Vehicular Networks

Vehicle-to-Everything (V2X) communications are vital for autonomous vehicles to share sensing data about the surrounding environment, particularly in non-line-of-sight (NLOS) areas where the camera and radar systems often perform poorly. However, an insider adversary such as a compromised vehicle can disseminate false sensing data that even a signature scheme cannot counter. Trusting such shared data, the surrounding vehicles may be trapped to react unexpectedly and potentially poses the risk of a fatal crash. In this work, we introduce a prospective cooperative verification scheme to support both the host vehicles and V2X edge applications in validating the truthfulness of sharing data in the fifth-generation (5G) vehicular networks. First, the detection systems at the host vehicle (local detector) and the road-side unit (RSU) (global detector) separately recreate a trajectory of a target vehicle by extracting its status and attributes from the received Cooperative Awareness Messages (CAM). Simultaneously, they also build another trajectory of the vehicle by independently fusing real-time measurement metrics from signal-based positioning. We then perform a Student’s t-test to detect any significant differences between the extracted trajectory and the corresponding measured one. Finally, the quantified evidence from the local and global detector tests will be fused through the Dempster-Shafer fusion for the final decision, i.e., whether the target vehicle is trustful. Besides the theoretical analysis of basic limits, we perform extensive evaluations of the work in cases of both sparse and heavy traffic densities. Through the simulation, this work demonstrates its significant effect in terms of detection performance and response time, particularly for detecting Sybil and false data attacks quickly.
Fluorescence sensing of biological tissue structures using Mn-doped CdS nanoparticles as biomarkers

The present paper describes the growth, absorption and photoluminescence spectra of Mn-doped cadmium sulfide nanoparticles, and application of nanoparticles for cellular imaging. Formation of CTAB-coated CdS:Mn nanoparticles is monitored by optical methods. The optical absorption edge of CdS:Mn nanoparticles is shifted to the higher-energy side as compared to bulk crystals due to the quantum confinement effect. TEM images demonstrate that the average size of CdS:Mn nanoparticles embedded into gelatin matrix is larger than the one of CTAB-coated nanoparticles. The changes of the optical density during the process of the nanoparticles growth are attributed to the increase of their density in the solution. The effects of coverage layer in the PL properties nanosensors are studied by the photoluminescence method. Interactions between CdS:Mn NPs and organic molecules are probed by photoluminescence method, and the results obtained are used for identification of the Kupffer's cells in the histologic specimens of liver.
Photoplethysmogram Signal Quality Evaluation by Unsupervised Learning Approach

Photoplethysmography (PPG) is gradually becoming popular tool for cardiovascular and respiratory function monitoring under ambulatory condition. However, these measurements are prone to motion artifact (MA) corruption, and hence, signal quality assessment (SQA) is essential before computerized analysis. The published research on PPG SQA, mostly utilizing supervised learning approaches, suffer from the universality of feature selection against PPG morphology variability. Secondly, beat detection from the MA corrupted is a challenging task and partly limits the success of SQA utilizing beat segmenting approaches. The present research describes an unsupervised learning approach for identification of ‘clean’, ‘partly clean’ and ‘corrupted’ segments in the MA contaminated PPG data. Few entropy features and some signal complexity related features calculated by statistical methods in a 5 s window were fed to a self-organizing map (SOM) for direct quality assessment of PPG data. The number of input node to the SOM was 7 and the output was connected to a square matrix consisting of 25 nodes. The multiclass classification model achieved 94.10%, 89.27%, 92.67% accuracy score for the three classes respectively on 200 min of PPG data collected from 30 healthy and CVD human volunteers under mild to high level of hand movement. The model achieved better result than recently published work utilizing non-segmenting approach based PPG SQA.
Event-triggered based consensus control for a type of multi-agent systems

In this note, the consensus control problem has been researched for a type of leader-follower multi-agent systems by using the event-triggered strategy. In order to eliminate continuous information transmission between the neighboring agents or nodes, the consensus controller is constructed by using the estimated state information of neighboring agents instead of their real states. The communication instants are determined by the developed event-triggered strategy to minimize the amount of communication between neighboring agents. A type of error convergence analysis based on Lyapunov function has been provided to prove the bounded convergence of the proposed consensus scheme. Finally, a simulation case is given to verify the effectiveness of the given event-based consensus control strategy.
THz-Wave Power Multiplication by Parallel-Connection UTC-PDs

We investigated an enhancement of a THz wave at two types of photomixer/antenna configurations. While arrayed antennas each of which has a photomixer lead to a power concentration into a desired direction, an antenna which has photomixers in parallel provides an isotropic multiplication. We combined these two configurations to make four-channel arrayed antennas each of which has two UTC-PDs as photomixers. Using two channels of the integrated device, we demonstrated that the peak power of the THz wave at 300 GHz was increased by 11 dB compared to a single photomixer/antenna configuration.
Transmit Signal and Receive Filter Design of PMCW Radar with Low-Resolution ADC : (Invited paper)

In this paper, we consider the problem of transmit signal and receive filter design for a phase modulated continuous wave (PMCW) monostatic single-input single-output (SISO) radar system when low-resolution analog-to-digital-convertor (ADC) is used at the receiver. By applying Bussgang decomposition model, the effect of low-resolution ADC is considered in the model, and two cases of colored and white noise are investigated. In the white noise case, it is concluded that the matched filter (MF) is the best filter maximizing the signal-to-interference-plus-noise-ratio (SINR) of the receive filter output. In the presence of colored noise, we propose a cyclic design procedure for maximizing the output SINR. Numerical examples illustrate the superiority of the proposed method in comparison with the well-known m- sequence probing signal with matched or designed receive filter. The effect of different parameters is also verified.
Analysis of the Technology of Transfering a Three-Dimensional Model from Cad Format to the Control Code For 3D Printing

The paper analyzes the technology for translating a three-dimensional model from a CAD format into a control g-code for subsequent three-dimensional printing. The main stages of the process are considered, the principles of mathematical modeling at the stages are highlighted, recommendations for possible improvement of the software part of the 3D printing technology are indicated.
A Survey on Heating Effects of Electromagnetic Radiation on Human Body

The upsurge in technology has led to the higher amounts of electromagnetic waves in the earth atmosphere. This excess quantities of electromagnetic radiation (EMR) in the atmosphere can lead to health hazards in living creatures. Influence of EMR on each component of the ecosystem depends upon its physical characteristics. One of the major effects that occurred on human beings due to the continuous exposure of EMR is the thermal heating of body tissue. This will affect the normal working of different organs within the human body. This paper discusses the heating effect of EMR based on different studies.