Miracle-dz/UniFAR-FTUs huggingface dataset:
LOCAL ADDING-WEIGHT LINEAR REGRESSION FORECASTING METHOD OF CHAOTIC SERIES BASED ON DEGREE OF INCIDENCE

The defect of local forecasting method based on Euclidean distance is analyzed. On this basis, a novel method called local adding-weight linear regression forecasting method based on degree of incidence is proposed. In this method, degree of incidence, instead of Euclidean distance, is used as criterion to judge the correlation between different phase points. At the same time, the values of expressing correlation are acted on chaotic series forecasting model by means of adding-weight. It overcomes the defect of local linear regression forecasting method. Firstly, the principle and reasonability of the new method are demonstrated systematically. Then, its algorithm process is derived. In the end, this method is applied to the short-term load forecasting of power system, and get ideal results. Through analyzing and comparing, the validity of the suggested method is verified.
MRAM-Based Cache System Design and Policy Optimization for RISC-V Multi-Core CPUs

On-chip cache, being the crucial constituent of central processing unit (CPU), accounts for a pivotal portion of the system’s overall power consumption. The typical static random access memory (SRAM)-based cache is vulnerable to high static leakage power consumption, while multiple challenges encountered in scaling up its capacity. In the article, magnetic random access memory (MRAM) cache is considered as a promising candidate in Reduced InstrucTIon Set Computer-Five (RISC-V) CPU systems. After analyzing the performances of single-, dual-, quad-, and octa-core systems, a quad-core RISC-V-based CPU system with a two-level hierarchical cache structure is designed, in which spin-orbit transfer (SOT)-MRAM is adopted as the L1 private cache and spin-transfer torque (STT)-MRAM as the L2 shared cache. Details on the microarchitecture of the multi-core CPU design are provided. Energy evaluation shows that this quad-core cache system can achieve 66.4% leakage power saving and 34.5% total power saving compared to SRAM. For high efficiency of data exchange in the novel MRAM CPU systems, three types of characteristics optimizing methods are proposed. An optimized cache-coherency protocol incorporating non-inclusive policy is proposed. The quad-core system is updated by adding the coherence control module and a directory in the design scheme. The simulation results on multiple dimensions show that the policy of the hybrid MRAM memory is a promising candidate for multi-core RISC-V system, with the benefits of low power consumption and high hit rate. Finally, the peripheral circuitry and manufacturing cost for the implementation of the MRAM cache is discussed in this article.
Gauge invariance and the electric polarization field

Physical observables associated with interactions between electromagnetic radiation and charged particles are required to be gauge invariant, i.e. independent of the gauge of the field potentials. Gauge invariance implies the involvement of the electric polarization field, P(x), in electrodynamics, but leaves undetermined the transverse component P(x)⊥ which occurs in the interaction terms coupling charges to radiation. We put the Hamiltonian for non-relativistic electrodynamics into a completely general form displaying the arbitrary polarization field. The well-known Coulomb gauge and ‘multipolar’ Hamiltonian formalisms then arise as special cases corresponding to particular choices of P(x)⊥. For practical calculations some choice of P(x)⊥ has to be made, and we present a particularly useful form for neutral collection of charges, not necessarily bound, but typically appropriate to atoms and molecules. Some results concerning the independence from the arbitrary quantities of physical observables are desc.
A Standard Two Stage On-Board Charger With Single Controlled PWM and Minimum Switch Count

A novel two-stage standard battery charger having minimum switch count using a single controlled PWM signal is presented in this article for Electric Vehicle (EV) charging application. The first stage is responsible for AC to DC conversion with power factor correction (PFC) operation that consists of two switches and two diodes. The second stage is a DC-DC converter having a half bridge LLC resonant configuration along with an isolation transformer. The complete charger consists of only four switches and four diodes, which is minimum among the reported literatures. Moreover, unlike a conventional control strategy that requires multiple separate controlled PWM signals for different switches, the new control scheme manages both the PFC operation as well as constant current–constant voltage (CC-CV) optimal battery charging with a single controlled PWM signal. The detailed operation and its modeling are presented in this article. A 470 W scaled down laboratory prototype is built to validate the proof of concept. The proposed charger is tested to charge a battery set of 24 V, 30 Ah using CC-CV logic with a maximum efficiency of 97.6%. The prototype is also tested with resistive load at its rated power and dynamics results are captured. A TMS320F28335 DSP board from Texas Instrument is used for implementing the control technique.
Direct Experimental Evidence of Hole Trapping in Negative Bias Temperature Instability

Negative bias temperature instability (NBTI) in ultrathin-plasma-nitrided-oxide (PNO) based p-type metal-oxide-semiconductor field effect transistors (pMOSFETs) is investigated at temperatures ranging from 220K to 470K. It is found that the threshold voltage VT degradation below 290 K is dominated by the hole trapping process. Further studies unambiguously show that this process is unnecessarily related to nitrogen but the incorporation of nitrogen in the gate dielectric increases the probability of hole trapping in the NBTI process as it introduces extra trap states located in the upper half of the Si band gap. The possible hole trapping mechanism in NBTI stressed PNO pMOSFETs is suggested by taking account of oxygen and nitrogen related trap centers.
β-Glucan Enhances the Biocontrol Efficacy of Marine Yeast Scheffersomyeces spartinae W9 against Botrytis cinerea in Strawberries

The marine yeast Scheffersomyeces spartinae W9 is a promising biocontrol agent for gray mold caused by Botrytis cinerea in strawberries. Improving the biocontrol efficacy of S. spartinae W9 is necessary for its commercial application. In this study, different concentrations of β-glucan were added to the culture medium to evaluate its effect on the biocontrol efficacy of S. spartinae W9. The results showed that 0.1% β-glucan could increase the biocontrol effect of S. spartinae W9 against B. cinerea in strawberries and in vitro. We found that adding 0.1% β-glucan to the culture medium promoted the growth of S. spartinae W9 in wounds of strawberries, enhanced biofilm formation ability, and secreted more β-1,3-glucanase. In addition, 0.1% β-glucan increased the survival rate of S. spartinae W9 under oxidative, thermal, osmotic, and plasma membrane stressors. Transcriptome analysis revealed 188 differential expressed genes in S. spartinae W9 cultured with or without 0.1% β-glucan, including 120 upregulated and 68 downregulated genes. The upregulated genes were associated with stress response, cell wall formation, energy production, growth, and reproduction. Thus, culturing with 0.1% β-glucan is an effective way to improve the biocontrol ability of S. spartinae W9 against gray mold in strawberries.
Characterization of Increased Extracellular Vesicle-Mediated Tigecycline Resistance in Acinetobacter baumannii

Carbapenem-resistant Acinetobacter baumannii (CRAB) is the most detrimental pathogen that causes hospital-acquired infections. Tigecycline (TIG) is currently used as a potent antibiotic for treating CRAB infections; however, its overuse substantially induces the development of resistant isolates. Some molecular aspects of the resistance mechanisms of AB to TIG have been reported, but they are expected to be far more complicated and diverse than what has been characterized thus far. In this study, we identified bacterial extracellular vesicles (EVs), which are nano-sized lipid-bilayered spherical structures, as mediators of TIG resistance. Using laboratory-made TIG-resistant AB (TIG-R AB), we demonstrated that TIG-R AB produced more EVs than control TIG-susceptible AB (TIG-S AB). Transfer analysis of TIG-R AB-derived EVs treated with proteinase or DNase to recipient TIG-S AB showed that TIG-R EV proteins are major factors in TIG resistance transfer. Additional transfer spectrum analysis demonstrated that EV-mediated TIG resistance was selectively transferred to Escherichia coli, Salmonella typhimurium, and Proteus mirabilis. However, this action was not observed in Klebsiella pneumonia and Staphylococcus aureus. Finally, we showed that EVs are more likely to induce TIG resistance than antibiotics. Our data provide direct evidence that EVs are potent cell-derived components with a high, selective occurrence of TIG resistance in neighboring bacterial cells.
Design and Development of a Novel Bluetooth Based Vehicle Scanner : Perspective based on new MCUs with integrated Wi-Fi and Bluetooth

Effective traffic management and smooth traffic flow are core requirements of the smart city. Low-cost, easyto-install, and easy-to-maintain sensors for capturing traffic data on them in real-time are required to realize the dream of a smart city. With the increasing number of mobile users and the number of Bluetooth modules in automobiles, Bluetoothbased vehicle scanners are attractive. This paper offers various perspectives on the fabrication of Bluetooth-based vehicle scanners. It demonstrates the fabrication and use of a Bluetooth-based vehicle scanner based on the selection of discrete components. In light of the launch of various integrated Wi-Fi and Bluetooth development boards during 2016-2020, the development of Bluetooth vehicle scanners based on these development boards is explored for the first time in the literature. This manuscript highlights that even though there appears to be a visible reduction in hardware, the Wi-Fi and Bluetooth coexistence for field deployment can be challenging. The various development boards appear promising, yet their utility can be ascertained only after thorough field testing. Few are ruled out because they do not support simultaneous Wi-Fi and Bluetooth. In contrast, the discrete component-based Bluetooth vehicle scanner has worked satisfactorily and can be further developed into a field deployable commercial-grade sensor.
Fuzzy Adaptive Passive Control Strategy Design for Upper-Limb End-Effector Rehabilitation Robot

Robot-assisted rehabilitation therapy has been proven to effectively improve upper-limb motor function in stroke patients. However, most current rehabilitation robotic controllers will provide too much assistance force and focus only on the patient’s position tracking performance while ignoring the patient’s interactive force situation, resulting in the inability to accurately assess the patient’s true motor intention and difficulty stimulating the patient’s initiative, thus negatively affecting the patient’s rehabilitation outcome. Therefore, this paper proposes a fuzzy adaptive passive (FAP) control strategy based on subjects’ task performance and impulse. To ensure the safety of subjects, a passive controller based on the potential field is designed to guide and assist patients in their movements, and the stability of the controller is demonstrated in a passive formalism. Then, using the subject’s task performance and impulse as evaluation indicators, fuzzy logic rules were designed and used as an evaluation algorithm to quantitively assess the subject’s motor ability and to adaptively modify the stiffness coefficient of the potential field and thus change the magnitude of the assistance force to stimulate the subject’s initiative. Through experiments, this control strategy has been shown to not only improve the subject’s initiative during the training process and ensure their safety during training but also enhance the subject’s motor learning ability.
CAMERA SELF-CALIBRATION——THEORY AND ALGORITHMS

Camera self calibration is one of the fundamental issues in computer vision. This paper discusses the calibration of camera intrinsic parameters from the rotation of camera. When camera is rotated around its coordinate axis, the formulas of camera intrinsic parameters are obtained by the algebraic method. These formulas are very useful when 2D projective transformation is very close to the theoretic P. When rotational axis are unknown, the general solution of camera intrinsic parameters is obtained by the eigenvectors of 2D projective transformation. The camera intrinsic parameters could be uniquely determined through the method based on two different rotational axes. These results are the theoretic basis of the self calibration algorithm. Meanwhile a practical algorithm is provided. Tests with synthetic data and real images indicate that the algorithm presented in the paper is robust.
Transitory behavior of uncertain systems A VOLUME IN HONOR OF DIEDERICH HINRICHSEN

The notion of a transitory excursion is introduced as a measure of the distance a stable semigroup (generated by a matrix A) moves away from the origin. Various estimates for the excursion are obtained via the distance of A from the normal matrices, properties of spectral value sets of A, and time-varying Lyapunov equations. It is shown how the excursion can be improved by state feedback. Finally the notion of transitory excursion radius for uncertain systems is introduced and estimates obtained.
Design of Prepaid Energy Counter for Smart Billing System

A factor of a challenge is to limit the line at the energy meter charging counters and to confine the usage of the strength meter certainly, within the occasion that the bill isn't paid. The challenge additionally objectives offering a framework that willlessen the deficiency of force and profits because of force robberies and different crook operations. The running framework embraces an genuinely new concept of “prepaid power Counter”. The GSM innovation is utilized so the consumer could get messages about theusage of force (in watts) and on the off risk that it arrives at the bottom sum, it would clearly make the purchaser privy to re- energize. This innovation holds clearly first rate for all power dissemination corporations, personal networks, IT parks, and self- containing lodging tasks. There are clean consequences from numerous nations, in which the pay as you go framework has reduced the earnings misfortune via an substantial sum A GSM- primarily based energy Recharge Interface contains a pre-loaded card comparable to a flexible SIM card. This gives the plan and demonstration of a GSM-based strength Recharge system for paid in advance of time Metering. The present day association of electricity charging in India is mistake willing and furthermore timeand work ingesting. Errors get presented at each segment of power charging like errors with electro-mechanical meters, human errors, managing errors. The factor of the venture is to restriction the blunder through supplying another association of pay as you go energy Metering utilizing GSM. The GSM module offers a method of correspondence between the consumer/and dealer. This mayempower the consumer to re-energize his/her strength account from home. Keywords-Energy Meter, GSM Technology, Prepaid
Controlled total variation regularization for image deconvolution

To resolve the image deconvolution problem, the total variation (TV) minimization approach has been proved to be very efficient. However, we observe that this approach has an over-minimizing TV effect in the sense that it gives a solution whose TV is usually smaller than that of the original image. This effect is due to the pre-pondering role of the TV in the corresponding minimization problem and prevents from finding the exact solution of the deconvolution problem when such a solution exists. We propose a modified version of the gradient descent algorithm, which leads to an exact solution of the deconvolution problem if it exists and to a satisfactory approximative solution if there is no exact one. The idea consists in introducing a control on the contribution of the TV in the classical gradient descent algorithm. The new algorithm has the advantage that the restored image has the TV closer to that of the original image, compared to the classical gradient descent approach. Numerical results show that our method is competitive compared to some recent ones.
Accuracy Assessment of Hand-Eye Calibration Techniques in Uncertain Environments for Vision Guided Robots

The hand-eye calibration accuracy of a visionguided robot plays a huge role in the decision-making process of the robot during operation. The majority of work focuses on passive calibration where the calibration is done with a batch of data prior to putting the robot in service. In a previous study, ‘‘Accuracy evaluation of hand-eye calibration techniques for vision- guided robots, (2022) the accuracy of six commonly used passive calibration methods was investigated and showed good performance in terms of small rotation and translation errors. However, that investigation was carried out assuming no uncertainties in the robot operating environment. In this study, we extend that investigation by evaluating the accuracy of those six methods when the robot is operating in uncertain environments. By introducing changes in calibration parameters to mimic uncertain environments, the accuracy of the six methods deteriorates significantly suggesting a need to address this issue. We suggest in our future work, the probable deployment of active calibration to improve the accuracy and discuss some expectations and limitations associated with it.
Stronger Approximate Singular Value Decomposition via the Block Lanczos and Power Methods

We re-analyze Simultaneous Power Iteration and the Block Lanczos method, two classical iterative algorithms for the singular value decomposition (SVD). We are interested in convergence bounds that do not depend on properties of the input matrix (e.g. singular value gaps). Simultaneous Iteration is known to give a low rank approximation within (1 + ǫ) of optimal for spectral norm error in Õ(1/ǫ) iterations. We strengthen this result, proving that it finds approximate principal components very close in quality to those given by an exact SVD. Our work bridges a divide between classical analysis, which can give similar bounds but depends critically on singular value gaps, and more recent work, which only focuses on low rank approximation Furthermore, we extend our bounds to the Block Lanczos method, which we show obtains the same approximation guarantees in just Õ(1/ √ ǫ) iterations, giving the fastest known algorithm for spectral norm low rank approximation and principal component approximation. Despite their popularity, Krylov subspace methods like Block Lanczos previously seemed more difficult to analyze and did not come with rigorous gap-independent guarantees. Finally, we give insight beyond the worst case, justifying why Simultaneous Power Iteration and Block Lanczos can run much faster in practice than predicted. We clarify how simple techniques can potentially accelerate both algorithms significantly.
Estimation of PSD and Non-linear Entropy Parameters of FHRV

Changes observed in fetal heart rate (FHR) in response to stress induced by uterine contractions is recorded using Cardiotocography (CTG). More than three decades of research on electronic fetal monitoring (EFM) revealed that the study of FHR variability helps in assessing fetal well being during labor. Based on characteristics of FHR changes in neonatal outcomes were predicted. Research studies have not demonstrated any significant reduction in overall perinatal mortality with the use of continuous EFM. Hence, the area of FHR monitoring still faces challenges related to disagreements over the clinical interpretation of FHR, the absence of standard terminology, and significant differences in how to define and handle unsettling FHR patterns. Algorithms developed to extract various features from FHR signals help in FHR variability analysis. To determine the power spectrum density of FHR signals at various frequencies, the current work conducted a frequency domain analysis of FHR tracings. The nonlinearity in these signals due to FHR variability was measured by calculating the statistical entropy parameters of non-linearity.
Radar and Camera Fusion for Multi-Task Sensing in Autonomous Driving

Multi-modal fusion is imperative to the implementation of reliable autonomous driving. In this paper, we make full use of both mmWave radar and camera data to reconstruct reliable depth and full-velocity information. To overcome the sparsity of radar points, we leverage full-velocity based egomotion compensation to achieve more accurate multi-sweep accumulation. Besides, we incorporate an adaptive two-stage attention module within the fusion network to exploit the synergy of camera and radar information. Furthermore, we conduct extensive experiments on the prevailing nuScenes dataset. The results show our proposed fusion system consistently outperforms the state-of-the-art methods.
Design of a miniature bi-band patch antenna with asymmetrical feedline for 5G applications

Nowadays, the generalization of wireless communication systems and the need to miniaturize antennas to allow their integration into small objects at ultra-high frequencies is growing. At these frequencies, the antenna is the bulkiest component and its miniaturization constitutes one of the most important current challenges for designers of communicating objects. The main objective of our work is the design of a dual-band patch antenna working for fifth-generation systems. For this purpose, we designed a miniature antenna having two resonance frequencies, one around 7GHz and the other around 28GHz. For this, our work is based on a classic rectangular patch antenna. Miniaturization techniques and ground plane deformation (GDS) are used to obtain the best performance. A parametric study was performed to see the most influential parameters to achieve the desired requirements. The influence of the geometrical parameters of the antenna on the resonance frequency, bandwidth, and directivity has been taken into consideration. The results obtained showed a good performance of the designed antenna.
A New Overcomplete ICA Algorithm Based on Shortest Path and Nature Gradient

Independent component analysis(ICA) is a statistical methods for finding statistically independent data within given random vector,ovecomplete ICA is a special case of ICA,which gives more source vectors than observe vectors.This paper introduces a new overcomplete ICA algorithm,named Turbo-overcomplete algorithm,based on shortest path algorithm and nature gradient.Turbo-overcomplete algorithm uses shortest path method to infer source vector and nature gradient to learn the basis vector.It uses Turbo-overcomplete algorithm to separate speech signals and compares the experimental results with current ovecomplete algorithms.