Abstract Accurate CT image segmentation is of great importance to the clinical diagnosis. Due to the high similarity of gray values in CT image, the segmented areas are easily affected by their surroundings, which leads to the loss of semantic information. In this paper, we propose a multi-scale dilated convolution network (Md-Net) for CT image segmentation with superior segmentation performance compared

Abstract This paper presents a 1 MHz PVT compensated dual phase relaxation Oscillator. The oscillator core employs a current controlled voltage bias replica circuit to limit the charging of capacitor. Furthermore, the current starved schmitt trigger circuit is employed in oscillator in place of conventional power consuming comparators. They also provide stable switching threshold voltage across temperature

Abstract This paper presents a linear sampling switch for low-voltage successive-approximation register (SAR) analogue-to-digital converters (ADCs) operating at a frequency of tens of MHz. The proposed switch employs a bootstrapped transmission gate, where the bulk voltages are generated internally to minimize variations in the threshold voltage of transistors with input signal amplitude. Thus, ensuring

In multi-modal medical images such as X-ray and CT, automated organ segmentation is often disturbed by the frequent existence of shape variation, intensity non-uniformities and blurs. Introducing supplementary information helps with eliminating the negative effects of these factors. Medical priors are often leveraged to supplement for specific tasks in previous works, but the specificity of priors

Abstract This paper deals with cell identifier (ID) estimation for narrowband-Internet of things (NB-IoT) system. It is suggested to transform the usual maximum likelihood (ML) estimator expression in order to highlight a discrete Fourier transform (DFT), which can be computed with fast algorithms. Therefore, the proposed method is a DFT-based low-complexity cell ID estimator that can be qualified

No abstract is available for this article.

Abstract In view of China’s economy achieves rapid development, technology and science change with each passing day and gradually integrate into our life. Accustomed to the intelligent age, higher requirements caused by the design of public facilities is proposed. The public facilities of the historic block are not only the effective guarantee of people’s life, but also the embodiment of the urban

Abstract In this paper, we improved the error vector magnitude (EVM) performance of six-port receiver using a low noise amplifier (LNA) bias control algorithm based on analyzing the correlation between normalized output DC offset voltage and EVM relative to input radio frequency (RF) power variation. In contrast to the other works published in the literature, we consider test setup through which the

Abstract Biopotential amplifier (BPA) remains one of the most crucial blocks for the successful implementation of any of the biomedical systems. However, design of a BPA remains challenging owing to most of the topologies reported in literature displaying high values of noise, consuming high value of power and working in limited range of bandwidth. Thus, circuit topologies capable of providing an optimum

This paper analyses how the knowledge shared between employees and suppliers within a private enterprise social network affects process improvement. Data was collected from internal documents, and the internal and external enterprise social networks used by an international insurance company; the average cycle time for handling 8494 claims and 3240 messages posted on the internal and external social

Most of the existing spectral efficiency (SE) investigations for massive multi-input multi-output (MIMO) relaying assume that each antenna has a dedicated radio-frequency (RF) chain with high-quality user and relay hardware. We consider a hybrid massive MIMO multi-pair two-way half-duplex relay, wherein each RF chain steers multiple antennas and assume that both users and relay have hardware impairments

In this paper, a hybrid power domain non-orthogonal multiple accessing (NOMA) scheme by the superposition of orthogonal frequency division multiple accessing (OFDM) and index modulated OFDM (OFDM-IM) technologies is presented and named IM-NOMA. It is shown via both computer-based simulations and mathematical analysis that IM-NOMA outperforms the classical OFDM-NOMA in terms of bit error rate (BER)

Abstract This article is devoted to the problem of determining the coordinates of wave field sources using phases of complex Fourier transforms of signals recorded by the sensor array. Phase-based source localization algorithms have an important reliability property: they provide the quality of determining the source coordinates, which weakly depends on the statistical characteristics of random noise

Abstract In this paper, plus-type differential voltage current conveyor based two voltage-mode (VM) analog filters with high input impedance properties yielding easy cascadability with other VM circuits are proposed. The first proposed filter can simultaneously provide all the second-order universal filter responses except all-pass one, and employs only grounded passive elements that are canonical

Abstract In this paper, a method for designing output matching network is proposed. The impedance matching idea is based on the sufficient condition of the ideal transistors. At this condition, the improved terminal load accommodates to the transistor load at the variation of the input power, which simplifies the design process and increases the matching accuracy. For verification, a Doherty power

In recent years, mainly the functionality of services are described in a short natural text language. Keyword-based searching for web service discovery is not efficient for providing relevant results. When services are clustered according to the similarity, then it reduces search space and due to that search time is also reduced in the web service discovery process. So in the domain of web service

Abstract In this paper, we develop a novel neural network model with mapping and piecewise optimization technology for several classes of the linear singularly perturbed initial value and boundary value differential equations with variable coefficients. First, the Legendre polynomials are selected as the activation function of the artificial neural network, the mapping technology is employed to transform

People are increasingly searching for information in social Q&A communities, especially through a new form of paid knowledge product, namely, live course. Such course provides a way for users to interact synchronously with content creators online. However, how this knowledge product is accepted and why users pay for it deserve attention from researchers. In this study, a research model was developed

The primary aim of location recommendation is to predict users’ future movement by modeling user preference. Multiple types of information have been adopted in profiling users; however, simultaneously combining them for a better recommendation is challenging. In this study, a novel location recommendation method that incorporates geographical, categorical, and social preferences with location popularity

Abstract A simple energy-efficient switching procedure is proposed to reduce the total number of switches and facilitate the capacitors matching requirements in SAR ADCs. The main idea is that the coupling capacitor (CC) is utilized as the same as the unit one, which is applied for LSB charge production. After the reset phase, only the MSB capacitor is connected to the input potential, while the other

Abstract 2D electrical resistivity inversion is a complicated nonlinear optimization problem, which is high-dimensional and non-convex. Using traditional neural networks to solve resistivity inversion problem is cost effective but suffers from trapping in local minima. In order to solve the above problem, a multi-output support vector regression (MSVR) nonlinear inversion method with limited ERI learning

Abstract In the current decade, scalability has been developed in video coding (VC) schemes to reply end-user demands and heterogeneity of networks. In this paper, a low bit-rate signal-to-noise ratio (SNR) scalable VC based on dictionary learning (DL) and sparse representation is proposed. A notable feature of SNR scalability compared to spatial and temporal versions is that there are not any limitations

Abstract The co-prime sensor array (CSA), which is an effective sparse configuration, has the drawback of generating grating lobes in passive beamforming. To mitigate this problem, we propose a novel method based on null synthesis with cancellation beams (NSCBs) under original pattern perturbations minimization. In this paper we regard the grating lobes as interference signals with known directions

Abstract Based on synchronized time interleaved (STI)analog to digital conversion system, an alternative method for ultra-wideband signals sampling has been developed and named as the generalized asynchronous time interleaved (G-ATI) sampling structure. When the input signal bandwidth is large enough, such as 50GHz and above, the STI is generally constructed by three parts: (i) the analog preprocessing

Abstract The paper considers first, the admissibility conditions for continuous 2D systems represented by Roesser model by dealing with non-strict LMIs. Secondly, admissibility and stabilization conditions using strict LMIs conditions are investigated. For these strict LMIs conditions, necessary and sufficient conditions can be directly solved with LMI toolbox since they are more traceable and reliable

Abstract Development of medical image segmentation techniques has become one of the most important challenges in many applications that employ computers-based medical image analysis techniques. However, most of current-existing medical image segmentation techniques still have poor efficiency and complexity in calculations. A new technique for X-ray bone image segmentation has been presented in this

Abstract Second-order sampling has been discussed in the contexts of 2-D frequency distributions made up of two tiling clusters with lattice systems having the same periodicity, while mixed-order sampling has been discussed for those made up of tiling clusters with lattice systems having different periodicities. However, there has been no discussion when the 2-D frequency distribution is made up of

Abstract In this paper, an algorithm of combing unitary Root-MUSIC method based on tensor mode-R and projection separation approach is proposed for multidimensional (R-D) sinusoidal parameters estimation. The model of the proposed algorithm based on tensor mode-R with the unitary matrices is firstly transferred into multiple single-sample models, and then the eigenvalue decomposition (EVD) or singular

Abstract In the field of agriculture, image processing plays a significant role in which Image compression and Encryption is the most important tool. Image processing provides applications for agriculture in detection of unwanted growth of crops and its health monitoring. Image Encryption and Compression techniques are utilized to achieve better reconstructed image. Generally, remote sensing equipment

Abstract Multi-focus image fusion plays an important role in the field of image recognition and analysis. However, current focus evaluation operators are complex and inefficiency. In this paper, a new focus evaluation operator based on max–min filter is proposed. In new focus measure, we use max–min filter with the help of average filter and median filter (MMAM) to evaluate the focus degree of source

Abstract Outdoor images are often degraded by haze, causing a change of image contrast and color values. In this paper, we propose a novel variational model for the removal of haze in a single color image, by incorporating an inter-channel correlation term into the total variation based model in Wang et al. (Pattern Recognit 80:196–209, 2018). The proposed model enables both color and gray-valued transmission

Abstract Epileptic seizure detection from the brain EEG signals is an essential step for speeding up the diagnosis that assists researchers and medical professionals. For this, various classification signal processing techniques have been developed in the traditional works. Still, they limit with the problems of increased complexity, reduced performance and insufficient classification rate. This motivates

Abstract Inclement weather existence of fog, haze, and dust generally degrades the visibility of outdoor images. Bad visibility may cause failure in computer vision applications. Existing dehazing methods cannot work well on dust haze images. Such images appear yellowish due to the absorption of blue light by dust particles. In order to solve this problem, we propose an optical compensation method

Abstract The most prominent issue relevant to the initiative multi-level inverters is how to provide a high-step staircase quasi-sinusoidal voltage against low switch numbers. This paper presents an innovative asymmetrical multi-level inverter structured by cascaded sub-multi-level inverter bonded to H-bridge inverter to unravel aforesaid issue. DC power sources of sub-multi-level inverters have been

Abstract In this paper, the problem of direction-of-arrival (DOA) estimation with a new nested array is addressed. It is known that the original two-level nested array is composed of two uniform linear arrays (ULAs), and there exist some redundant elements in their difference co-array. In order to reduce the redundancy, a new array configuration which consists of a ULA and a non-uniform linear array

Abstract Time–frequency (TF) approaches are frequently employed for source localization at low signal to noise ratio. However, TF approaches fail to achieve the desired performance for sparsely sampled signals or signals corrupted by heavy noise in an under-determined scenario when sources are not TF separable. In this study, we propose a new TF method for direction of arrival (DOA) estimation of sources

Abstract Image dehazing is a challenging task of restoring a clear image from a haze-polluted image. However, most popular dehazing methods have color shift and overexposure problems owing to the inaccurate estimation of the transmission and atmospheric light in the atmospheric scattering model. In view of the existing problems, this paper proposes a simple but effective dehazing network by learning

Abstract Up to date technological implementations of deep convolutional neural networks are at the forefront of many issues, such as autonomous device control, effective image and pattern recognition solutions. Deep neural networks generally utilize a hybrid topology of a feature extractor containing convolutional layers followed by a fully connected classifier network. The characteristic and quality

Abstract The optimal architecture of a deep feedforward neural network (DFNN) is essential for its better accuracy and faster convergence. Also, the training of DFNN becomes tedious as the depth of the network increases. The DFNN can be tweaked using several parameters, such as the number of hidden layers, the number of hidden neurons at each hidden layer, and the number of connections between layers

Abstract The separation of overlapping components is a well-known and difficult problem in multicomponent signals analysis and it is shared by applications dealing with radar, biosonar, seismic, and audio signals. In order to estimate the instantaneous frequencies of a multicomponent signal, it is necessary to disentangle signal modes in a proper domain. Unfortunately, if signal modes supports overlap

In this letter, we improve lossless intra-frame compression of color filter array (CFA) video based on Camera-Aware Multi-Resolution Analysis (CAMRA). CAMRA-based compression leverages the correlation between LH and HL subbands of wavelet-transformed CFA video frames. The key contribution of this letter is an analysis showing that the chrominance components shared by LH and HL subbands of LeGall 5/3

A raw image captured by a color filter array (CFA), such as a Bayer pattern, is usually compressed after demosaicing with some processings (denoising, deblurring, tone-mapping, and so on). However, since photographers, designers, and high-end users prefer to work with the raw image sampled by CFA (referred to as “raw image”) directly, a raw image should be compressed before demosaicing. For effective

With the advance in wireless network technique, its security becomes of paramount importance. Radio Frequency Fingerprint (RFF) is the underlying characteristic of hardware chains in transmitters, which can be used as a unique ID for specific emitter identification (SEI) and a non-cryptographic access authentication technology in physical layer to enhance wireless network security. To date, few studies

In this letter, a novel kernel function named $q$ -Rényi kernel is proposed. Based on it, a new online adaptive learning algorithm is presented, which is derived based on the recursive adaptive filtering paradigm under the reproducing kernel Hilbert space. The proposed learning algorithm is different from the conventional kernel-based learning paradigm in two senses: first, the reproducing kernel so-called

Different from traditional image super-resolution task, real image super-resolution(Real-SR) focus on the relationship between real-world high-resolution(HR) and low-resolution(LR) image. Most of the traditional image SR obtains the LR sample by applying a fixed down-sampling operator. Real-SR obtains the LR and HR image pair by incorporating different quality optical sensors. Generally, Real-SR has

Presents the table of contents for this issue of the publication.

Presents a listing of the editorial board, board of governors, current staff, committee members, and/or society editors for this issue of the publication.

The development of the smart ocean requires that various features of the ocean be explored and understood. The Underwater Internet of Things (UIoT), an extension of the Internet of Things (IoT) to the underwater environment, constitutes powerful technology for achieving the smart ocean. This article provides an overview of the UIoT with emphasis on current advances, future system architecture, applications

Recent advances in fine manipulation have led to increased interest in both scientific research works and engineering applications. Robot manipulation at a level approaching human skills is gaining attention in both industrial and individual services. A major challenge in fine manipulation is the unavoidable uncertainties and unpredictable conditions encountered in dynamic and unstructured application

The increased complexity of modern energy network raises the necessity of flexible and reliable methods for smart grid operation. To this end, this article is centered on the economic dispatch problem (EDP) in smart grids, which aims at scheduling generators to meet the total demand at the minimized cost. This article proposes a fully distributed algorithm to address the EDP over directed networks

In this article, a rapid and precise position measurement method based on joint spatial phase is studied for linear motors. First, a low-cost mover position measurement system is designed on the basis of motion characters of linear motors. The target image is an aperiodic fence stripe. The image sequences with the movement of the mover are recorded quickly by linear charge coupled device (CCD) camera

Vision systems are the core information collection module in outdoor industrial systems such as factory inspection robots. However, haze greatly reduces working efficiency. Existing dehazing methods have two problems—first, they are not specifically designed for the industrial systems; second, these methods include several assumptions in their design processes and imaging models, leading to unsatisfactory

This article presents an automatic recognition of power quality events (PQEs) by integrating variational mode decomposition (VMD) with Hilbert transform (HT) and the proposed online P-norm adaptive extreme learning machine (OPAELM). The robust parameters estimation capability from the highly nonstationary PQE patterns is presented using VMDHT method and a novel mode selection scheme is introduced based

The problem of inefficient and unevenly distributed spectrum usage in industrial wireless networks has led to the emergence of the concept of industrial cognitive radio (CR) networks, which have particularly important applications in automotive industry. Industrial CR networks are planned to function in a wide spectrum range; therefore, they have high energy consumption because of frequency switching