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In modern-day multi-dimensional recreational drones (UAVs), the global navigation satellite system (GNSS) units in- use are commonly fraught with precise-point-positioning (PPP) data errors or inaccuracies, hence, necessitating this work. These data inaccuracies, occasioned by the system’s drawbacks such as sudden GPS lock or jamming, embedded device misalignment, drone’s limited communication coverage, signaling and detection, all contributes to the system’s PPP computation complexity. To mitigate PPP complexity, an intelligent and robust accurate continuous-discrete (ACD) based hybrid cubature-extended Kalman filter (C-EKF) computation model for an integrated GNSS unit is corroborated in this article. More precisely, time updates to the state and parameter sub-vectors for the GNSS unit is accomplished using the third-degree spherical-radial cubature rule. The system’s testbed simulation is then conducted using tightly-coupled units of (i) ring laser gyroscope (RLG) and (ii) micro-electro-mechanical system (MEMS) variants of the inertial measurement unit (IMU) to ascertain the PPP cooperative tendencies. Optimized performance comparisons of the proposed hybrid C-EKF over the existing cubature Kalman filter (CKF) and extended Kalman filter (EKF) models with-respect-to (w.r.t) its probabilistic outages, Yaw error-differences and ergodic capacities are demonstrated and presented.

In this paper, a novel deep learning-based robust automatic modulation classification (AMC) method is proposed for cognitive radio networks. Generally, as network input of AMC convolutional neural networks (CNNs) images or complex signals are utilized in time domain or frequency domain. In terms of the image that contains RGB(Red, Green, Blue) levels the input size may be larger than the complex signal, which represents the increase of computational complexity. In terms of the complex signal it is normally used as $2 \times N$ size for the input, which is divided into in-phase and quadrature-phase (IQ) components. In this paper, the input size is extended as $4 \times N$ size by copying IQ components and concatenating in reverse order to improve the classification accuracy. Since the increase in the amount of computation complexity due to the extended input size, the proposed CNN archiecture is designed to reduce the size from $4 \times N$ to $2 \times N$ by an average pooling layer, which can enhence the classification accuracy as well. The simulation results show that the classification accuracy of the proposed model is higher than the conventional models in the almost signal-to-noise ratio (SNR) range.

In this paper, a prioritized-MAC protocol model for unmanned aerial vehicle (UAV) data collection and processing in an industrial wireless sensor network system (IWSN) is proposed. The model encapsulates the existing legacy IEEE 802.11 carrier-sense multiple access collision avoidance (CSMA/CA) MAC protocol, where nodes are kept active when in UAV’s coverage area. A level-sided access channel approach is then deployed to distinguish the priority allotment to each ground node using the distributed coordinated function inter-frame spacing (DCFIS) approach. Consequently, nodes located at the highest priority level-sided frame have shorter time-length with more DCFIS values than those of lower priority level-sided frames. On simulation, our proposed protocol not only improves fairness, but enhances network fairness with reduced delay time.

Recently, deep learning (DL) is an innovative machine learning (ML) technique that has gained the outstanding achievements in computer vision and natural language processing. This work takes advantage of DL for effectively handling automatic modulation classification (AMC), which is the fundamental function of numerous cognitive radio-based and spectrum sensing-based applications in many modern communication systems. Concretely, a novel deep convolutional neural network (DCNN) is proposed for learning a classification model from a massive amount of modulated signals, in which the network architecture has several convolutional blocks specialized to simultaneously capture the temporal intra-signal correlations and the spatial inter-signal relations. To this end, each block comprises various convolutional layers of asymmetric convolution kernels, whose outputs are gathered via a concatenation layer. For the enrichment of multi-scale deep feature and the prevention of gradient vanishing problem, these blocks are associated by skip connections to take into account the useful residual information. In experiments, the proposed CNN-based AMC method achieves the overall 24-modulation classification rate of 88.22% at 10dB SNR on the well-known DeepSig dataset.

Numerous existing handcrafted feature-based and conventional machine learning-based approaches cannot seize the intensive correlations of skeleton structure in the spatiotemporal dimension. On another hand, some modern methods exploiting Long Short Term Memory (LSTM) to learn temporal action attribute, which lack an efficient scheme of revealing high-level informative features. To handle the aforementioned issues, this research introduces a novel hierarchical deep feature fusion model for 3D skeleton-based human action recognition, in which the deep information for modeling human appearance and action dynamic is gained by Convolutional Neural Networks (CNNs). The deep features of geometrical joint distance and orientation are extracted via a multi-stream CNN architecture to uncovering the hidden correlations in both the spatial and temporal dimensions. The experimental results on the NTU RGB+D dataset demonstrates the superiority of the proposed fusion model against several recently deep learning (DL)-based action recognition approaches.

In this paper, the wireless communication channels of the aircraft environment are investigated and total energy consumption, throughput metrics are analyzed by non-cooperative schemes which are single-hop, multi-hop, and cooperative relaying schemes which are Amplify and Forward(AF), Decode and Forward(DF), Incremental Decode and Forward(IDF), Incremental Amplify, Forward(IAF) to compare each performance. In case of the channel model, path-loss, large-scale fading, and small-scale fading channels are modeled by referring experimental parameters of ITU(International Telecommunication Union) report, which is measured in the aircraft between inter-cabin and inter-cabin and between inter-cabin and a wing. When the total energy consumption and throughput performance are analyzed by using six schemes, the incremental cooperative schemes outperform the other schemes in terms of energy consumption and throughput.

In this paper, an efficient firmware design scheme is proposed for a 100-Gbps CFP(C form-factor pluggable) optical transceiver. The proposed method uses an FPGA approach to integrate the CFP communication interface and register structure, and uses an MCU to implement the operation of the CFP optical transceiver. To ensure the implemented firmware satisfies the proposed design scheme, a real testbed was constructed and the performance of the firmware was evaluated.

In this research, we introduce a strain-insensitive soft pressure sensor using 3D-printed microchannel mold and liquid metal for health monitoring applications. Our soft pressure sensor consists of elastomer and liquid metal for its intrinsic stretchable property. Also, serpentine geometric pattern of the microchannel enabled the sensor to be strain-insensitive for stable signal response and recovery in wearable applications. Various experiments for sensor characterizations were conducted and the study of FEM simulation verified the strain-insensitive behavior of serpentine pattern. As a health monitoring application, body pressure distribution was monitored using several pressure sensors attached on the clothes and the body pressures were compared according to various lying conditions.

This paper reports a wide range-sensitive, bending-insensitive pressure sensor based on a carbon nanotube (CNT)-coated porous elastomer for a wearable healthcare application. (1) Sensing performance was evaluated over ~1MPa, which includes whole human tactile and body weight levels. The sensor exhibits a very wide sensing range from ultralow to high pressure (50Pa-1MPa) with maintenance of favorable sensitivity and reliable dynamic responses. (2) To our knowledge this is the first to investigate bending-insensitivity of the CNTs-coated porous PDMS, which facilitates accurate detection of normal pressures even on curved surfaces like human skins. (3) Finally, we demonstrated a foot insole for real-time monitoring of foot plantar pressure distribution.

In the above article [1], in Table 4, the operator * was used to represent frame sizes, which are 2 * 128 and 4 * 128. The correct operator should be a multiplication operator $\times $ for $2 \times 128$ and $4 \times 128$ .

In this work, we developed micro-crack based stretchable strain sensors consist of polydimethylsiloxane (PDMS) with micro-dome structure arrays and carbon nanotube (CNT) film coated on its surface. Due to a stress concentration caused by micro-dome structure under a certain strain, micro-cracks of CNT film are generated and propagated more easily as compared with the case of a CNT film on the plane surface. In addition, because the micro-cracks are only positioned at designed region which is between micro-domes, electrical resistances in elongated and perpendicular directions are clearly different thanks to the novel mechanism. As results of these phenomena, strain decoupling is achieved and a sensitivity of the sensor can be modulated by adjusting the dimension of micro-dome arrays. We also conducted the numerical simulation based on finite element method (FEM) to verify the designed sensing mechanism and predict the performance of the sensor. This kind of work is important for the motion detecting sensor for acquiring decoupled information from complex signal. Finally, we fabricated a smart glove that could detect a biaxial strain applied on the back of a hand skin to demonstrate that this sensor could be used as wearable device.

We consider the problem of equalizing the quantization noise between two video encoders operating with video stored using different transfer function. Here, a transfer function is the mapping between linear light and the quantized code words and includes, for example, the well-known “gamma curve” used for most video applications. Our motivation for studying this problem is that the solution enables the direct conversation of a quantization strategy developed for a legacy, standard dynamic range transfer function to be easily mapped to a quantization strategy for a new, high dynamic range transfer function. This is especially timely given the beginning deployment of high dynamic range services throughout the world that use the BT-2020/SMPTE ST 2084 transfer function and not the BT.709/BT.1886 transfer function historically employed for coding high definition digital video. The paper derives a model for the needed relationship. Results show the benefit of the approach.

This paper describes high-quality compression of high dynamic range (HDR) video using existing tools such as the HEVC Main 10 profile, the SMPTE ST 2084 (PQ) transfer function, and the BT.2020 non-constant luminance Y'CbCr color representation. First, we present novel mathematical bounds that reduce complexity of luminance-preserving subsampling (luma adjustment). A nested look-up table allows for further speedup. Second, an adaptive QP scheme is presented that obtains a better bit allocation balance between dark and bright areas of the picture. Third, a method to control the bit allocation balance between chroma and luma by adjusting the chroma QP offset is presented. The result is a considerable increase in perceptual quality compared to the anchors used in the 2015 MPEG High Dynamic Range/Wide Color Gamut Call for Evidence. All techniques are encoder-side-only, making them compatible with a regular decoder capable of supporting HEVC Main10/PQ/BT.2020, which is already available in some TV sets on the market.

This paper presents a rate adaptation algorithm for directional multicast communication in tactical networks. The proposed algorithm is based on the received signal strength indicator (RSSI) and delay constraint that are sent by receivers in the network. This feedback from receivers provides accurate real-time information about the current state of the communication channel so that the transmission rates can be varied to reduce the loss of the transmitted data packets. Typically, rate adaptation algorithms consider packet loss, modify frames in only the MAC layer, and accordingly change modulation scheme employed by the transmitter. In the proposed method, the modulation technique used for data transmission is changed according to the RSSI by considering the delay constraints of transmission to ensure satisfactory real-time performance. Simulation results show that the proposed method based on the IEEE 802.11a standard ensure good performance and reliability in terms of reduced the delay, increase throughput and the number of nodes that received data.

The design trend of mobile handset become slim and thin, and the handset has covered a lot of communication service bands including GPS, WiFi, and Bluetooth. Moreover, 4G communication service needs plural antennas and the handset has been supporting additional functions such as cameras, sensors, and u-USB. Because of these backgrounds, the antenna design condition is becoming worse and this causes poor radiation performance. Based on the limited antenna volume, controlling the antenna impedance by tuner is one of the good solutions for designing the antenna. Tuner can modify the impedance characteristics of antenna and it makes possible to have multiband in the low frequency range under 1 GHz. Even though there are very shrunk antenna volumes inside the phone, we can overcome the bandwidth problem in low band partly. Recently, the handset should support the CA service in LTE bands, this is becoming a big challenge for antenna designers.

This paper describes a scalable extension of the High Efficiency Video Coding (HEVC) standard that supports different color gamuts in an enhancement and base layer. Here, the emphasis is on scenarios with BT.2020 color gamut in an enhancement layer and BT.709 color gamut in the base layer. This is motivated by a need to provide content for both high definition and ultra-high definition devices in the near future. The paper describes a method for predicting the enhancement layer samples from a decoded base layer using a series of multiplies and adds to account for both color gamut and bit-depth changes. Results show an improvement in coding efficiency between 65% and 84% for luma (57% and 85% for chroma) compared to simulcast in quality (SNR) scalable coding.

This paper presents a compact printed dual-band WLAN antenna with a shorted coupling strip for mobile terminals. A shorted coupling strip is utilized to improve impedance matching at the upper band and a chip capacitor is used to reduce an antenna size. The proposed antenna area is 10 × 5 mm2 with a ground size of 70 mm × 40 mm. The proposed antenna yields a VSWR of better than 3:1 at dual bands of 2.39∼2.49 GHz and 5.07∼5.88 GHz. The measured gain is 1.3 dBi at 2.44 GHz and 3.7 dBi at 5.35 GHz, respectively.

The FOR/SOR algorithm was initially proposed in [1] and shown to outperform H.264/AVC by a significant margin for high definition (HD) video coding when the bit rate is equal to 20Mbps or higher. In this work, we propose an improved FOR/SOR coding scheme which offers a superior coding performance in a bit rate range of practical interest, which ranges from 1–15 Mbps. To enhance the coding performance of the proposed algorithm, we incorporate several new coding tools in the basic FOR/SOR coding algorithm in [1]. Furthermore, we attempt to give an intuitive explanation of the superior performance of the FOR/SOR coding scheme using arguments based on the R-D analysis. Finally, it is shown by experimental results that the proposed algorithm outperforms H.264/AVC significantly for HD video in the bit rate range of common interest.

Four-wave-mixing (FWM) efficiency of a silicon-based one-dimensional photonic crystal waveguide was measured along with its spectral profile of the group index. High FWM efficiencies were observed near the band edge compared to those at the middle sections of its transmission band despite its high dispersion effect.

In this work, we propose the use of a set of new features based on CELP (Code Excited Linear Prediction) to enhance the performance of the environmental sound recognition (ESR) problem. Traditionally, Mel Frequency Cepstral Coefficients (MFCC) have been used for the recognition of structured data like speech and music. However, their performance for the ESR problem is limited. An audio signal can be well preserved by its highly compressed CELP bit streams, which motivates us to study the CELP-based features for the audio scene recognition problem. We present a way to extract a set of features from the CELP bit streams and compare the performance of ESR using different feature sets with the Bayesian network classifier. It is shown by experimental results that the CELP-based features outperform the MFCC features in the ESR problem by a significant 9% margin in average and the integrated MFCC and CELP-based feature set can even reach a correct classification rate of 95.2% using the Bayesian network classifier.

A first-order-residual/second-order-residual (FOR/SOR) based video coding algorithm that incorporates the super macroblock (SMB) and the inter-frame stripe prediction (ISP) technique is proposed for high definition (HD) video coding in this work. We first examine the limitation of the SMB in high-bit-rate coding, and show that a simple extension of the block-size is not sufficient to get a significant improvement in coding performance. Then, we introduce the FOR/SOR coding technique to resolve this issue. For the FOR coding, we apply a larger quantization stepize and motion-predictive coding to remove the temporal correlation. Then, for the SOR coding, we propose an efficient prediction method, called the inter-frame stripe prediction (ISP) technique, to remove the structured residuals after the FOR coding to achieve a higher coding gain. It is demonstrated by experimental results that the proposed FOR/SOR algorithm outperforms H.264/AVC by a significant margin; namely, about 21.57% in the bit rate saving or 1.09dB in the PSNR improvement.

This paper proposes a modified Wilkinson divider using a zero-degree phase shifting composite right/left-handed (CRLH) transmission line to obtain good isolation between output ports and to obtain easy fabrication. A zero-degree phase shift CRLH transmission line, which has a total phase shift of zero-degrees, is combined with a right-handed (RH) transmission line with negative phase and a left-handed (LH) transmission line with positive phase. To validate a value of zero-degree on the phase shift CRLH transmission line, compared to a conventional Wilkinson divider, the divider using a zero-degree phase shift line provides comparable input return loss and insertion loss. In addition, the meta-material divider is significantly more compact, occupying only 50% of the size that the conventional divider space.

This paper introduces a rat-race coupler, with size reduction and bandwidth enhancement, using shunt capacitors, high impedance lines and Composite Right/Left-Handed Transmission Lines (CRLH-TLs). The reduced method of line length is used to combine a short length high impedance line and two shunt capacitors. Also, there is combined CRLH meta-material, using nonlinear phase characteristic of CRLH-TL that consists of series capacitors and shunt inductors, so as to obtain wide bandwidth. The implemented rat-race coupler shows a novel design with compact size that is smaller by 10% and a bandwidth that is larger by 60% than that of a conventional rat-race coupler.

This paper proposes a design of a variable attenuator based on meta-material structuring and its application. The unit-cell of attenuator, based on the lossy transmission line, consists of the composite right/left-handed transmission line (CRLH-TL) and PIN diodes to control internal loss according to resistance variation of diode. Also, to reduce the initial losses, a parallel connection of PIN diodes is used. Because of constituting a periodic structure to increase attenuations, an attenuator with a cascade unit-cell is connected. The attenuation quantities of the unit-cell are about 10dB and phase variations are a maximum of 15° at 1.5 GHz ∼ 2.5 GHz. To attenuate more than 10dB, the unit-cell of attenuator must be connected to a cascade. Also, its application is represented by a vector modulator.

In Robot-assisted surgery, haptic feedback is ongoing issue. The breaking of surgical suture material and the damage of tissue are avoidable with haptic feedback. This paper is proposing to add haptic feedback in the da Vinci like robot using unmodified da Vinci surgical instrument. To overcome the restriction of space and difficulty in measuring the force at the end-effector, the torque sensor-motor integrated module is developed. The proposed torque sensor-motor module has a totally integrated design that can replace a nominal motor. It also shows linear stress-strain relation and inherent high sensitivity.

The context-based adaptive variable length coder (CAVLC) in H.264/AVC is not appropriate for lossless video coding because it was designed for lossy video coding. Since statistical characteristics of residual data in lossy and lossless coding are quite different, we design a new VLC table for the number of non-zero coefficients and an adaptive scheme for VLC table selection in level coding for lossless intra coding. Experimental results show that the proposed CAVLC scheme provides approximately 10% bit saving, compared to the original CAVLC scheme in H.264/AVC.

Context-based adaptive variable length coding (CAVLC) of H.264/AVC was originally designed for quantized transform coefficients in lossy video coding, and as such does not yield adequate performance in lossless video coding. In this paper, we propose an improved CAVLC for lossless intra coding. Considering statistical differences of residual data in lossy and lossless coding, we design a new CAVLC encoding algorithm. Experimental results show that the proposed method provides approximately 7.6% bit savings, compared to the current H.264/AVC FRExt high profile.

In this paper, a third- and fifth-order analog predistorter using series feedback constituted individual predistorter of common-emitter amplifiers and schottky diodes has been developed. The individual order predistorters of the proposed circuit have shown the gain and phase control characteristics in order to compensate nonlinearity of amplifier with wide dynamic range. The individual predistorters with improvement of AM/AM and AM/PM is controlled the optimum condition of third- and fifth-IMD by the diode bias. The proposed circuit consists of the individual predistorters, power splitter and divider. The test results show that the third- and fifth-IMD of power amplifier is cancelled maximum 13.5 dB and 13.4 dB for two-tone signals, respectively. Also, it's improved the adjacent channel leakage ratio (ACLR) approximate 2.5 dB and 3 dB each other for CDMA 2FA signals at 1.23 MHz and 1.98 MHz offset points. The proposed predistorter provides moderate distortion improvement and control individual-orders at little extra cost. It also is realized with advantages of miniaturized size, low complexity, and stable operation.

In the former researches (Ingyu Park, et al., 2001), (Sangduck Lee and Woonchul Ham, 2002), (Seonghoon Kim and Woonchul Ham, 2004), we suggested an algorithm which can be used for deriving the nonlinear inverse kinematic problem in unmanned bicycle system by using iterative method. In this short note, we reinforce the former method and propose a new iterative algorithm for a certain type of nonlinear dynamic equation such as inverse kinematics of bicycle system. The idea of proposed algorithm is similar to Piccard's iterative method in basic concept. We also propose a robust control strategy for tracking problem in bicycle system based on nonlinear compensation. In this control algorithm, we invent and attach the load mass balance system for the self stabilization with more ease. From the computer simulation results, we can see that the proposed control algorithm can be applied to the real system.

The H.264 standard achieves higher compression efficiency than previous video coding standards with the rate-distortion optimized (RDO) method for mode decision. The outstanding coding performance of H.264, however, comes at the cost of significantly increased complexity. In this paper, we present algorithm-level optimization methods: input parameter selection, fast inter-mode decision, and efficient combination of motion estimation and mode decision. Simulation results show that our optimized H.264 encoder achieves realtime encoding for video graphics array (VGA) and extended graphics array (XGA) on a commercial personal computer without introducing serious quality degradations.

Multi-view video allows us to experience more realistic feelings with arbitrary view-points and a wide range of scenes, because those are captured by multiple cameras simultaneously but at different positions. Since the amount of data to be processed increases in proportion to the number of cameras, we need to develop efficient coding methods. In this paper, we propose an efficient view interpolation scheme and coding method for multi-view video using the correlation between views. After generating an intermediate view image, we use it at the encoder as an additional reference frame using the proposed 'VIP P-picture' coding method. The proposed view interpolation method improves the generated inter-view image about 1~4 dB and the 'VIP P-picture' coding method improves coding efficiency about 0.5 dB.

Three-dimensional numerical device simulations are done to gain physical insights on multi-gate FinFETs, which portend the infeasibility of nanoscale triple-gate CMOS, and process/physics-based device/circuit simulations are done to check the concept of pragmatic nanoscale double-gate CMOS design, showing encouraging performance projections near the end of the SIA 2003 ITRS (2003).

Three- and two-dimensional numerical simulations of double-gate (DG) and triple-gate (TG) FinFETs having undoped thin bodies have revealed the significance of bulk-inversion current in I/sub on/, as well as I/sub off/, and the consequent insignificance of the commonly defined effective gate width in comparisons of DG and TG currents.

In general, the source data to be quantized cannot be defined by a single distribution because it has a problem caused by the exhaustive approximation of the actual source distribution. In order to avoid this problem, we use the generalized Gaussian distribution (GGD) for modeling the distribution of the source. GGD is a parametric family of distributions, including the uniform, Laplacian, and Gaussian distributions as special cases. In this paper, we propose a quantization algorithm for H.264 video rate control based on the rate-quantization model, which is derived from the rate-distortion function of GGD. We implement our rate control scheme for low-delay inter-frame coding, and compare its performance with those of TM5 and TMN8 for various video sequences.

This paper proposes a new double talk detection algorithm which is based on fuzzy theory for use in the adaptive echo canceller of a telecommunication system. In this method, the two inputs of the fuzzy inference for detecting double talk condition are used. One input is the cross-correlation coefficient between the error signal and the primary signal which is the summed signal of the real echo signal and the near-end signal. The other is the cross-correlation coefficient between the estimation error signal and the primary signal. It is confirmed by computer simulation that this fuzzy double talk detector is able to track echo path variation accurately during the double talk.

In this paper, we propose an efficient scheme to write a transmission schedule for playback restart of a video stream at a new frame position after interactive operations such as jump or fast playback in a video-on-demand (VoD) service. The proposed scheme is based on convergence characteristics, that is, transmission schedules with different playback startup frame position in a video stream meet each other at some frame position. The scheme applies bandwidth smoothing from a new frame position to a convergence position without considering all the remaining frames of the video stream. The scheme then transmits video data according to the new schedule from the new frame position to the convergence position, and then transmits the remaining video data according to the reference schedule from the convergence position to the last frame position. In this paper, through many experiments based on MPEG-1 bit trace data, we show that there exists the convergence position corresponding to any frame position in a video stream.