Miracle-dz/UniFAR-FTUs huggingface dataset:
Indoor Pedestrian Positioning Method Based on Pelvic Motion Model Using Inertial Sensors

Indoor positioning technology has been widespreadly studied by researchers at home and abroad. The sensor located at pelvis is used to estimate the location of human by acceleration. The existence of the acceleration error will lead to the increasing position error after double integrations. Step length algorithm using foot-mounted inertial sensor need to use Zero Velocity Update (ZUPT) method to reset velocity in order to reduce accumulated error. In this paper, we propose a new position method based on the pelvic motion model. The center of the pelvic is selected as the root point. The five sensors are located at the shank, thigh and the pelvis to measure the kinematics of the lower limbs. First, the coordinate values of the left and right knee joints are calculated by the rotation matrix. The roll obtained from the sensor attached to the shank is used to estimate the horizontal distance from the ankle to the knee joint. The yaw is used to estimate the heading of pedestrian. Finally, the position is determined by step length and heading information. The proposed method and the conventional method are tested in two scenarios: rectangular motion and straight-line motion. The experimental results show that the proposed position estimation method has higher position accuracy indoors.
Near-Optimal Decoding of Incremental Delta-Sigma ADC Output

This paper presents a nonlinear digital decoder (reconstruction filter) for incremental delta-sigma modulators. This decoder utilizes both the magnitude and pattern information of the modulator output to achieve accurate input estimation. Compared to the conventional linear filters with the same oversampling ratio (OSR), it can improve the converter’s signal-to-quantization noise ratio by a few dB to a few 10’s of dB with slight thermal noise performance degradation. Using the proposed decoder, the modulator’s OSR can be a few times less while achieving the same resolution and data rate, thus minimizing the modulator as well as its peripheral circuits’ energy consumption. In this paper, the proposed decoder is optimized for digital implementation, with its function being verified using a modulator prototype. This decoder is mainly designed for dc or near-dc signal conversions and it does not provide frequency notches.
On Task-Specific Redundant Actuation of Spring-Assisted Modular and Reconfigurable Robot

Modular and reconfigurable robots (MRRs) are unique and highly versatile for their self-innovation potential. Multiple working mode (MWM) on-line control adds potential by enabling each spring-assisted MRR (SA-MRR) joint module to switch independently between primary (motor-only) mode, and secondary, redundant actuation (spring-assisted) mode. In this work we proposed the spring-assisted mode as an on-board, physical innovation aid for uncertain, task-critical manipulation acts in uncontrolled environments. The spring-assisted mode is characterized by synergy of the spring and motor energy, and strengthens the SA-MRR by complementing the net actuation effort to help overcome task failure, to improve competency at ordinary tasks, and to enhance SA-MRR suitability as a tool for new tasks. Spring modules are fully reconfigurable offline through component swapping, and human–robot collaboration safety is considered. Task-specific, physical innovation with the SA-MRR was investigated by applying the spring-assisted mode directly to strenuous task segments in simulation case studies, demonstrating effectiveness of the proposed MWM approach.
Power–Efficient Grid Voltage Waveform Conditioning via Feed–Forward Compensation

The transformation from an unidirectional to a bidirectional electricity infrastructure brings new challenges regarding the quality of the electricity service. One of these challenges concerns the quality of the voltage waveform. Due to high concentrations of power electronics such as photovoltaic inverters, the voltage waveform can become distorted beyond the limits stated in the network code. Apart from exceeding the network code, a low quality voltage waveform can affect electric appliances. It also negatively influences the current waveforms, further straining the voltage waveform quality. To enable conditioning of the voltage waveform, a series voltage compensator is proposed. Two control objectives are defined for the voltage compensator controller. The main objective addresses the tight quality limits to which the voltage waveform has to comply to. Additionally, a power and budget efficient solution is proposed and validated. Real–time low voltage experiments are performed on a fully functional voltage compensator.
A 56-to-66 GHz CMOS Low-Power Phased-Array Receiver Front-End With Hybrid Phase Shifting Scheme

This paper presents a millimeter-wave phased-array receiver front-end with compact size and low-power consumption. A combination of local oscillator (LO) and radio frequency (RF) phase-shifting schemes is used to reduce the power consumption and RF path loss. Moreover, in the implementation of active circuits, a bulk isolation technique is used to achieve a higher power gain with a minimum number of stages. This technique is also utilized in the RF path phase shifter switches to mitigate the loss. To validate the proposed architecture, a single-element 56-to-66 GHz phased-array receiver front-end is fabricated in a 65-nm bulk CMOS process. Based on the measurement results, the receiver achieves a power gain of ~14.85 dB and a minimum noise figure (NF) of 5.7 dB. The measured average RMS phase and gain errors are ~3.5° and ~0.45 dB, respectively. The input 1-dB compression point ( $\text{P}_{\mathrm {-1dB}}$ ) of the receiver chain is about −19 dBm. The complete receiver, including active balun and required buffers (excluding the LO), consumes ~50 mW from a 1-V power supply and excluding the pads occupies a silicon area of 0.93 mm2.
FAA-NASA vs. Lane-Based Strategic Deconfliction

The Federal Aviation Administration (FAA) and NASA have provided guidelines for Unmanned Aircraft Systems (UAS) to ensure adequate safety separation of aircraft, and in terms of UAS Traffic Management (UTM) have stated[1]:A UTM Operation should be free of 4-D intersection with all other known UTM Operations prior to departure and this should be known as Strategic Deconfliction within UTM … A UTM Operator must have a facility to negotiate deconfliction of operations with other UTM Operators … There needs to be a capability to allow for intersecting operations.The latter statement means that UTM Operators must be able to fly safely in the same geographic area. The current FAA-NASA approach to strategic deconfliction is to provide a set of geographic grid elements, and then have every new flight pairwise deconflict with UTM Operators with flights in the same grid elements. Note that this imposes a high computational burden in resolving these 4D flight paths, and has side effects in terms of limiting access to the airspace (e.g., if a new flight is deconflicted and added to the common grid elements during this analysis, then the new flight must start all over). We have proposed a lane-based approach to large-scale UAS traffic management [2], [3] which uses one-way lanes, and roundabouts at lane intersections to allow a much more efficient analysis and guarantee of separation safety. We present here the results of an in-depth comparison of FAA-NASA strategic deconfliction (FNSD) and Lane-based strategic deconfliction (LSD) and demonstrate that FNSD suffers from several types of complexity which are generally absent from the lane-based method. This algorithm is based on optimization methods which form the core origins of artificial intelligence.
Field Experiments on Shooter State Estimation Accuracy Based on Incomplete Acoustic Measurements

This paper investigates the problem of shooter localization fusing complete or incomplete experimental data of one or multiple acoustic sensors. A microphone array can measure a complete measurement data set, composed of two bearing angles of the two impulsive sound events of a supersonic bullet and the TDOA between both events, or an incomplete subset. In this paper experimental results from a field experiment with volumetric microphone arrays are investigated and compared with the associated Cramér-Rao bound.
A Review of Algorithms, Datasets, and Criteria in Word Sense Disambiguation With a View to its Use in Islamic Texts

Most of the words in a natural language are polysemous; it means, they have multiple senses. Word sense disambiguation is the process of determining the exact sense of the polysemous word by analyzing the context in which the word occurs. Word sense disambiguation is one of the fundamental tasks in the field of natural language processing. However, There have been few studies in word sense disambiguation in Persian and Arabic languages. For the above reason and considering the abundance of ambiguous words and phrases in Islamic texts, the need for a special algorithm to help the disambiguation of such texts is felt. The present study attempted to have an overall review of word sense disambiguation approaches, strategies and issues, in order to open the way for future work on the presentation of similar algorithms for Islamic texts. We review approaches such as semi-supervised, unsupervised, supervised and knowledge-based approaches. The best strategy will be introduced, and the state-of-the-art systems related to it will be compared.
An Effective Adaptive Gain Dynamics for Time-Delay Control of Robot Manipulators

The time-delay control (TDC) has recently been spotlighted as an effective solution owing to model-free, efficient, and robust properties thanks to a time-delay estimation (TDE) technique. The gain of TDC, usually denoted by <inline-formula> <tex-math notation="LaTeX">${\bar {\text M}}$ </tex-math></inline-formula>, is crucial for its stability and performance, and it is reported that the constant gain of TDC does not always guarantee the best performance. To cope with this problem, this paper proposes an effective gain adaptation together with a nonlinear desired error dynamics and a new sliding variable. The resulting adaptive gain dynamics is combined with the TDC to form the proposed control, whose closed-loop stability is proved. Through simulation and experiment, we have shown that the proposed control enables to transfer <inline-formula> <tex-math notation="LaTeX">${\bar {\text M}}$ </tex-math></inline-formula> from an unstable initial value to a stable one, better than a best-tuned gain by trial and error. As a result, the proposed control is model-free, able to achieve time responses as fast as the inclusive enhanced TDC (IETDC) – arguably the fastest TDC – and tracking accuracy better than the IETDC. The proposed method has shown a strong potential to significantly relieve the burden of gain selection.
Faulty Characteristics and Identification of Increased Connecting and Internal Resistance in Parallel-Connected Lithium-Ion Battery Pack for Electric Vehicles

This paper investigates the faulty characteristics and develops an identification method to distinguish connecting and increased internal resistance faults in the parallel-connected lithium-ion battery pack. On one hand, the experiments under faulty conditions are conducted. A novel method for collecting cell voltage is adopted to reflect the difference in the tab voltage. The incremental capacity is analyzed to clarify the reason for the capacity loss of the battery pack. The current and temperature are also discussed to investigate the characteristics. On the other hand, an identification method is proposed based on the experiments. The parallel-connected battery unit is regarded as a large battery. The parameters of the large battery are estimated by recursive least squares. It is judged whether the large battery has a loose connection or internal resistance increases by the estimated resistance and its standard deviation. Then, combine with the tab voltage and temperature, the specific faulty cell is identified. The fault is considered as the second level. When the temperature difference among cells exceeds 5°C, the fault deteriorates to a first level. The estimated resistance, the tab voltage, and the temperature are used as faulty indicators, which jointly determine the specific fault type and position.
Privacy-Preserving and Trustworthy Device-to-Device (D2D) Offloading Scheme

In device-to-device (D2D) offloading, frequent offloading to a specific mobile device (i.e., an offloadee) can violate the privacy of a task owner and proper offloading results cannot always be guaranteed due to untruthful mobile devices. To address these problems, we propose a privacy-preserving and trustworthy D2D offloading scheme (PPTS) with two steps: 1) a privacy-preserving offloading step and 2) a blockchain-based verification step. In the first step, a task owner selects several offloadees and offloads the tasks redundantly to them to obtain reliable offloading results with a minimum task completion delay while preserving its own privacy at a sufficient level. In addition, the task owner chooses another mobile device as a verifier. In the second step, the task owner and verifier exploit blockchain networks to check whether the offloading results are appropriately processed. We formulate a static game to decide an appropriate redundancy ratio of offloading tasks and incentives for the offloadees.The evaluation results demonstrate that PPTS can provide reliable offloading results with a reduced task completion delay and guarantee a sufficient level of privacy of the task owner.
The Terminal Trajectory Drive and Control of a Three-Channel Soft Actuator

The nature of high flexibility and adaptability brings soft robot more potential applications on industry, therapy and many other fields. The terminal locomotion of a soft actuator can be flexible and random to some extent. At the same time, the model construction and locomotion control have some difficulties. Different from most soft actuators with single channel unit, a self-developed three-paralleled-channel pneumatic soft actuator has been already fabricated before. This paper aims to do a coupling control of three paralleled channels’ pressures and establish a pneumatic drive model of extruding and bending, and then present the terminal trajectory control system.
A Reconfigurable Dual-Band Dual-Circularly Polarized Antenna for Vehicle Global Navigation Satellite System Application

A simple and novel reconfigurable dual-band dual-circularly polarized (CP) cavity backed high-gain antenna for vehicle global navigation satellite system (GNSS) is first reported in this paper. This design consists of a simple planar printed monopole with four branches, four pin-diodes and a modified cavity. Four pin-diodes are used to control the length of these four branches. By asymmetrically changing the states of these four diodes, this antenna can resonate both right-hand circular polarization (RHCP) wave and left-hand circular polarization (LHCP) wave at two bands. An elliptical cavity with a metal step is adopted to realize unidirectional radiation. To verify the concept, one prototype is fabricated and measured. The measured impedance bandwidths (|S11| < −10 dB) are 22.69% (1.055-1.325 GHz) and 5.68% (1.54-1.63 GHz), and the 3-dB axial ratio (AR) bandwidths are 7.4% (1.211-1.304 GHz) and 3.91% (1.554-1.616 GHz) with only 1.261 center frequency-ratio (CFR). The proposed antenna has advantages of simple structure, reconfigurability, higher gain, and smaller CFR.
Reciprocating Bus in FREEDM System with Solar Farm Integration

Speeding up the transition to clean renewable energy is one of the best ways to curb the dangers of carbon pollution that cause the climate changes. Solar power is one of sustainable and clean energy sources. Abounding type of solar power is photovoltaic PV, so it needs to be integrated into the utility grid to reduce the amount of burning fossil fuel, which causes the pollution problem. Besides, different DC voltage levels, in the medium voltage bus (MVB), are needed to fulfil the customer expectation and to harvest the solar power into Future Renewable Electric Energy Delivery and Management (FREEDM) system. Therefore, this paper discusses the integration of PV power with the main power grid via reciprocating bus based on power electronic transformer (PET), because PET can provide galvanic isolation instead of using the bulky conventional line-frequency transformer. Moreover, it can be controlled. Reciprocating bus is created by changing the connection of PETs in the secondary side to provide different voltage levels 10KV and 20KV in the MVB. 20KV bus is used to integrate the PV power to a main grid; in fact, it can feed the load from the solar power and from the grid at the same time. Rewarding of using PET is small, efficient and cheaper as compared with power transformer. Simulation results validate the effectiveness and superiority of proposed diagram; the results are verified by PSCAD / EMTDC software.
Tree-Based Real-Time Advertisement Recommendation System in Online Broadcasting

The viewing time of media content per week through TV is still dominant. Users are exposed to numerous advertisements, such as commercials, electronic home shopping, product placement (PPL), and T-Commerce while watching TV programs. Most of the advertisement systems provide a good overview of products. However, traditional advertising services do not consider user preferences, meaning it is difficult to expect anything more than mere exposure to them. We can adopt a recommendation system to predict the preference. However, existing recommendation systems find it difficult to satisfy the real-time requirements of online broadcasting because of the large overhead incurred in preference prediction processes. In this paper, we propose a real-time recommendation system to provide personalized advertisements. The proposed system generates tree models based on user historical data. To reduce the overhead of preference prediction, we introduce a sorted HashMap that enables fast tree searches. For sophisticated preference prediction, the proposed system normalizes the users’ preferences by considering the characteristics of their tree model. Finally, we conduct experiments to evaluate the performance of the proposed tree-based recommendation system.
Study on Freshwater Fish Image Recognition Integrating SPP and DenseNet Network

With the development of image processing and machine vision, there are emerging fish species classification algorithms that use machine vision technology to identify specific scenes. In order to solve the problem of poor working environment and low efficiency of traditional artificial identification of fish species, this paper proposes a deep learning method combining SPP (spatial pyramid pooling) and DenseNet (dense neural network). The model is connects the spatial pyramid pooling layer in front of the full connection layer of DenseNet network. On the basis of maintaining good recognition accuracy of DenseNet, the integrated new network can increase scale invariance and reduce overfitting. Through the identification test of 6 kinds of freshwater fish, the classification accuracy rate reached 97%. Experimental results show that the new network SPP-Densenet can effectively identify species of freshwater fish images.
Performance Evaluation of Collision Avoidance Techniques using Wake-Up Radio in WSNs

In recent years, wake-up radio (WuR) approaches are being widely used for enhancing the global performance of communications of wireless sensor networks (WSN). In fact, WuR fulfils the requirements of WSNs in terms of latency and energy efficiency. However, it remains ineffective in the case of a heavy traffic load since the collision between the wake-up calls (WuCs) becomes significant. For this reason, researchers tried to implement collision avoidance mechanisms to control the sending of WuCs and maximize the reliability of WuR approaches. WuR using collision avoidance mechanisms have being evaluated using analytical frameworks or discrete event simulators but so far, no one used OMNET++/MiXiM simulator. Thus, in this paper we implement WuR using collision avoidance mechanisms in the OMNET++/MiXiM framework. We also compare the performance obtained by our implementation to those obtained by other simulators with similar parameters. We also study the performance of WuR under various traffic loads and different network densities. We show that CSMA-WuR outperforms other WuR mechanisms in the case of heavy traffic load and a large network. Moreover, CCA-WuR is a good alternative for light traffic and also for heavy traffic if we increase the number of WuC attempts. We also show that the Performance of BO-WuR strongly depends on the size of the contention window but cannot ensure good performances when the traffic is extremely heavy.
Automatic Detection of Exudates and Hemorrhage in Fundus images

Diabetic Retinopathy disease might lead to total loss of diabetic patient’s sight. In this research, we aim to detect the lesions of the Diabetic Retinopathy including Hemorrhage, and exudates. To be sure that the fundus images are in the same conditions of brightness, we applied Grey World approach on brightness channel then reconstruct the RGB. CLAHE and Unsharp filter are applied on reconstructed green channel and resulted in corrected green channel Gcor. The contrast stretching function is applied on the original green channel to result in stretched green channel Gs. The two images Gcor and Gs, are processed using thresholding and morphology operations to extract and localize optic disk, exudates, blood vessels, micro-aneurysm, Hemorrhage and macula. The color correction steps highlights Diabetic Retinopathy lesions. Sensitivity in our computer Diabetic Retinopathy diagnoses system achieved 94.44 % and outperforms most of current research works.
Optimized Model Predictive Control With Dead-Time Voltage Vector for PMSM Drives

In order to improve the current steady-state control performance of the model predictive control (MPC), a dead-time voltage-vector based MPC method is proposed in this article. First, the effect of the dead-time on MPC is introduced, and the formation process of the dead-time voltage vector existed in MPC is analyzed. Furthermore, the beneficial dead-time voltage vector and nonbeneficial dead-time voltage vector for the current steady-state control performance of MPC is distinguished, and the advantage of the beneficial dead-time voltage vector is analyzed. Then, the MPC method based on dead-time voltage vector is presented, which optimizes the action time of dead-time. Finally, the experimental results prove that the current steady-state control performance of the proposed MPC method is better than the conventional MPC method without increasing the switching frequency.
Digital Twin and Its Application in Power System

This paper introduces the digital twinning technology, which integrates multi-disciplinary, multi-physical, multi-scale and multi-probability simulation processes by using physical models and sensors, and completes mapping in virtual space, thus reflecting the whole life cycle process of corresponding entities, and the existing models based on digital twin in related fields and their uses and implementation methods are analyzed. According to the existing models and methods, the digital twin technology is combined with the power system, which can be applied to the optimization design of the power grid, the simulation and simulation of power grid faults, virtual power plants, intelligent equipment monitoring, and other services. The application scenario of digital twin of power systems (PSDT) is expounded, and the key technologies of PSDT implementation are exemplified by Cai-Lun Station as an example. The model structure of PSDT and the method of model reduction are explained.