Miracle-dz/UniFAR-FTUs huggingface dataset:
Loss Minimization Control of PMSM Using Gradient Descent Algorithm

In this paper, loss minimization control method (LMC) based on gradient descent algorithms (GDA) is aimed at enhancing the efficiency of permanent magnet synchronous machines (PMSMs) in high-speed operation. This approach reduces the power loss by controlling the magnitude of the torque component of the d-axis current in terms of the gradient of power loss. Besides, this kind of search-based method can avoid the influence of changes in motor parameters on control. Maximum torque per ampere (MTPA) and id = 0 control are also simulated so as to verify the effects of LMC. Compared with these two methods, the simulation results of LMC indicate that this approach could improve the efficiency of the PMSM.
An Improved Buck-Boost Circuit Equalization Method for Series Connected Battery Packs

Series-connected lithium-ion battery packs have inherent divergence of cell state of charge (SOC) and the differences will be further enlarged with repeated charging and discharging cycles, which will reduce the available capacity and lifetime. In this paper, an improved equalization circuit is proposed based on the buck-boost principle and the control simulation is implemented. The lithium-ion battery model is established and a series-connected lithium-ion battery pack balancing system with SOC as the balancing target is built. Simulation verification and comparative analysis show that comparing with the traditional buck-boost circuit, the improved design without adding any components is faster and much efficient: the time to realize the equalization is reduced and the energy utilization rate is improved.
Analysis of Modern Approaches to Optimizing Traffic Control Systems

The existing topical problems caused by the development of vehicles and increased mobility of the population are analyzed. the relevance of this analysis of modern methods of intelligent control of traffic control systems. The analysis of publications and scientific works related to the considered research topic is carried out. Modern methods and approaches of traffic light objects control are analyzed. In accordance with the structural and functional features of intersections, an approach is proposed that allows you to quickly and visually orient the researcher of a transport worker when solving problems of optimization of traffic light objects.
An Energy Efficient Channel Bonding and Transmit Power Control Approach for WiFi Networks

Future green WiFi networks will require Access Points (APs) to minimize their energy usage and maximize their spectral efficiency; equivalently, APs need to maximize their Energy Efficiency (EE). To this end, transmit power control and channel bonding are promising approaches to improve the EE of APs. However, these approaches may cause interference between neighboring APs that lead to low capacity or data rates. To this end, we first outline a Continuous Time Markov Chain (CMTC) to study an AP's channel bonding process given random traffic arrivals and interference. After that, we outline a Deep Reinforcement Learning (DRL) solution that controls when an AP uses a single or bonded channel and its transmit power. Simulation results show that an AP equipped with our DRL solution improves its EE by 40% to 560% as compared to competing solutions.
Performance Evaluation of the SRS Based MIMO Channel Estimation on 5G NR Open Source Channel Model

In 5G NR sounding reference signals are used for pilot-aided uplink MIMO channel estimation. Obtained channel responses due to channel reciprocity are processed further to compute downlink MU-MIMO beamforming vectors. The resulting performance of beamforming depends of accuracy obtained in channel response estimation. In this work typical scenario of massive MIMO deployment in the open source 5G channel model QUADRIGA is configured. Least square channel estimation based on SRS under pilot contamination from neighbouring cell are performed and MSE compared.
Research on Variable Gap Simultaneous Wireless Power and Information Transmission Method Based on Nonlinear PT Symmetry Principle

The variable gap simultaneous of wireless information and power transmission (SWIPT) is a hotspot of wireless power transmission system. Based on the single coil and dual band resonant structure, an energy transmission method is proposed by using the nonlinear gain saturation mechanism of voltage amplifier with variable transmission gap. The accurate analytical solutions of system transmission efficiency and harmonic frequency are deduced by analyzing the circuit model of the system, and the correctness of the theoretical model is verified by using a simulation method.
Enabling Terminal-Side Intelligence for Smart Meters: Design and Applications

With the increasing demand for electrical data analysis, close proximity of computational resources to the terminal side has become a priority in modern power systems considering extant weaknesses with regard to operational efficiency, data security and the increasing burden of the cloud. Nevertheless, smart meters lacks local resources as modern terminals of smart grids. On the other hand, the alternative solutions based on edge computing may be inadequate in flexibility. To this end, a device aiming to enable terminal-side intelligence for smart meters is proposed in this work. First the functional design of the device is elaborated and a prototype of it is then introduced. Finally, two typical applications of this device are illustrated respectively. In addition to the traditional functions of smart meters, the proposed device is endowed with the capability of local computing whereby it has broad application prospects in the future.
Design of a Mirror Stairs Multiband Microstrip Antenna Using Defected Structures

In this article, a suggested design of mirror stairs microstrip antenna that has a planar geometry with defected structures is presented for multiband applications. The suggested antenna generates six resonance frequencies to cover 3.965 GHz (WiMAX), 7GHz, 9.188GHz (ultra-wideband, satellite)11.664GHz (space program application), 12.956GHz (indoor high-data-rate application) and 13.861 (land mobile satellite, radio navigation application) that cover the range from 2 to 17 GHz. The suggested antenna contains five rectangular slots based upon the defected ground structure (DGS) under the transmission line feed. The middle rectangular slot works as a mirror that reflects the image of the second rectangular slot. The third slot and all the rectangular slots have the same width, whereas the top side of the suggested antenna contains three rectangular strips as patch antennas based on defected microstrip structure (DMS). The suggested antenna is designed by a simulator that depends on the finite element method (FEM). The suggested antenna is printed and fabricated on double-sided substrate material that is 1.524 mm thick with an area of 45 × 40 mm2. The simulation and measurement results prove that the suggested antenna has good input impedance bandwidths as S11 ≤ −10 dB at six operating frequencies. The measurement results display good agreements with simulation results. For study purposes, we analyze the suggested antenna and simulated results compared on bandwidth, gain, efficiency, and return loss. The resultant antenna with mirror stairs shape based on DGS and DMS has improved in parameter performance mostly enhancement in bandwidth.
Diagnostics of the State of Secondary Power Supplies Input Circuits Parameters Based on Analytical Expressions

The aviation equipment of modern aircraft in most cases has built-in sources of secondary power supply. The amplitude-frequency characteristics of the input stages of the secondary power supply have a characteristic shape, the form of which is determined by the total input impedance of the circuit. The presence of pronounced resonant points in the frequency response allows evaluating and, in the future, predicting the states (failures and changes in parameters) of electrical circuit elements based on the assessment of changes in the resonance parameters. Obtaining the frequency response allows one to predict with a certain degree of accuracy failures characterized by changes in the parameters of the technical condition and caused by wear or aging of the material of parts or components of electrical equipment. The resulting frequency response can be considered as a “digital portrait” and constantly monitor the smooth changes in the state of the secondary power supply (from aging and wear of the elements) and abrupt (in case of such failures as “short circuit” and “breakage”). It is proposed to use the analytical dependences of the measured electrical parameters on the values of the parameters of the reactive elements instead of the frequency response. The analytical equations are derived using a modification of the limit state method, which makes it possible to form differential equations for circuits with reactive elements using resistive subcircuits.
Virtual Energy Regulator: A Time-Independent Solution for Control of Lower Limb Exoskeletons

In this letter, we introduce a novel control strategy called Virtual Energy Regulator (VER) for lower limb rehabilitation exoskeletons. Unlike the conventional trajectory tracking controllers, VER, which is a time-independent controller, does not control the exoskeleton joints over a reference trajectory. Instead, it imposes a constraint to the state-space and consequently creates a limit cycle for each joint. The time-independent property of VER can resolve the human-exoskeleton coordination problem. The analytical perspectives of VER are studied in detail where we present the limit cycle existence conditions, considerations for the definition of the desired limit cycles, convergence proof, and limit-cycles synchronization. Finally, to support the presented mathematics, we apply the designed VER on Indego exoskeleton (without human) to perform a limit-cycle behavior similar to walking. The experimental and simulation results show that VER generates stable and synchronized limit-cycles at the joints. Our experimental and simulation results support our analytical findings and demonstrate the efficacy of VER for lower limb exoskeletons.
3D ego-Motion Estimation Using low-Cost mmWave Radars via Radar Velocity Factor for Pose-Graph SLAM

Achieving general 3D motion estimation for all-visibility has been a key challenge in robotics, especially in extreme environments. The widely adopted camera and LiDAR-based motion estimation critically deteriorate under fog or smoke. In this letter, we devised a unique sensor system for 3D velocity estimation by compositing two orthogonal radar sensors. The proposed configuration allowed securing returns from the static objects on the ground. This work aimed at a realistic sensor deployment in a harsh environment by casing the bare sensor rig into a plastic box. As will be shown, the proposed velocity-based ego-motion estimation presented reliable performance over existing point matching-based methods, which degraded when measurement attenuates due to the casing. Furthermore, we introduce a novel radar instant velocity factor for pose-graph simultaneous localization and mapping (SLAM) framework and solve for 3D ego-motion in the integration with IMU. The validation reveals that the proposed method can be applied to estimate general 3D motion in both indoor and outdoor, targetting various visibility and the structureness in the environment.
Missing Data Completion Based on Nonlinear Feature Space Mapping for the Power Grid

The power grid is a non-linear, highly-coupled, multi-dimensional mathematical-physical system, and its informatization is mostly dependent on empirical data. Nonetheless, this data is occasionally misplaced because of signal transmission malfunctions, sensor faults, or human errors. Retrieving these missing data is indispensable for the power system digitization, informatization, and intellectualization. This paper proposes a missing data completion method by a non-linear feature space mapping algorithm that maps nonlinearly related variables to linear space to obtain data linearly coupled with the variable, including missing data. Comparative experiments based on actual multi-dimensional grid data show that compared with multi-dimensional linear interpolation, the proposed algorithm can reduce the root mean squared error by 87.95% and the mean absolute error by 88.20% on average. And R2 is more significant than 0.99. Besides, for all dimensional variables in the data set, the proposed algorithms have relatively high accuracy. Experiments prove that this algorithm is sufficient for the application of the power grid.
The Insulation Characteristics of Optical Fiber in Transformer Oil Under Long-term Thermal Aging

Traditional methods cannot detect hot spot temperature, mechanical vibration and partial discharge signal and other state parameters of the transformer in real time. Optical fiber sensing technology has a wide range of application prospects due to its high accuracy, strong anti-interference ability and distributed measurement. However, the premise for its application is that the embedded optical fiber does not affect the safe operation of the transformer. This paper explores the interact between embedded fibers and transformers. In this paper, four different types of optical fibers were initially selected to prepare fiber-oil composite insulation. Samples under different aging time were obtained through accelerated thermal aging experiments. The mechanical strength and optical loss characteristics of fibers with different aging degrees were tested separately. At the same time, moisture content, acid value, oil chromatogram, dielectric loss factor and volume resistivity of insulating oil were tested. The results show that the mechanical strength of the PVC tight fiber decreases significantly as the aging time increases. PVC tight fiber significantly improves the dielectric loss factor, CO2/CO and total hydrocarbon content in insulating oil. The mechanical properties of the other three optical fibers remain basically unchanged and have little effect on the insulating oil. Thermal stress does not affect the optical transmission characteristics of all optical fibers. The PVC tight fiber is not suitable as the embedded optical fiber in transformers, while the other three optical fibers meet the basic requirements of the embedded optical fiber. The experimental results provide solutions for the safety risk assessment of the embedded optical fiber in transformers.
The Influence of Salp Swarm Algorithm-Based Feature Selection on Network Anomaly Intrusion Detection

Network security plays a critical role in our lives because of the threats and attacks to which we are exposed, which are increasing daily; these attacks result in a need to develop various protection methods and techniques. Network intrusion detection systems (NIDSs) are a way to detect malicious network attacks. Many researchers have focused on developing NIDSs based on machine learning (ML) approaches to detect diverse attack variants. ML approaches can automatically discover the essential differences between normal and abnormal data by analysing the features of a large dataset. For this purpose, many features are typically extracted without discrimination, increasing the computational complexity. Then, by applying a feature selection method, a subset of features is selected from the whole feature set with the aim of improving the performance of ML-based detection methods. The salp swarm algorithm (SSA) is a nature-inspired optimization algorithm that has demonstrated efficiency in minimizing the processing challenges faced in performing optimization for feature selection problems. This research investigates the impact of the SSA on improving ML-based network anomaly detection using various ML classifiers, including the extreme gradient boosting (XGBoost) and Naïve Bayes (NB) algorithms. Experiments were conducted on standard datasets for comparison. Specifically, two datasets explicitly focused on network intrusion attacks were used: UNSW-NB15 and NSL-KDD. The experimental results show that the proposed method is more effective in improving the performance of anomaly NIDSs in terms of the F-measure, recall, detection rate, and false alarm rate on both datasets, outperforming state-of-the-art techniques recently proposed in the literature.
A 36-year-old patient with acute urinary retention due to an anterior midline prostatic cyst: A case report and review of the literature

During the years, there have been no more than a few reports (with ours being so far the sixth) of prostatic cysts prolapsing into the bladder and thus causing urinary obstruction. Most of those cystic formations are generally asymptomatic and are found during random controls. In our case, the cyst was located in the anterior midline of the prostate in a 36-years-old patient presenting at the E. R with severe suprapubic pain and urinary retention after 3 months of constantly deteriorating lower urinary tract symptoms. Transabdominal ultrasonography and magnetic resonance imaging revealed a projecting prostatic cyst that like a valve was blocking the bladder neck at 12 o'clock position. It was successfully removed by transurethral resection leaving the patient free of symptoms.
Green and sustainable membrane fabrication development

To meet the present demands of environmental protection, resource efficiency, and specific separation under severe conditions, continued research and enhancement of membrane technology is necessary. One of the major innovations for improving the sustainability of separation processes has been the use of green solvents for membrane preparation. In this regard, environmentally friendly methods and preparation techniques for high-performance membranes have recently been developed. This article gives an overview of current advancements in polymeric membrane manufacturing processes in terms of environmental preservation and health safety.
A Complexity Study for Interleaving Search

We study the worst-case time complexity of relational programs for the canonical implementation of miniKan-ren. We propose a model that breaks the evaluation time in miniKanren into several different parts and provides methods to estimate the complexity of these parts. These methods can be combined into an approach for analyzing the complexity of recursive relations using the ideas originating from symbolic execution. Our approach puts a number of limitations on the program being analyzed but we show that is still practically applicable by applying it to a number of typical relations in miniKanren.
Influence of Movement Energy and Affect Priming on the Perception of Virtual Characters Extroversion and Mood

Movement Energy – physical activeness in performing actions and Affect Priming – prior exposure to information about someone’s mood and personality might be two crucial factors that influence how we perceive someone. It is unclear if these factors influence the perception of virtual characters in a way that is similar to what is observed during in-person interactions. This paper presents different configurations of Movement Energy for virtual characters and two studies about how these influence the perception of the characters’ personality, extroversion in particular, and mood. Moreover, the studies investigate how Affect Priming (Personality and Mood), as one form of contextual priming, influences this perception. The results indicate that characters with high Movement Energy are perceived as more extrovert and in a better mood, which corroborates existing research. Moreover, the results indicate that Personality and Mood Priming influence perception in different ways. Characters that were primed as being in a positive mood are perceived as more extrovert, whereas characters that were primed as being introverted are perceived in a more positive mood.
Assessing the Psychometric Properties of Hindi Version of Relationship Structure (ECR-RS) Scale among Young Adults

Relationship science has proliferated in the last few years. However, most of these studies have remained focused on western culture. An important reason for the lack of relationship studies in the non-western, particularly Indian context, is the lack of culturally validated scales. The present study was aimed at assessing the psychometric properties of the relationship structure (ECR-RS) scale. ECR-RS is a nine-item questionnaire used to measure attachment patterns for different relationships. It has been translated and modified in multiple languages. The study (N = 223, undergraduate students, 32.7% females) evaluated the Hindi version of ECR-RS scale’s psychometric properties for mother, father, close friend, and global attachment. The confirmatory factor analysis supports the presence of the two-factor model as originally theorized in ECR-RS. The findings support the reliability and validity of Hindi ECR-RS. The study contributes methodologically by providing an instrument of attachment styles, which could be a valuable resource for practitioners and researchers in the Indian context.
Analysis of External Debt Sustainability in Mongolia: an Estimated DSGE Approach

In this study, we assess the effects of the structural shocks on the external debt sustainability in Mongolia, based on an estimated small open economy (SOE) dynamic stochastic general equilibrium (DSGE) model with the traded, the non-traded, and the mining sectors. The impulse response results show that the traded sector’s productivity shock, the commodity price shock, the mining output shock, and the foreign interest-rate shock have a decreasing effect on external debt accumulation in Mongolia, whereas the non-traded sector’s productivity shock, the household preference shock, and the government spending shock have an increasing effect on the same. Furthermore, we assess Mongolia’s external debt sustainability under the COVID−19 pandemic shock. Under our assumed pandemic scenario, Mongolia’s external debt will increase by 30% from its steady state over the next 10–28 quarters. Our recommended solution in this study is to develop the traded sector, instead of the mining sector, to maintain sustainability of the external debt and to decrease vulnerability of the economy.