ISSN / EISSN : 2169-3536 / 2169-3536
Current Publisher: Institute of Electrical and Electronics Engineers (IEEE) (10.1109)Former Publisher:
Total articles ≅ 47,167
Latest articles in this journal
IEEE Access, pp 1-1; doi:10.1109/access.2021.3078162
This paper proposed a rapid design and additive manufacturing method of customized bionic sports sole with high performance for the elderly. A parametric modeling software of human foot is developed, which can realize the rapid measurement and modeling of the elderly’s foot and corresponding sole structure with specific characteristics. A self-developed material extrusion equipment is adopted to fabricate thermoplastic polyurethanes (TPU) material parts. The influence of extrusion temperature on the tensile properties of fabricated TPU parts is investigated, the hyperelastic model is applied to simulate the mechanical response of TPU, the sole shape is designed and optimized by finite element method (FEM). The leopard paw bionic sole pattern is designed and the antiskid performance is tested by friction experiment. Customized bionic sports sole made of TPU material is successfully manufactured by the self-developed material extrusion equipment. The results indicate that the personalized customization of sports sole for the elderly can be quickly designed and manufactured by the combination of parametric modeling software and material extrusion equipment.
IEEE Access, pp 1-1; doi:10.1109/access.2021.3078295
Image data contain spatial information only, thus making two-dimensional (2D) Convolutional Neural Networks (CNN) ideal for solving image classification problems. On the other hand, video data contain both spatial and temporal information that must be simultaneously analyzed to solve action recognition problems. 3D CNNs are successfully used for these tasks, but they suffer from their extensive inherent parameter set. Increasing the network’s depth, as is common among 2D CNNs, and hence increasing the number of trainable parameters does not provide a good trade-off between accuracy and complexity of the 3D CNN. In this work, we propose Pooling Block (PB) as an enhanced pooling operation for optimizing action recognition by 3D CNNs. PB comprises three kernels of different sizes. The three kernels simultaneously sub-sample feature maps, and the outputs are concatenated into a single output vector. We compare our approach with three benchmark 3D CNNs (C3D, I3D, and Asymmetric 3D CNN) and three datasets (HMDB51, UCF101, and Kinetics 400). Our PB method yields significant improvement in 3D CNN performance with a comparatively small increase in the number of trainable parameters. We further investigate (1) the effect of video frame dimension and (2) the effect of the number of video frames on the performance of 3D CNNs using C3D as the benchmark.
IEEE Access, pp 1-1; doi:10.1109/access.2021.3078165
To provide a new level of reliability, latency, and support a massive number of users and smart objects, a new 5G multi-services air interface needs to be addressed for the factory of the future (FoF). However, there are limitations in providing connectivity to a dynamic machine in a factory due to several strict industrial automation requirements. In particular, the strict wireless communication latency and reliability requirements are the major challenges to enable the Industry 4.0 vision. In this paper, a PHY-MAC layer cross-layer model that combines a semi-persistent scheduling at the medium access control layer and NOMA at the physical layer has been proposed to address the limitations. The work extensively investigates the performance of the factory of the future with various considerations of 5G spectrums (in this case 3.5 GHz and 28 GHz), speeds and frequency diversity. In addition, the packet error rate (PER), outage probability and throughput in MAC are evaluated in terms of network density deployment (sparse, moderate, dense), different kinds of speed; 0 km/h, 3 km/h, 7 km/h and 10 km/h, under two 5G frequency spectrums. Through extensive simulations, the considered 5G system parameters produced better results in terms of reliability, where the results showed that the frequency diversity outperformed non-diversity by 2 dB. In a sparse network, the PER results showed better results compared to the dense network density by 2 dB (MMSE), 8 dB (LS-Linear) and 2 dB (LS-Spline). Besides that, robotics in sparse network density and stationary exhibited the best PER results, which is as low as 10-7. Moreover, the performance of mid-band frequency outperformed the high-band frequency by 1.8dB (MMSE) in dense condition and 1.5 dB (MMSE) in sparse deployment at PER = 10-6. Hence, this study could be a useful insight for the factory of the future services that are utilizing a 5G mid-band spectrum as well as a high-band spectrum.
IEEE Access, pp 1-1; doi:10.1109/access.2021.3078258
Face expression recognition is a key technology of robot vision, which can help the robotic understand human emotions. However, interference from the real-world, such as light changes, face occlusion, and pose variation, reduces the recognition rate of the model. To solve above problems, in this paper, a novel deep model is proposed to improve the classification accuracy of facial expressions. The proposed model has the following merits: 1) A pose-guided face alignment method is proposed to reduce the intra-class difference, which can overcome the impact of environmental noise; 2) A hybrid feature representation method is proposed to obtain high-level discriminative facial features that achieves better results in classification networks; 3) A lightweight fusion backbone is designed, which combines the VGG-16 and the ResNet to achieve low-data and low-calculation training. Finally, to evaluate the proposed model, we conduct a series of experiments on four benchmark datasets, including the CK+, the JAFFE, the Oulu-CASIA, and the AR. The results show that the proposed model achieves state-of-the-art recognition rates, that is, 98.9%, 96.8%, 94.5%, and 98.7%, respectively. Comparing with the traditional methods and other advanced deep learning methods, the proposed model can comparable performance in a variety of tasks.
IEEE Access, pp 1-1; doi:10.1109/access.2021.3078232
Polarimetric synthetic aperture radar (PolSAR) image classification has become a hot research topic in recent years. Sparse representation plays an important role in image processing. However, almost all the existing dictionary learning methods are linear transformation in the original data space, so they cannot capture the nonlinear relationship of the input data. The recently proposed projective dictionary pair learning (DPL) method has acquired good performance in classification result and time consumption. In this paper, we propose the nonlinear projective dictionary pair learning (NDPL) model, which introduced the nonlinear transformation to the DPL model. Our method can adaptively obtain the nonlinear relationship between the elements of input data, and it also has the excellent performance of DPL model. In this paper, we use three PolSAR images to test the performance of our proposed method. Compared with several state-of-the-art methods, our proposed method has obtained promising results in solving the task of PolSAR image classification.
IEEE Access, pp 1-1; doi:10.1109/access.2021.3078410
Commonly used variants of the proportional-integral, PI, and the integral-proportional, IP, compensator gains selections, merged with the D-decomposition technique are presented in this paper. The motivation to this work is the willingness to check whether such a combination can lead to unified and perhaps simplified approach in this matter. Therefore, the D-decomposition technique has been effectively combined with the frequency- and the time-domain driven requirements regarding the control dynamics. Criteria such as the gain- and phase-margins, (GM, PM), the sensitivity, MS, the pole placements by means of the (σ, ωd) and the (ξ, ωn), and the overshoot with the rise time (δ, tr) are considered. It has been shown that the control design effort can be reduced by the means of the D-decomposition to intuitive judgements in the proportional and integral gains coordinates (KP, KI) with parametric curves. As such it can be thought of as a promising scenario in a case considered. The analyses are presented and discussed in details. They are conducted basing on example of output voltage closed loop control of the Dual Active Bridge, DAB, converter. The circuit operates under the phase shift control scheme. The control-to-output transfer function identification and the control circuit delays are included in the analyses. The case analysis have shown that the time domain requirements are less effectively met with the PI regulator when compared to its IP configuration. This is due to the commonly used simplifications during conversion between the (ξ,ωn) and the (δ, tr) in presence of uncompensated zero of the closed loop transfer function. The paper contains complete and intelligible approach to dedicated mathematical investigations verified experimentally.
IEEE Access, pp 1-1; doi:10.1109/access.2021.3078185
Fuzzy set theory resolved the crux of modeling uncertainty, vagueness, and imprecision. Many researchers have contributed to the development of the theory. This paper intends to define the innovative concept of the interval valued complex fuzzy relations (IVCFRs) using the proposed Cartesian product of two interval valued complex fuzzy sets (IVCFSs). Moreover, the types of IVCFRs are devised with some exciting results and properties. Furthermore, a couple of prodigious applications have been established as an illustration of the modeling capabilities of the proposed structures. The concept of interval valued complex fuzzy (IVCF) composite relations is used in the medical diagnosis of patients on the basis of symptoms. The inclusion of phase term in the grade of membership of IVCFRs facilitated modeling the periodic diseases. Additionally, another application of the Cartesian products and the IVCF equivalence relations is proposed that studies the life expectancies or mortality rates of patients with certain diseases. In addition, the effects of multiple illnesses on the life expectancy of a patient are also deliberated through IVCFRs. The proposed framework is also compared with the existing structures in the field of fuzzy set theory.
IEEE Access, pp 1-1; doi:10.1109/access.2021.3078325
The detection and repair of cycle slips are key steps in high-accuracy GNSS (Global Navigation Satellite System) data processing using carrier phase observations. BDS (BeiDou Navigation Satellite System) triple-frequency observations provide better combinations for cycle slip detections and repairs compared to dual-frequency observations. Although a number of algorithms have been developed and may correctly detect cycle slips most of the time, the reliability of empirical thresholds methods cannot be guaranteed. In this study, an adaptive threshold is proposed for three sets of triple-frequency Geometry-Free (GF) pseudorange minus phase combinations to improve the cycle slip detection performance and reduce the false alarm rate of the cycle slip detection by combining the predicted epoch-differenced ionospheric delays under active ionospheric conditions. Moreover, in the cycle slip repair, the integral combined cycle slips are determined by directly rounding the estimated float-combined cycle slips, which will lead to a repair error if the between-epoch ionospheric variation is large. In this study, a new rounding method considering the predicted epoch-differenced ionospheric delays is proposed, and it is proven that the new method has a higher success rate for estimating the integer value of a cycle slip than the traditional method. The performance of the newly proposed method is validated by using static BDS triple-frequency observations that contain simulated cycle slips. BDS triple-frequency observations were collected at 30-s sampling intervals under active ionospheric conditions. The results show that this method can successfully detect and repair all slips of more than one cycle. In addition, dynamic BDS data collected with a vehicle-based receiver at a 1-s sampling intervals are processed, and the results show that the proposed method is also effective in the detection and repair of cycle slips in dynamic data.
IEEE Access, pp 1-1; doi:10.1109/access.2021.3078173
This paper studies the formation control problem of discrete-time multi-agent systems with noisy information in time-varying communication networks. To achieve the desired formation, a control law with a decaying-gain is designed. Under the zero-expectation and independent noise assumption on the communication noise, we give the rigorous proof that the desired formation can be asymptotically stabilized in the mean square and almost sure sense under the designed distributed control law when the time-varying communication network is composed of strongly connected digraphs. In addition, the mean square convergence rate is quantified. Simulations are conducted to verify the correctness of our result.
IEEE Access, pp 1-1; doi:10.1109/access.2021.3078179
For the on-orbit service spacecraft attitude tracking task with external disturbances, considering the limited capacity of its actuators and high control performance required, an improved performance constraint control algorithm based on command filters is proposed in this paper. For the proposed control algorithm, before the theoretical control signal is transmitted to the actuator, it needs to be filtered by the command filter. This filter can constrain the rate, magnitude, and bandwidth of the signals, smooth the command signals and avoid peak interference. In terms of performance constraints, inspired by the performance constraint curve, this paper uses the determined points to re-design a new performance constraint function, which shows the maximum settling time parameters, allowing designers to pre-defined this limited time of the closed-loop system according to needs. Therefore, the maximum settling time of the actual closed-loop system will be less than the pre-defined maximum settling time. The controller based on the command filter is designed, and on this basis, the corresponding performance-constrained control algorithm with pre-defined maximum settling time guaranteed is proposed. Through the proof and simulation, the rationality and effectiveness of the proposed controller are further demonstrated.