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The endoscopy procedure has demonstrated great efficiency in detecting stomach lesions, with extensive numbers of endoscope images produced globally each day. The content‐based gastric image retrieval (CBGIR) system has demonstrated substantial potential in gastric image analysis. Gastric precancerous diseases (GPD) have higher prevalence in gastric cancer patients. Thus, effective intervention is crucial at the GPD stage. In this paper, a CBGIR method is proposed using a modified ResNet‐18 to generate binary hash codes for a rapid and accurate image retrieval process. We tested several popular models (AlexNet, VGGNet and ResNet), with ResNet‐18 determined as the optimum option. Our proposed method was valued using a GPD data set, resulting in a classification accuracy of 96.21 ± 0.66% and a mean average precision of 0.927 ± 0.006, outperforming other state‐of‐art conventional methods. Furthermore, we constructed a Gastric‐Map (GM) based on feature representations in order to visualize the retrieval results. This work has great auxiliary significance for endoscopists in terms of understanding the typical GPD characteristics and improving aided diagnosis. [ABSTRACT FROM AUTHOR]

Based on the relaxation digital‐to‐analog converter (ReDAC) architecture and the capacitor charge/discharge function under discrete time conditions, this paper proposes a new mathematical model for the output voltage of the ReDAC to implement the unconstrained relaxation DAC (Uc‐ReDAC). The system clock calibration is not required. An adaptive probabilistic binary particle swarm optimization (AP‐BPSO) algorithm is proposed for solving the binary coding configuration problem under the Uc‐ReDAC model. Simulation results show that the 8‐bit (10‐bit) Uc‐ReDAC has an average sampling rate of 7.9 MS/s (6.76 MS/s). [ABSTRACT FROM AUTHOR]

In the age of the artificial intelligence of things (AIoT), wearable devices have been extensively developed for smart healthcare. This paper proposes a self‐powered and self‐sensing lower‐limb system (SS‐LS) with negative energy harvesting and motion capture for smart healthcare. The SS‐LS achieves self‐sustainability via a half‐wave electromagnetic generator (HW‐EMG) that recovers negative work from walking with a low cost of harvesting. Additionally, the motion capture function of the system is achieved by the three‐channel triboelectric nanogenerator (TC‐TENG) based on binary code, which can accurately detect the angle and direction of the knee joint rotation. The bench test experiment indicates that the HW‐EMG has an average output power of 11.2 mW, sufficient to power a wireless sensor. The three‐channel voltage signal of TC‐TENG fits well with the binary signal, which can precisely detect the angle and direction of rotation. Furthermore, the SS‐LS demonstrates an identification accuracy of 99.68% and a motion detection accuracy of 99.96% based on an LSTM deep learning model. Demonstrations of Parkinson's disease and fall detection and monitoring of three training modes (sit‐and‐stand, balance, and walking training) are also performed, which exhibit outstanding sensing capabilities. The SS‐LS is highly promising in sports rehabilitation medicine and can contribute to the development of smart healthcare. [ABSTRACT FROM AUTHOR]

This paper presents a low‐power self‐contained overvoltage detector. Compared with conventional detectors that consist of stacked Zener diodes, the proposed structure can trim the threshold with binary codes to accommodate system‐level changes. The proposed structure enables trimming by adding a decoder, a biasing circuit, and switches in parallel with Zener diodes. The newly configured structure forms a standalone detector that can operate independently and be powered from the supply under detection with negligible current addition. The proposed structure is applicable to any high‐voltage process that contains N‐type isolation layer and needs no high‐voltage device. The proposed circuit with three bits adjustment circuit was fabricated in a 0.18 μm Bipolar‐CMOS‐DMOS (BCD) process, the overvoltage threshold can be adjusted from 8 to 38 V with post trim variation of ±2.5 V. The measured quiescent current was around 0 μA at 10 V and 28 μA at 38 V, which was comparable to the current consumption in a conventional structure with 38 V overvoltage threshold. © 2022 Institute of Electrical Engineers of Japan. Published by Wiley Periodicals LLC. [ABSTRACT FROM AUTHOR]

Summary: This paper proposes a coded modulation scheme based on frequency shift keying (FSK) modulation and a simple binary permutation code. FSK detection is based on the knowledge of the probability density function (PDF) of the noise and the attenuation of the channel, called FSK "Soft‐Decision" (FSK/SD) detection. We introduce an approximation of the FSK/SD, called FSK "Select Largest" (FSK/SL). We compare the FSK/SL detection with the classical PDF‐based detection techniques, such as FSK/SD and spread‐FSK (SFSK), for both coded and uncoded transmission. As a practical application, we use the power line communication (PLC) channel. We analyze and compare the performances for a narrowband PLC channel with attenuation and impulse noise. [ABSTRACT FROM AUTHOR]

A single‐element antenna is unfit for application in most wireless systems and an alternative is an array of antenna. The desire to reduce weight and cost of antenna arrays gave rise to sparse arrays. The design of a sparse antenna array requires an optimization process, which is time‐consuming for large arrays. In order to accelerate the optimization process, a method combining the numerical Green's function (NGF) and genetic algorithm (GA) is presented in this paper. In the proposed method, binary coding is applied to describe the status of antenna elements, and GA optimization is performed to sparsify the array subject to constraint on the peak side lobe level (PSLL). The PSLL is calculated efficiently by the NGF. Simulation results are presented to illustrate the advantage of the proposed method. It is shown that the proposed method significantly reduces the optimization time. [ABSTRACT FROM AUTHOR]

Combinatorial t‐designs have nice applications in coding theory, finite geometries, and several engineering areas. A classical method for constructing t‐designs is by the action of a permutation group that is t‐transitive or t‐homogeneous on a point set. This approach produces t‐designs, but may not yield (t+1)‐designs. The objective of this paper is to study how to obtain 3‐designs with 2‐transitive permutation groups. The incidence structure formed by the orbits of a base block under the action of the general affine groups, which are 2‐transitive, is considered. A characterization of such incidence structure to be a 3‐design is presented, and a sufficient condition for the stabilizer of a base block to be trivial is given. With these general results, infinite families of 3‐designs are constructed by employing almost perfect nonlinear functions. Some 3‐designs presented in this paper give rise to self‐dual binary codes or linear codes with optimal or best parameters known. Several conjectures on 3‐designs and binary codes are also presented. [ABSTRACT FROM AUTHOR]

Univariate data has been the focus of optimal design for generalized linear models. It is common practice to conduct experiments with multiple dependent responses that are modelled using regression techniques. To design the experiment for all these responses, one needs a multivariate distribution supporting a previously chosen data model. The T‐optimal criterion is used to discriminate between two competing models. The designs that are optimal for discrimination between two models may be unsuitable for describe the quality of predictions for test data. G‐optimal criterion overcomes this restriction by minimizing the maximum variance of the predicted values. The design of experiments with dependent bivariate binary data is a topic we discuss in this paper. For dependent bivariate binary data, a technique for deriving TG‐optimal experimental designs using Copula is shown. The new compound TG‐criterion satisfy the dual aim to selecting the true model and minimizing the maximum prediction variance. The equivalence theorem is demonstrated and proved for the new compound criterion. A numerical example is presented to show the properties of the new compound criterion for bivariate binary setting and its value in meeting the dual aims. [ABSTRACT FROM AUTHOR]

Summary: In this paper, we propose a simple method for generating short‐length rate‐compatible codes that are robust to noncoherent detection forM‐PSK constellations. For any given constellation set, first we use a greedy algorithm to construct a family of rotationally invariant codes. Then, by properly modifying such codes, we obtain a new family of codes that are robust to noncoherent detection. We briefly discuss the optimality of the constructed codes for special cases of BPSK and QPSK constellations. Our method provides an upper bound for the length of optimal codes with a given desired noncoherent distance. We also derive a simple asymptotic upper bound on the frame error rate (FER) of such codes and provide some simulations. Finally, the problem of designing binary codes that are robust to noncoherent detection for QPSK constellation is briefly discussed. [ABSTRACT FROM AUTHOR]

This paper presents an EMI (Electromagnetic interference) reduction high‐voltage source driver circuits for large‐size printed OLED (Organic Light Emitting Diode) panel. The proposed 10‐bit source driver output glitch reduces by 94.2% because the coding mode is changed from traditional binary to Gray code. The EMI of source driver to pixel circuit and touch panel is reduced owing to smaller glitch. The proposed Gray code source driver decreases power consumption at the same time. [ABSTRACT FROM AUTHOR]

Similarity search, that is, finding similar items in massive data, is a fundamental computing problem in many fields such as data mining and information retrieval. However, for large‐scale and high‐dimension data, it suffers from high computational complexity, requiring tremendous computation resources. Here, based on the low‐power self‐selective memristors, for the first time, we propose an in‐memory search (IMS) system with two innovative designs. First, by exploiting the natural distribution law of the devices resistance, a hardware locality sensitive hashing encoder has been designed to transform the real‐valued vectors into more efficient binary codes. Second, a compact memristive ternary content addressable memory is developed to calculate the Hamming distances between the binary codes in parallel. Our IMS system demonstrated a 168× energy efficiency improvement over all‐transistors counterparts in clustering and classification tasks, while achieving a software‐comparable accuracy, thus providing a low‐complexity and low‐power solution for in‐memory data mining applications. [ABSTRACT FROM AUTHOR]

In this paper, we present a useful technique for implementing practical static program analyzers that use widening. Our technique aims to improve the efficiency of the conventional widening-with-thresholds technique at a small precision compromise. In static analysis, widening is used to accelerate (or converge) fixed point iterations. Unfortunately, this acceleration often comes with a significant loss in analysis precision. A standard method to improve the precision is to apply the widening with a set of thresholds. However, this technique may significantly slow down the analysis, because in practice it is commonplace to use a large set of thresholds. In worst case, the technique increases the analysis cost by the size N of the threshold set. In this paper, we propose a technique to reduce the worst case by [ABSTRACT FROM AUTHOR]

Empirical systems research is facing a dilemma. Minor aspects of an experimental setup can have a significant impact on its associated performance measurements and potentially invalidate conclusions drawn from them. Examples of such influences, often called hidden factors, include binary link order, process environment size, compiler generated randomized symbol names, or group scheduler assignments. The growth in complexity and size of modern systems will further aggravate this dilemma, especially with the given time pressure of producing results. How can one trust any reported empirical analysis of a new idea or concept in computer science? DataMill is a community-based services-oriented open benchmarking infrastructure for rigorous performance evaluation. DataMill facilitates producing robust, reliable, and reproducible results. The infrastructure incorporates the latest results on hidden factors and automates the variation of these factors. DataMill is also of interest for research on performance evaluation. The infrastructure supports quantifying the effect of hidden factors, disseminating the research results beyond mere reporting. It provides a platform for investigating interactions and composition of hidden factors. This paper discusses experience earned through creating and using an open benchmarking infrastructure. Multiple research groups participate and have used DataMill. Furthermore, DataMill has been used for a performance competition at the International Conference on Runtime Verification (RV) 2014 and is currently hosting the RV 2015 competition. This paper includes a summary of our experience hosting the first RV competition. Copyright © 2015 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

Semisupervised classification aims to construct a classifier by making use of both labeled data and unlabeled data. This paper proposes a semisupervised classifier based on a piecewise linear regression model implemented by using a gated linear network. The semisupervised classifier is constructed in two steps. In the first step, instead of estimating the break points of a piecewise linear model directly, a label‐guided autoencoder‐based semisupervised gating mechanism is designed to generate binary gate control signals to realize the partitioning. In the second step, the piecewise linear model is first transformed into linear regression form, and the linear parameters are then optimized globally by a Laplacian regularized least squares (LapRLS) algorithm using a kernel function comprising the gate control signals obtained in the first step. Moreover, the composed kernel function is used as a better similarity function for the graph construction. As a result, we capture data manifold from both labeled and unlabeled data, and the data manifold is ingeniously incorporated into both the kernel and the graph Laplacian in LapRLS. Numerical experiments on various real‐world datasets exhibit the effectiveness of the proposed method. © 2020 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc. [ABSTRACT FROM AUTHOR]

Summary: Binary sensors are special sensors that only transmit one‐bit information at each time and have been widely applied to environmental awareness and medical monitoring. This paper is concerned with the distributed fusion Kalman filtering problem for a class of binary sensor systems. A novel uncertainty approach is proposed to better extract valid information from binary sensors at switching instant. By minimizing a local estimation error covariance, the local robust Kalman estimates are firstly obtained. Then, the distributed fusion Kalman filter is designed by resorting to the covariance intersection fusion criterion. Finally, a blood oxygen content model is employed to show the effectiveness of the proposed methods. [ABSTRACT FROM AUTHOR]

We investigate the weight distribution of random binary linear codes. For 0 < λ < 1 and n→∞ pick uniformly at random λn vectors in F2n and let C≤F2n be the orthogonal complement of their span. Given 0 < γ < 1/2 with 0 < λ < h(γ) let X be the random variable that counts the number of words in C of Hamming weight γn. In this paper we determine the asymptotics of the moments of X of all orders o(nlogn). [ABSTRACT FROM AUTHOR]

In this paper, we present examples of codes all of whose weight classes support 1‐designs, with duals whose classes include two that support 2‐designs. We can find these examples in the triply even binary codes of length 48, which have been classified by Betsumiya and Munemasa. [ABSTRACT FROM AUTHOR]

ABSTRACT The cyclostationarity property of GNSS signals has not been well addressed in the specialized literature so far and its potential usefulness in the context of a GNSS receiver is yet to be studied. In our paper, we build a novel analytical framework for exploiting the cyclostationarity properties of BOC-modulated GNSS signals and we illustrate how these properties may be used in the context of a multi-system multi-frequency positioning receiver in the future. We also introduce an algorithm based on the Spectral Correlation Function (SCF) for signal identification in the context of a cognitive positioning architecture and we compare it with classical Power Spectral Density (PSD) analysis. Statistical performance is studied in the presence of stationary wideband and narrowband noise sources. It is shown that distinguishing signals based on cyclostationarity properties has high potential in future cognitive positioning receivers. Copyright © 2014 Institute of Navigation. [ABSTRACT FROM AUTHOR]

As one of the hot topics in the field of computer vision research, face recognition technology has received significant attention due to its potentiality for a wide range of applications in government as well as commercial purposes. In practical applications, although several existing face recognition methods have achieved good performances in specific scenes, they easily suffer from a sharp decline in recognition rate if affected by different conditions of light, expression, posture and occlusion. Among many factors, influences of complex illuminations on face recognition are particularly significant. To further improve the performance of the existing local binary pattern (LBP) operator, neighbourhood weighted average LBP (NWALBP) is first proposed for fully considering the strong correlations between pixel pairs in the neighbourhood, which extends the traditional LBP uni‐layer neighbourhood template window to the bi‐layer neighbourhood template window and calculates the weighted average of bi‐layer neighbourhood pixels in each direction. Then, inspired by center symmetric LBP (CS‐LBP), centre symmetric NWALBP (CS‐NWALBP) is further proposed, which can effectively reduce computation complexity by only comparing the weighted average values of the neighbourhood pixels that are symmetric about the centre pixel. Finally, by combining the merit of histogram of oriented gradient (HOG), a feature fusion algorithm named CS‐NWALBP+HOG is suggested. Several experiments have eventually demonstrated that our proposed algorithms have more robust performance under complex illumination conditions if compared with many other latest algorithms. [ABSTRACT FROM AUTHOR]

This letter proposes an augmented scheme of LT codes to improve the decoding success rate. The method involves substituting the 1‐s in full‐degree columns of the generator matrix of conventional LT codes with binary extension field elements and simultaneously increasing the ratio of full‐degree columns in the ideal soliton distribution. For non‐full‐degree columns, we retain the nonzero elements as 1‐s in the conventional LT codes generator matrix to preserve computational efficiency. Compared to conventional LT codes, the proposed method enhances the linear independence of the generator matrix, leading to a higher decoding success rate with minimal data packets. Experimental results demonstrate the effectiveness of the method at improving the performance of LT codes, with close to 100% decoding success rate achieved with around 5% data redundancy. [ABSTRACT FROM AUTHOR]

This paper proposes a pipelined decoder architecture for generalised concatenated (GC) codes. These codes are constructed from inner binary Bose–Chaudhuri–Hocquenghem (BCH) and outer Reed–Solomon codes. The decoding of the component codes is based on hard decision syndrome decoding algorithms. The concatenated code consists of several small BCH codes. This enables a hardware architecture where the decoding of the component codes is pipelined. A hardware implementation of a GC decoder is presented and the cell area, cycle counts as well as the timing constraints are investigated. The results are compared to a decoder for long BCH codes with similar error correction performance. In comparison, the pipelined GC decoder achieves a higher throughput and has lower area consumption. [ABSTRACT FROM AUTHOR]

Petroleum explorers regularly make numerous forecasts for prospects and wells, but the quality of their predictions has inadequate documentation. Here I discuss the forecasting abilities of individual explorers inferred from a survey about future exploration wells, some of which were drilled in late 2018 and 2019. A total of 104 petroleum explorers provided 7,068 answers about eleven wells and about themselves, and subsets from this dataset were used to study their predictions. The survey participants were diverse, and most had M.Sc. or Ph.D. degrees with >16 years of industry experience working as individual contributors and/or middle managers for oil companies. Assessments of the geological probability of success (PoS) by different explorers for the same well were highly variable, and average assessments poorly discriminated between future discoveries and dry holes. Point (binary or multiple choice) forecasts by explorers participating in the survey were, on average, only slightly better than random guessing. The participants' highest academic degree had little apparent influence on the quality of the point forecasts. Years of experience resulted in only slightly better correlation with increasing quality of forecasts. Survey participants more familiar with the prospects (those who generated them or evaluated proprietary company data) made, on average, worse exploration forecasts than those who studied only the limited publicly available information provided with the survey. The duration of time spent on the survey did not affect the quality of forecasts. The aggregated opinion of all explorers (wisdom of the crowd) may be beneficial in assessments of the geological PoS, but perhaps not so when forecasted outcomes have binary or multiple possibilities. The generally poor forecasting abilities of individual petroleum explorers may surprise some decision‐makers and investors. However, many of the study results are based on relatively small datasets and should be treated as preliminary. Further research with larger datasets is necessary to replicate, validate and explain the findings of this study. [ABSTRACT FROM AUTHOR]

ABSTRACT In this paper, a high dynamic range digital pixel sensor (DPS) is presented. Each pixel receives light illumination and converts the intensity level to a digital code. The analog-to-digital conversion is performed in-pixel. The pixel structure incorporates light to pulse signal converter and compact in-pixel dynamic counter to convert the pulse signal to binary coded data. Different variations of the custom design dynamic counters are analyzed in a 0.18 µm technology, and their application in the DPS is investigated. It is shown that due to the limited clock frequency required in the sensor pixel, the dynamic counter can be incorporated as a pulse to binary code converter. Performance specifications such as power consumption, dynamic range and resolution of the presented structure are investigated using a 100 × 100 pixel sensor. The presented sensor is an effective solution for use in digital field programmable smart image sensors and vision chips since the pixel output is a regular binary code while no global digital counter bus is required. The fill factor of the presented design remains close to that of typical DPSs. Copyright © 2013 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

The design of a 4‐bit encoder with a bubble error correction of first order is described in this study. Since encoder restricts speed of the flash analogue‐to‐digital converter (ADC), therefore, an improved and faster encoder is an essential requirement to push its limits. Encoder is divided into two parts: one‐hot code generator [or bubble error corrector (BEC)] and binary encoder. Binary encoder proposed in this study is the modified Fat‐Tree encoder of types I and II. Three types of BECs which have been compared in this study are OR gate based, NAND gate based and the proposed BEC. The proposed BEC consumes less power and provides better speed as compared to NAND based and OR gate based BECs. It can be further employed for higher order bubble correction as well. The proposed BEC consumes dynamic power of 87.071 μW and leakage power of 18.3563 pW exhibiting the delay of 38.3 ps with 1.8 V supply voltage and 1 GHz clock frequency. It has a power‐delay product of 3.335 fJ, energy‐delay product of 127.7305 Js and an intrinsic area of 4.753 mm2. [ABSTRACT FROM AUTHOR]

A connected component analysis from a binary image is a popular character segmentation method but occasionally fails to segment the characters owing to image noise and uneven illumination. A multimethod binarization scheme that incorporates two or more binary images is a novel solution, but selection of binarization methods has never been analyzed before. This paper reveals the best combination of binarization methods and parameters and presents an in-depth analysis of the multimethod binarization scheme for better character segmentation. We carry out an extensive quantitative evaluation, which shows a significant improvement over conventional single-method binarization methods. Experiment results of six binarization methods and their combinations with different test images are presented. [ABSTRACT FROM AUTHOR]

The second-generation specification of the digital video broadcasting for satellite (DVB-S2) was developed in 2003 with the aim of improving the existent broadcasting standard DVB-S. The main new features introduced by DVB-S2 included increased baud rates, higher cardinality constellations (up to 32 points), and more efficient binary codes. The extension to DVB-S2, approved in 2014 with the name DVB-S2X, together with continuous technological evolution, moves further steps in this direction, with the use of constellations with cardinality up to 256 points, improved granularity of modulation and coding schemes, and the possibility to increase the baud rate. In this scenario, it is important to be able to ascertain what is the best transceiver structure, starting from the choice of the shaping pulse and the baud rate of the transmitted signals and ending with the most promising receiver architectures, with the aim of maximizing the spectral efficiency. In this paper, we will discuss some of the aspects of this investigation, namely, the optimization of transmission parameters and the description of an efficient receiver. We will then assess the performance of the proposed scheme in comparison with a classical DVB-S2 architecture. Some synchronization aspects will also be discussed, to account for the impairments introduced by the channel. Copyright © 2015 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

The increasing development and utilisation of optical camera communications offer an excellent opportunity for the implementation of the smartphone‐to‐smartphone‐based visible light communications (S2SVLC) system. In this study, the authors experimentally demonstrate that the S2SVLC system can support high‐quality multimedia transmissions by the investigation of the mean square error estimation, peak signal‐to‐noise (PSNR) degradation, bit error rate (BER), and data rate achieved. The experimental analysis has been carried out for different typical practical background illuminations (i.e., normal illumination and dark condition), distances, tilting, and rotation angles. The PSNR and BER are determined for different frame sizes in the S2SVLC system to provide an insight of system performance. Those results indicate that the data transmission at different conditions significantly impacts the system's performance. [ABSTRACT FROM AUTHOR]

Color, texture, and shape act as important information for images in human recognition. For content‐based image retrieval, many studies have combined color, texture, and shape features to improve the retrieval performance. However, there have not been many powerful methods for combining all color, texture, and shape features. This study proposes a content‐based image retrieval method that uses the combined local and global features of color, texture, and shape. The color features are extracted from the color autocorrelogram; the texture features are extracted from the magnitude of a complete local binary pattern and the Gabor local correlation revealing local image characteristics; and the shape features are extracted from singular value decomposition that reflects global image characteristics. In this work, an experiment is performed to compare the proposed method with those that use our partial features and some existing techniques. The results show an average precision that is 19.60% higher than those of existing methods and 9.09% higher than those of recent ones. In conclusion, our proposed method is superior over other methods in terms of retrieval performance. [ABSTRACT FROM AUTHOR]

Limited to the structure of traditional light‐emitting devices, electronic devices that can directly convert machine language into human visual information without introducing any back‐end circuit are still not easy to achieve. Based on a specially designed three‐phase co‐planar electrode structure, a new type of three‐phase alternating current driven organic light‐emitting device with the integration of emission and control functions, full‐color tunability and simple device structure is demonstrated in this study. We integrate the light‐emitting function of color‐tunable light‐emitting devices and the switching of three triodes in a single three phase organic light‐emitting device. The state control of luminous color and luminance intensity merely requires the introduction of a kind of machine language, that is an easy‐to‐program 6‐bit binary number coded digital signals. The color adjustable area covers 66% of the color triangle of the National Television System Committee. Such simple and easy‐to‐integrate light‐emitting system has great potential applications in the next‐generation man‐machine interface. [ABSTRACT FROM AUTHOR]

Polarimetric synthetic aperture radar (POLSAR) systems provide high resolution images containing polarimetric information. So, they have high capability in land cover classification. In this work, a binary coding‐based polarimetric‐morphological (BCPM) feature extraction is proposed for POLSAR image classification. At first, a set of polarimetric features is proposed. Then, a new morphological framework is introduced for contextual feature extraction from the POLSAR cube. The coherence matrix is composed from diagonal and non‐diagonal elements with different information. These elements are analysed separately in the proposed method. Moreover, the amplitude and phase components of the non‐diagonal elements are individually analysed using morphological filters by reconstruction. Finally, a binary coding‐based polarimetric‐spatial feature reduction, which uses the first order statistics, is proposed for feature transformation. The experiments on three real POLSAR images and a synthetic dataset show the superior performance of BCPM compared to several classification methods. [ABSTRACT FROM AUTHOR]

Multiple sets of measurements on the same objects obtained from different platforms may reflect partially complementary information of the studied system. The integrative analysis of such data sets not only provides us with the opportunity of a deeper understanding of the studied system but also introduces some new statistical challenges. First, the separation of information that is common across all or some of the data sets and the information that is specific to each data set is problematic. Furthermore, these data sets are often a mix of quantitative and discrete (binary or categorical) data types, while commonly used data fusion methods require all data sets to be quantitative. In this paper, we propose an exponential family simultaneous component analysis (ESCA) model to tackle the potential mixed data types problem of multiple data sets. In addition, a structured sparse pattern of the loading matrix is induced through a nearly unbiased group concave penalty to disentangle the global, local common, and distinct information of the multiple data sets. A Majorization‐Minimization–based algorithm is derived to fit the proposed model. Analytic solutions are derived for updating all the parameters of the model in each iteration, and the algorithm will decrease the objective function in each iteration monotonically. For model selection, a missing value–based cross validation procedure is implemented. The advantages of the proposed method in comparison with other approaches are assessed using comprehensive simulations as well as the analysis of real data from a chronic lymphocytic leukaemia (CLL) study. Here, we propose an exponential family SCA (ESCA) model for the integrative analysis of multiple data sets of mixed data types, such as quantitative, binary, or count, and introduce group concave penalty to induce structured sparsity on the loading matrix to separate common (global and local) and distinct variation in such data sets. The model is applied for the exploratory data analysis of quantitative drug response, gene expression, methylation, and binary mutation data sets measured on the same objects. [ABSTRACT FROM AUTHOR]

This letter proposes a high isolation two‐element multiple input multiple output (MIMO) antenna by using a wideband pixel neutralization line (NL). The design procedures are simplified as follows: (1) Obtaining the Y‐parameters of the original two‐element antenna with a grid of microstrip stubs, and discrete ports are inserted among microstrip stubs; (2) obtaining the binary codes of the optimum route. Importing Y‐parameters into MATLAB, and using a genetic algorithm to obtain the optimum connection route by design formulas upon scattering matrix which guarantees high isolation; (3) translating the binary codes into the actual connection metallic lines; (4) adding the designed pixel NL and appropriate matching branches into EM simulator to optimize the antenna; (5) obtaining a high isolation two‐element antenna. The original two‐element antenna has poor isolation with the main path coupling, and the pixel NL provides an auxiliary coupling path between two elements. By adjusting pixel NL, the magnitude strengths of two coupling signals realize the same, while the phases are exactly opposite. Therefore, the wideband high isolation between antenna elements is realized. To verify the practicability of the proposed pixel decoupling neutral line, a reference and proposed two‐element MIMO antennas are fabricated and measured. In the experiment, the isolation of the proposed two‐element antenna with an edge‐to‐edge distance of 0.0943λ0 (λ0 is the wavelength in free space at the center frequency) is enhanced by about 17 dB in the working frequency band from 0.975 to 1.025 GHz. Besides, an L‐typed feeding network is added to guarantee a good matching condition. The proposed two‐element antenna has a size of 0.617λ0 × 0.667λ0, and the dimension of each radiation patch is 0.3267λ0 × 0.0725λ0. The proposed GA algorithm‐based decoupling technique has a significant superiority over traditional ones. Efficient, simple, and one‐time EM simulation are its major advantages, which can liberate the RF engineer from the heavy debugging work. [ABSTRACT FROM AUTHOR]

With more and more smartphones with Intel inside available, the compatibility issues of Android applications have been rising. The efficiency on the emulated architecture is best translated into efficiency on the target machine if target instructions also operated on register operands. However, conventional binary translators of popular binary translators do not take into account instruction dependency among two or more basic blocks. This results in performance degradation because of intertranslation block dependency. Actually, x86 binary translators do not take into account instruction dependency within a basic block. Binary translation makes use of one or two registers for the majority of translation blocks. This is because the translation block corresponds to a guest instruction, which in turn the amount of work is not large. Even though there are no dependencies between translation blocks, false dependencies are generated by the same register usage order. In order to maximize the parallelism within a basic block, we maintain two different register usage orders, applying them in turn. This approach resolves the problem and outperforms conventional approach by up to around 27% for some cases. Copyright © 2014 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

Because of the congestion of current navigation signals in the L band, the frequency band between 5010 and 5030 MHz allocated as C band with smaller ionospheric errors can be taken as a candidate band for global navigation satellite system (GNSS). The main objective of C band signal design is to achieve band limitation, compatibility, multipath resistance, satisfactory tracking, and acquisition performance. The minimum shift keying (MSK) chip waveform has been proven to be effective in providing better spectrum confinement and a constant envelope. However, the MSK chip waveform with an arbitrary binary coded symbol (BCS) may not meet the requirements of the C band. Thus, the BCS sequence ([ s0, s1,⋯ , s n − 1], f c) = ([1,1,1,1,−1,−1,1,−1,1,−1],1) is obtained by means of a thorough computer search for low autocorrelation side lobes based on a Neuman-Hofman code of length 10 with MSK pulses form MSK-BCS ([1,1,1,1,−1,−1,1,−1,1,−1],1). It is proved to have better autocorrelation with a sharp main lobe and smaller side lobes, larger Gabor bandwidth, smaller Cramér-Rao lower bound, and less multipath error; more importantly, it can satisfy the threshold of leakage out of band. It will be of great significance for signal design in C band. © 2016 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc. [ABSTRACT FROM AUTHOR]

In this study, a novel solution is introduced to deal with excessive signal attenuation in distribution transformers for power line communication in smart grids. The results presented were not achievable before proposing this solution because of the filtering action of transformer. The solution is based on exploiting a unique frequency resonance spotted in transformer windings at 490 kHz with an amplifying gain (∼2 V/V) and a bandwidth about 40 kHz. It was successfully investigated to transmit a communication signal through 15 kVA distribution transformer. The 40 kHz bandwidth and the associated amplifying gain allowed fast and efficient transmission of data, which was not feasible before. The error of a coded binary phase shift keying signal propagating through a distribution transformer was measured in the laboratory. This simple and effective solution avoids costly hardware, such as bypassing circuits, and does not require sophisticated communication modulation schemes such as orthogonal frequency division multiplexing. A full model was developed for system simulations. The work evaluated factors that may influence the resonance frequency such as distribution cables and transformer ageing. All the simulated results were verified experimentally and met the expectations of the presented solution. [ABSTRACT FROM AUTHOR]

The data rate of a Tomlinson-Harashima (TH) precoder is limited by the delay in the feedback path of its infinite impulse response (IIR) filter that cancels the channel's post-cursor intersymbol interference (ISI). One reason for long loop delays is the requirement to perform the ISI subtraction from the data signal in binary arithmetic in order to properly execute the modulo (MOD) operation, which stabilises the IIR filter and limits the transmitter amplitude. The restriction to binary arithmetic is unfortunate, because some filter subcomponents such as, e.g. adder trees are often implemented in a faster data format that has no slow carry propagation [e.g. the carry-save adder (CSA) format]. This paper proposes a novel architecture for TH precoders in which the MOD operation is taken out of the loop, so that the remaining IIR filtering is performed entirely in CSA arithmetic to reduce the feedback delay as no conversion to binary format is required within the loop. With the pipelining technique applied, the filter's feedback delay reduces to the propagation delay of a multiply-accumulate unit operated with CSA arithmetic. The proposed concept was verified in a 14 nm CMOS test chip with multi-level signalling (NRZ, 4-/8-/16-PAM). [ABSTRACT FROM AUTHOR]

Summary: Hashing techniques have been seen huge adoption in large‐scale retrieval owing to the computational and storage efficiencies of binary codes. However, the binary codes might not preserve the semantic similarity powerfully and lead to poor accuracy. To evade binary limitation but remain hashing superiority, this paper introduces a novel asymmetric hashing framework for distance variety preserving, which yields preferable performance via real‐valued query and multi‐valued database with shorter code length. Concretely, a binary sparse representation is proposed for multivalued database encoding to make computation and storage complexity tolerable. By exploiting the supervised information, we learn a projective matrix that project data onto a sub‐space in which the similarity between realvalued query and multi‐valued database can be measured. Due to the discrete constraints, for different discrete variables, we present different meticulous discrete solutions for their sub‐problems. Exhaustive experiments on three multilabel datasets demonstrate our approach outperforms most state‐of‐the‐art hashing methods. [ABSTRACT FROM AUTHOR]

Merging cryptographic primitive technologies and physical unclonable functions (PUFs) have become a new paradigm of one‐way encryption. Herein, the authors report a dynamic PUF cryptographic primitive based on plasmonic fluorescence blinking from single or a few dye molecules embedded within the nanogaps of plasmonic patch nanoantennas. This cryptographic primitive carries two sets of high‐capacity optical codes: the fluorescence blinking of the embedded dye molecules and multi‐color light scattering enabled by the plasmonic nanoantennas. The former allows the generation of temporal binary codes from a large number of individual plasmonic patch nanoantennas by holding either "1" (bright state) or "0" (dark state), while the latter provides a permanent color‐based novenary code that acts as a decryption channel for authentication. Benefiting from the high electromagnetic field localized within the nanogaps and the large Purcell enhancement of the plasmonic nanoantennas, the fluorescence blinking is readily detectable by a common fluorescence microscope with a mercury arc lamp as a low‐power excitation source. The developed dynamic PUF codes are robustly and accurately authenticated by a self‐programmed computer vision algorithm. This study revolutionizes the conventional static PUF encryption to nanophotonics‐based dynamic encryption, opening a new avenue for next‐generation advanced anti‐counterfeiting. [ABSTRACT FROM AUTHOR]

In content‐based image retrieval (CBIR), primitive image signatures are critical because they represent the visual characteristics. Image signatures, which are algorithmically descriptive and accurately recognized visual components, are used to appropriately index and retrieve comparable results. To differentiate an image in the category of qualifying contender, feature vectors must have image information's like colour, objects, shape, spatial viewpoints. Previous methods such as sketch‐based image retrieval by salient contour (SBIR) and greedy learning of deep Boltzmann machine (GDBM) used spatial information to distinguish between image categories. This requires interest points and also feature analysis emerged image detection problems. Thus, a proposed model to overcome this issue and predict the repeating pattern as well as series of pixels that conclude similarity has been necessary. In this study, a technique called CBIR‐similarity measure via artificial neural network interpolation (CBIR‐SMANN) has been presented. By collecting datasets, the images are resized then subject to Gaussian filtering in the pre‐processing stage, then by permitting them to the Hessian detector, the interesting points are gathered. Based on Skewness, mean, kurtosis and standard deviation features were extracted then given to ANN for interpolation. Interpolated results are stored in a database for retrieval. In the testing stage, the query image was inputted that is subjected to pre‐processing, and feature extraction was then fed to the similarity measurement function. Thus, ANN helps to get similar images from the database. CBIR‐SMANN have been implemented in the python tool and then evaluated for its performance. Results show that CBIR‐SMANN exhibited a high recall value of 78% with a minimum retrieval time of 980 ms. This showed the supremacy of the proposed model was comparatively greater than the previous ones. [ABSTRACT FROM AUTHOR]

In order to train an end‐to‐end model for better performance in distinguishing superclasses and make the model more sensitive to inter‐class differences, the authors propose a Feature Context Network (FCNet), a novel ensemble framework for image retrieval based on clustering (EFC) and metric learning. In the authors' approach, the EFC framework consists of one common feature extractor and multiple learning branches. This tree‐like structure not only promotes the stability of the training process but also keeps the diversity by using multiple branches. Each branch is learnt by an independent random re‐labelling operation that distributes original classes into superclasses. In such a way, the framework thus can accelerate the training process. To make the EFC framework focus on the different attributes across the classes, the authors utilize k‐means clustering to divide the training set into subsets and train the model sequentially with those subsets. Meanwhile, to reduce the impact of over‐fitting problems, the authors design a branch weight structure during training. Further, FCNet fusions different scales of the neighbourhood information and consequently makes the feature map learn richer information with the different receptive fields. Simultaneously, it can reduce the layer of the network and the number of model parameters. Extensive experiments demonstrate that this approach outperforms the tested representative methods on CARS‐196, CUB‐200‐2011 datasets. [ABSTRACT FROM AUTHOR]

Aim: The species pool specific for a site includes all species from the region that are theoretically able to live in the site's particular ecological conditions. The absent portion of the site‐specific species pool forms the site's dark diversity, which is unobservable and can only be estimated. Most existing methods to designate dark diversity act in a binary fashion. Here, we argue that the species pool is more suitably defined as a fuzzy set, present a method to estimate probabilistic species pools using pairwise co‐occurrence data with a hypergeometric distribution, and compare it with established methods (Beals index and favourability correction). Innovation: We compare the different aspects of the method's performance using simulations based on individual agents in which the suitability for each species in each site is known. Further, we assessed the methods in two real datasets with nested sampling designs. We provide the R package 'DarkDiv' (https://cran.r‐project.org/web/packages/DarkDiv/index.html) that implements all the compared methods for estimations of probabilistic dark diversity and species pools. Main conclusions: Beals method is extremely sensitive to species frequency, and predicts species' suitability to local conditions less accurately than the other considered methods. The favourability transformation corrected this relationship, but still predicted extremely low probabilities for species with very little information. The hypergeometric method outperformed the Beals and favourability methods in all considered aspects in the simulations and displayed better characteristics in the real datasets. The hypergeometric method is currently the best option to estimate probabilistic dark diversity and species pool composition based on pairwise species co‐occurrence data. [ABSTRACT FROM AUTHOR]

In this study, an efficient a deep learning architecture‐based peripheral blood cell image recognition and classification is proposed using hybrid disruption‐based salp‐swarm and cat swarm (DSSCS)‐based optimized convolutional neural networks (DSSCSCNNs) method. The DSSCSCNN method is employed to overcome the hyperparameter problem in CNN and it also helps this model to work on small peripheral blood cell data sets. In the DSSCSCNN method, the authors develop a binary coding technique that converts parameter tuning problems into an optimization problem. The original salp swarm algorithm is enhanced using a disruptive operator and salp swarm optimization algorithm to form the novel DSSCS algorithm which increases the diversity of the search space by providing higher classification accuracy. In this study, the CNNs use Vgg‐16 architecture is used for training purposes. The global classification accuracy obtained when trained with the Vgg‐16 model is 97%. This method establishes a fine‐tuning process to develop a classifier trained using 15,976 images acquired from clinical practice. The proposed model gives improved performance in terms of accuracy, specificity, and sensitivity. In the WBC determination, the proposed approach has shown 100% achievement. It also provides the best overall classification accuracy of 99%. [ABSTRACT FROM AUTHOR]

The Lagrangian rate distortion optimisation is widely employed in modern video encoders, such as high‐efficiency video coding (H.265/HEVC). In this work, the authors propose a more accurate context‐based adaptive binary arithmetic coding look‐up table that can enhance compression quality and provide substantially better accuracy of range estimation, by employing one‐more bit with 64 probability states. For the hardware implementation, they propose a higher precision look‐up table instead of the HEVC Test Model (HM) standard table. The authors also define a new finite‐state machine to handle the probability changing in real‐time. The significant BD‐RATE gain of the proposed context modelling is up to 6.0% for all‐intra mode and 13.0% for inter mode. This finite state machine offers no divergence from the H.265/HEVC standards and can be used in the current systems. [ABSTRACT FROM AUTHOR]

The high optical bandwidth requirement in the mobile fronthaul link of the next generation cloud radio access network represents one of the major design constraints. In this study, a digital fronthaul link based on digital radio over fibre system that integrates the duobinary coding scheme with the optical single sideband (OSSB) transmission is proposed. This system reduces the spectral occupancy of the transmitted signals as well as the chromatic dispersion effects induced by fibre in both the electrical and optical domains. The OSSB signal is created by driving two cascaded optical modulators with a combination of a baseband digital signal and the Hilbert transform of that signal. The transmission performance of a digitised 16‐quadrature amplitude modulation 16‐QAM radio frequency signal with a bit rate of 1.25 Gb/s over a standard single mode fibre is investigated. The results show that the fronthaul transmission length can be extended by 75 and 16.6% relative to the case of transmitting the digitised signal using double sideband and single sideband (SSB) transmission formats, respectively. The power budget is improved by 10 dB compared to the SSB case with respect to the measured optical signal‐to‐noise ratio at 70 km fibre distance, while maintaining the EVM below the standardised values of the 3GPP. [ABSTRACT FROM AUTHOR]

Using the land‐bound vertebrates on the marine islands as model organisms, two metrics are presented that permit quantitative and succinct synopses of the 'evolutionary maturity' of the hosted faunal assemblages. In turn, these reflect the geo‐physical settings and geological developments of the substrates. The assemblage lineage‐taxonomy spectrum (ALTS) is based on the constituent lineages' taxonomic distinctiveness and diversity. Individual lineages within assemblages can in most cases be assigned to one of six categories, LT1‒LT6: LT1 is a non‐endemic taxon, whereas LT6 comprises multiple endemic genera from a family that arose elsewhere. If required, the scheme can be expanded: LT9 is an endemic order. The data can then be combined to provide an assemblage spectrum, for example, 00:08:38:30:08:15[13]. Here, the first six values denote the number of lineages assigned to each category expressed as percentages of the overall total, with the sum of the processed lineages listed as the seventh (in brackets and bold). The ALTS metric highlights efficiently the key features of a marine island's biological assemblage. Notably, the contrast between spectra for suites on geologically and geo‐physically varied island types can be striking, for instance the squamate suite on the young, proximate orogenic margin island of Taiwan is coded 78:16:05:00:00:00[37] whereas the one on the distantly located, Late Eocene composite terrane island of New Caledonia is 00:11:00:11:33:44[9]. To overcome the subjectivity that is inherent in assigning supraspecific ranks, an alternative assemblage lineage‐age spectrum (ALAS) is also introduced that makes use of the binary logarithm values of the colonization times of the island lineages (0–2, 2–4, ... , 32–64, >64 Ma). It is represented using a seven‐plus‐two‐number code, for instance Madagascar's squamates are 00:06:00:00:19:62:12[19(16)]; most colonizations took place in the Palaeogene (66–23 Ma); there are 19 lineages, but only 16 are presently age‐dated. In addition to marine‐island biogeography studies, the ALTS–ALAS spectrum approach is potentially useful for encapsulating biotas in other sorts of insular setting (e.g. lakes, mountain tops), and for evaluating palaeogeographical models. Furthermore, it may help emphasize the conservation value of an island's faunal assemblage. [ABSTRACT FROM AUTHOR]

Cross-modal hashing (CMH) has received widespread attention due to high retrieval efficiency, which plays an extremely important role in cross-modal retrieval. Recently, many CMH methods have been proposed to establish the semantic connection of different modalities. However, most of these methods only use a simple quantisation strategy, resulting in large quantisation error, and inferior hash codes. To address this issue, in this study, the authors propose a novel self-taught CMH (STCMH) to minimise the semantic encoding loss. In particular, the common semantic representations across different modalities are first learnt based on collective matrix factorisation. Then, the quantisation procedure based on orthogonal transformation is integrated to encode the semantic representations into discriminative binary codes. Moreover, similarity preservation is imposed to further boost the discriminative power. Finally, hashing functions learning is formulated as a binary classification problem by self-taught scheme. Experimental results on three public datasets demonstrate that STCMH significantly outperforms most state-of-the-art CMH methods. [ABSTRACT FROM AUTHOR]

Cross‐modal hashing (CMH) has received widespread attention due to high retrieval efficiency, which plays an extremely important role in cross‐modal retrieval. Recently, many CMH methods have been proposed to establish the semantic connection of different modalities. However, most of these methods only use a simple quantisation strategy, resulting in large quantisation error, and inferior hash codes. To address this issue, in this study, the authors propose a novel self‐taught CMH (STCMH) to minimise the semantic encoding loss. In particular, the common semantic representations across different modalities are first learnt based on collective matrix factorisation. Then, the quantisation procedure based on orthogonal transformation is integrated to encode the semantic representations into discriminative binary codes. Moreover, similarity preservation is imposed to further boost the discriminative power. Finally, hashing functions learning is formulated as a binary classification problem by self‐taught scheme. Experimental results on three public datasets demonstrate that STCMH significantly outperforms most state‐of‐the‐art CMH methods. [ABSTRACT FROM AUTHOR]

Hashing has been widely deployed to approximate nearest neighbour search for large‐scale multimedia retrieval tasks due to storage and retrieval efficiency. State‐of‐the‐art supervised hashing methods for image retrieval construct deep structures to simultaneously learn image representation and generate good hash codes, and the key step among them is simultaneously learned feature representation and binary hash code. Existing methods use similarity and regularity loss to train deep hashing systems, but these two functions usually work together but not cooperative, which may lead to inadequate performance of the whole system. In this study, a new method for training deep hashing system to learn compact binary codes is presented. The deep supervised hashing network with integrated regularisation (DSHIR) system develop the zero division restriction as a new part of the loss function, which settles the problem of cooperatively guiding the system generate similarity preserving binary codes. DSHIR system also modifies the similarity handling loss to better extract features from image data, which promotes the performance compared to existing end‐to‐end deep hashing systems. Experiments show that DSHIR yields about 10 per cent higher mean average precision on CIFAR‐10 dataset, and also promote on other evaluation indexes compared with state‐of‐the‐art systems. [ABSTRACT FROM AUTHOR]

The electron‐precise binary boron subhalide species [B2X6]2− X=F, Br, I) were synthesized and their structures confirmed by X‐ray crystallography. The existence of the previously claimed [B2Cl6]2−, which had been questioned, was also confirmed by X‐ray crystallography. The dianions are isoelectronic to hexahaloethanes, are subhalide analogues of the well‐known tetrahaloborate anions (BX4−), and are rare examples of molecular electron‐precise binary boron species beyond B2X4, BX3, and [BX4]−. [ABSTRACT FROM AUTHOR]

Embedded zerotree wavelet (EZW) algorithm is the well‐known effective coding technique for low‐bit‐rate image compression. In this study, the authors propose a modification of this algorithm, namely new enhanced EZW (NE‐EZW), allowing to achieve a high compression performance in terms of peak‐signal‐to‐noise ratio and bitrate for lossy image compression. To distribute probabilities in a more efficient way, the proposed approach is based on increasing the number of coefficients not to be encoded by the use of new symbols. Furthermore, the proposed method optimises the binary coding by the use of the compressor cell operator. Experimental results demonstrated the effectiveness of the proposed scheme over the conventional EZW and other improved EZW schemes for both natural and medical image coding applications. They have also shown that the proposed approach outperforms the most well‐known algorithms, namely set partitioning in hierarchical trees (SPIHT) and JPEG2000. [ABSTRACT FROM AUTHOR]