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A common method for reading information stored in DNA molecules is shotgun sequencing. This method outputs a histogram of the frequencies of all the molecules’ substrings of a given length $\ell $. To protect against noisy readings, the rank-modulation scheme encodes the information in the relative ranking of the substring frequencies, instead of their absolute values. However, the best rank-modulation codes for shotgun sequencing have low rates which are asymptotically vanishing. In this paper we propose new constructions of rank-modulation codes for shotgun sequencing. The first code construction is systematic, allowing the user to arbitrarily set the frequencies of a large subset of the substrings, which the encoder then completes to a permutation that may be realized by a DNA molecule. The construction is then improved by allowing the user to set the frequencies of additional substrings, at the cost of imposing constraints on the frequencies. The resulting codes have higher, non-vanishing rates, compared with previously known codes. As an example, for histograms of substrings of length $\ell =2$ , and an alphabet of size 4 (as in DNA molecules), we are able to construct a code with rate $\approx 0.909$ , whereas previously, the best construction resulted in a code with rate $\approx 0.654$. Additionally, the encoded information in our construction may be written to shorter DNA molecules than possible before. We also prove that the systematic codes constructed in this paper are the largest possible among all systematic codes. [ABSTRACT FROM AUTHOR]

A nonlinear optimization algorithm has been described for the inversion of gravity data profile by a faulted 2-D horizontal thin block. The algorithm simultaneously optimizes for the depth to the center ($z$) of the faulted block, the amount and direction of dip ($\theta $) of the fault plane, and the amplitude coefficient ($A$), which is dependent on the amount of throw $t$ and the density contrast $\Delta \rho $ of the block. The objective functional of this algorithm coupled with both the space of logarithmed absolute values of the observed and predicted gravity data and the space of logarithmed [ $\log (z)$ , $\log (|A|)$ , and $\log (\theta $)] model parameters is the basis of the new inversion scheme introduced here. It has been found essential that the objective functional of this scheme be formulated in this particular combination so that the iterative solver/minimizer (the Gauss–Newton (GN) method) can converge. The developed scheme has been successfully verified on numerical models without noise and achieved superior convergence. It is found stable and can determine the inverse parameters of the faulted block with acceptable accuracy when applied to data contaminated with insignificant noise levels and/or geologic interference. In order to investigate the usefulness of the developed scheme, a published gravity profile has been inverted and analyzed, suggesting new results that are of some geologic significance. The computational efficiency, thorough analysis of the investigated numerical examples, and comparisons of the real data inverted in this paper have demonstrated that the scheme developed here is advantageous to the existing gravity data inversion schemes that solve for the characteristic inverse parameters of a faulted thin block. [ABSTRACT FROM AUTHOR]

Lidar is considered to play an essential role on the road towards fully autonomous driving. In this context, coherent lidar systems hold the potential for lean, efficient and inexpensive sensors, but their performance depends significantly on suitable modulation and signal processing methods that can handle high Doppler shifts and enable high measurement rates at low computational complexities. This paper presents four novel phase-modulation-based approaches that utilize pseudo-random binary sequences to estimate target distances up to 180 m and the absolute value of target velocities up to 80 m/s. The corresponding system setup is lean, as it is based on only one phase modulator and one non-quadrature demodulator. The proposed methods are assessed analytically and by simulations and are compared in terms of computational complexity, detection performance, measurement rate and accuracy. The results demonstrate that while each approach has individual advantages and limitations, the proposed methods offer essential advancements in terms of measurement rate, multiplexing potential and multi-target capability, compared to already known methods. The feasibility of all presented approaches is validated by measurements. [ABSTRACT FROM AUTHOR]

A state estimation framework that eliminates the need for a topology processor is presented in this paper. By retaining switching devices (SDs) in the network model, this approach allows estimation of their statuses. Consequently, topology error detection becomes part of the SE process. Since this approach requires expansion of bus-branch models with SDs, the conventional state estimation formulation is accordingly modified to avoid numerical issues due to extremely small (large) impedance values of open (closed) switching devices. The scalability of the proposed framework is achieved by parallel processing, which is implemented after partitioning the system into zones. The measurement overhead is kept minimal by utilizing two optimal measurement placement algorithms and taking advantage of KCL-based virtual measurements. Case studies presented show that the proposed method can identify concurrent bad data and topology errors. The improvements in computation times due to parallel processing are demonstrated through simulations on the IEEE 300-bus system with and without zone-partitioning. [ABSTRACT FROM AUTHOR]

Measurement error is a crucial factor that determines the accuracy of state estimation (SE). Conventional estimators have fixed models, and can yield optimal performance only when the measurement error statistics exactly meet the assumptions. In reality, however, the error distribution is usually unknown and time-varying, resulting in suboptimal state estimates in most cases. This paper develops the concept of adaptive SE for power systems measured by phasor measurement units (PMUs). First, the Gaussian-Laplacian Mixture (GLM) model is developed to fit the body and tail of unknown measurement error distributions. Then, an adaptive estimation framework is proposed based on the Expectation-Maximization (EM) algorithm. It is capable of tracking the actual error statistics online, and adjusting the parameters of SE to maintain near-optimality of state estimates under complex measurement error conditions. Simulation results demonstrate that the proposed adaptive estimator yields more accurate state estimates than the well-known Weighted Least Squares (WLS) and Weighted Least Absolute Value (WLAV) estimators by adapting itself to the variations of measurement error statistics. [ABSTRACT FROM AUTHOR]

Recently, maximum correntropy criterion (MCC) has been widely and successfully used in robust signal processing and machine learning, in which the correntropy is maximized instead of minimizing the popular mean square error (MSE) to improve the robustness with respect to outliers or impulsive noises. A lot of efforts have been devoted to derive different adaptive algorithms under MCC, but to date, little insight has been gained as to how the MCC solution will be influenced by outliers. In this paper, we investigate this problem and our focus is mainly on the parameter estimation of a simple linear errors-in-variables (EIVs) model with scalar variables. Under some conditions, we derive an upper bound on the absolute value of the estimation error and show that the MCC solution can get very close to the true value of the unknown parameter even with arbitrarily large outliers in both the input and output variables. Illustrative examples are provided to verify and clarify the theory. [ABSTRACT FROM AUTHOR]

In this paper, the problem of the finite-time synchronization is addressed for a kind of fractional-order memristive neural networks (FMNNs). First, a new power law inequality with fractional-order and two finite-time fractional differential inequalities are established by means of L’Hospital rule, Laplace transform, and reduction to absurdity, which greatly extend some existing results. In addition, unlike the traditional maximum absolute value-based method to propose memristive synaptic weights, by introducing some transformations, FMNNs are translated to a type of fractional-order systems with uncertain parameters. Furthermore, the finite-time synchronization of FMNNs is investigated by designing a discontinuous control scheme and several criteria are derived based on the developed fractional inequalities and M-matrix theory. Note that in addition to the traditional Lyapunov function with absolute value form, a more general Lyapunov function is constructed to deal with the finite-time synchronization, which makes the derived criteria more flexible and less conservative. Lastly, the derived theoretical results are verified via numerical simulations. [ABSTRACT FROM AUTHOR]

Enhanced unipolar orthogonal frequency division multiplexing (eU-OFDM) and layered asymmetrically clipped optical OFDM (LACO-OFDM) are spectrally efficient modulation techniques for intensity modulated systems which layer multiple non-negative signals. In this paper, we propose absolute value layered asymmetrically clipped optical OFDM (ALACO-OFDM), which further improves the spectral efficiency while using a smaller number of layers and no explicit direct current (DC) bias. In ALACO-OFDM, asymmetrically clipped optical OFDM (ACO-OFDM) signals are sent at the first $L$ layers and absolute value optical OFDM (AVO-OFDM) is used for the remaining subcarriers and transmitted simultaneously. Analysis indicates that ALACO- achieves higher spectral efficiency than eU- or LACO-OFDM while using a smaller number of layers. Bounds on achievable information rates of ALACO-OFDM and related layered ACO-OFDM techniques are also developed. Two optical power allocation schemes over the layers of ALACO-OFDM are developed with the objective of optimizing uncoded transmission performance and the achievable information rate respectively. Additionally, a theoretical bound on the uncoded BER of ALACO-OFDM is derived. Monte Carlo simulation results indicate ALACO-OFDM with the optimum power allocation achieves significant uncoded BER performance gains compared to its counterparts at the same spectral efficiency while having a smaller peak-to-average power ratio. [ABSTRACT FROM AUTHOR]

Distance protection encounters some problems such as time coordination, protection of short lines, capacitive charging current and high impedance faults. Its shortcomings are extended in the case of protection of hybrid transmission lines, including overhead line and underground cable. To cope with the mentioned problems, in this paper, a novel approach is proposed for pilot protection of hybrid transmission lines. The proposed approach utilizes three phase voltage and current signals of both ends and transfer matrix of the hybrid line. Indeed, voltage and current angles of specific points on the line are calculated from both ends and the absolute values of the differences between the results obtained from the sending and receiving ends are computed for each point to detect the fault and identify its exact location and phase. The achieved results confirm the security, dependability, and efficiency of the algorithm in critical conditions of power system, i.e., high impedance fault occurrence, power swing, different strengths of equivalent sources at both ends, loss of time synchronization of remote end data, and different fault locations with various inception angles. Although the proposed method is very simple, its performance is surprisingly satisfactory and it is suitable for practical implementation in real-life applications. [ABSTRACT FROM AUTHOR]

Systems using microcontrollers make the interface of a transducer with the digital world much easier. They build smart, lucid, compact, cheap, and less power consuming electronic interfaces. Limited acquisition time is critical for many industrial applications. Single-element resistive sensors are used on a large scale. An attempt has been made to reduce the acquisition time of the measuring system compared to the existing work which converts the change in sensor resistance to the change in time with three charge–discharge cycles. Efforts have been made in this paper to reduce this to two charge–discharge cycles. The proposed work also compensates the errors due to lead wire resistance, the change in lead wire resistance, port pin resistances, and varying ambient temperature with reduced acquisition time. The mean of absolute errors, standard deviation, integral squared error (ISE), nonlinearity, and hysteresis of the proposed method have been computed. Simulation and experimentation study of the proposed system provided encouraging results. The mean of absolute errors and standard deviation of the proposed method in the simulation were 0.07 and 0.08 $\Omega $ , respectively. Furthermore, during experimentation, the values of the mean of absolute errors and standard deviation were 0.11 and 0.11 $\Omega $ , respectively. ISE was found to be 0.09 and 0.19 in simulation and experimentation, respectively. The proposed two-cycle method has an acquisition time of only 60% of the three-cycle method with no reduction in performance. [ABSTRACT FROM AUTHOR]

As the second part of two series paper, the protection scheme is proposed. First of all theoretical analysis and threshold calculation methods are introduced. Aiming to the problem that relay needs to send alert signal instead of trip signal in non-effectively grounded system when single pole to ground fault occurs, a fault type identification method is introduced based on the ratio of absolute values of two poles voltage derivatives. Then 1 mode voltage based protection scheme is developed and the feasibility of design of criterion based on pole voltages, impact of sampling frequency, fault types, resistance and branch on the proposed criterion are discussed comprehensively. MMC based two-terminal and radial and VSC based four-terminal dc distribution systems are simulated in PSCAD. Relay behaviors are tested in three systems under different locations, resistances and types of faults. Results show that the proposed methods can be applied to both MMC and VSC based dc distribution systems and are immune to the fault type, fault location and fault resistance. [ABSTRACT FROM AUTHOR]

Fault diagnosis of induction motors through the analysis of the stator current is increasingly being used in maintenance systems, because it is non-invasive and has low requirements of hardware and software. Nevertheless, its industrial application faces some practical limitations. In particular, the detection of fault harmonics that are very close to the fundamental component is challenging, as in large induction motors working at very low slip, because the leakage of the fundamental can hide the fault components until the damage is severe. Several methods have been proposed to alleviate this problem, although all of them increase noticeably the complexity of the diagnostic system. In this paper, a novel method is proposed, based on the analysis of the rectified motor current. It is shown that its spectrum contains the same fault harmonics as the spectrum of the original current signal, but with a much lower frequency, and free from the fundamental component leakage. Besides, the proposed method is very easy to implement, either by software, using the absolute value of the current samples, or by hardware, using a simple rectifier. The proposed approach is presented theoretically and validated experimentally with the detection of a broken bars fault of a large induction motor. [ABSTRACT FROM AUTHOR]

Active magnetic bearings (AMBs) are being continuously explored for industrial applications mainly because of their friction-free operation. However, if a rotor-shaft-AMB system is used in applications such as turbo engine of an aircraft or in the propeller shaft of a ship, it would be subject to parametric excitation because of the moving base of the system. Parametric excitation is known to cause instability in systems. This paper addresses the issue of such flexible rotor-AMB system and performs the parametric stability analysis. A novel control law based on the constitutive relationship of a viscoelastic material called the four-element control law is developed. Because of the presence of periodic base motion terms in the system state matrix, the system can be classified as a linear periodic system. Thus, the stability analysis is carried out using Floquet–Liapunov theory on stability of periodic system, for which an approximate state transition matrix is first found and stability of the system is then decided based on the absolute value of eigenvalue. Three different base motions (roll, pitch, and yaw) were considered for evaluating the performance of the proposed control law. Simulation results reveal that the proposed control law has better stability characteristics than the proportional-integral-derivative (PID) control law. [ABSTRACT FROM AUTHOR]

An electric power distribution system is operated in several distinct radial topologies by opening and closing of system's sectionalizing and tie switches. The estimation of the system's current operational topology is a precursor to implementing any optimal control actions (during normal operation) or restorative actions (during outage condition). This paper presents a mathematical programming approach to estimate the operational topology of a three-phase unbalanced power distribution system under both outage and normal operating conditions. Specifically, a minimum weighted least absolute value estimator is proposed that uses the line flow measurements, historical/forecasted load data, and ping measurements and solves a mixed-integer linear program (MILP) to estimate the operational topology and any outaged sections simultaneously. We thoroughly validate the accuracy of the proposed approach using IEEE 123-bus and a 1069-bus three-phase multi-feeder test system with the help of numerous simulations. It is observed that the approach performs well even at high percentages of measurement errors. [ABSTRACT FROM AUTHOR]

This paper proposes a new state estimation approach for large-scale power systems called spanning tree maximum exponential absolute value (ST-MEAV). The novel state estimator is developed based on the combination of the maximum exponential absolute value (MEAV) and a fast-linear solver. An overall algorithm is presented to show the process. A modified ST-MEAV called ST0-MEAV is also proposed to improve computational efficiency. Furthermore, the state estimation of the two FACTS devices called interphase power controllers (IPC) and unified interphase power controllers (UIPC) is addressed. The new formulations minimize the number of additional variables needed for the state estimation to reduce the computational load and to simplify implementation compared to previous methods presented in the literature for similar FACTS devices like UPFC or IPFC. The state estimation approach incorporates detailed steady-state models of the devices including IPC and UIPC constraints. The ST-MEAV algorithm is modified based on the new formulations for IPC and UIPC. Two modified IEEE test systems are used to verify the performance of ST-MEAV in the presence of IPC and UIPC. Application tests of ST-MEAV on two real power grids are also presented to evaluate the state estimator performance in large-scale power systems. The simulation results of the proposed method compare favorably with those for weighted least square-largest normal residual (WLS-LNR) and MEAV with reduced correction equation (MEAV-RCE). [ABSTRACT FROM AUTHOR]

Besides the nature and condition of the surfaces in contact, several factors influence the triboelectric charging of polymer slabs in frictional sliding contact: pressure load and relative velocity between the two bodies, number of friction cycles, ambient temperature, and humidity. This paper is aimed at pointing out the peculiarities of the statistic control of such a process. Thirty experiments were performed for the optimal combination of factor values (i.e., normal force: 10 N; sliding speed: 55 mm/s; number of sliding cycles: 10) that maximize the absolute value of the average potential at the surface of the tribocharged materials: 1600 V. The capability index calculated from the experimental data was satisfactory and two Shewart charts were established for the statistical control of the process. Two out-of-control situations were simulated, in order to test the efficiency of the charts. [ABSTRACT FROM AUTHOR]

With the development of easily wearable devices for humans, monitoring, and collecting lifelog data related to personal health status is easier than ever before. The advances in such wearable devices allow healthcare service providers to easily collect a vast amount of health lifelogs from diverse users for the purpose of data analysis. However, collecting health information of individual users indiscriminately may lead to serious privacy issues, because health lifelog data usually contain sensitive information. Thus, in this paper, we develop methods capable of collecting sensitive health lifelogs from a smartwatch, which is the most popular wearable device, while protecting the data privacy of smartwatch users. Experimental results show that the proposed approach can achieve an effective tradeoff between the degree of privacy protection and the accuracy in aggregate statistics. A correlation coefficient with an absolute value ranging from 0.808 to 0.945 between the degree of privacy protection and the accuracy in aggregate statistics can be accomplished using the proposed methods. [ABSTRACT FROM AUTHOR]

Commercial time-of-flight (TOF) ultrasonic flowmeters (UFM) are rapidly expanding in the general industry. Among the different techniques that can be applied to determine the TOF of ultrasonic waves, the cross-correlation method presents numerous advantages, such as robustness for weak signals and noise suppression. However, the selection of an appropriate reference wave is presumably a key element in the precise measurement of TOF. In this paper, an algorithm to compute an accurate TOF is proposed. The form of the electric signal received by the transducer is obtained from an acoustically forced underdamped oscillator model, and the analytical solution of the model is proposed as a reference wave. In order to validate the effectiveness of this procedure, a UFM system is designed and tested in a flowmeter calibration test rig. It is demonstrated that the use of the presented scheme overcomes the average method limitations, and turns out to be a convenient solution in a wide range of conditions. Robust measurements of near-zero flow values are acquired, which allow the achievement of a high dynamic range. The error curve of the proposed system have been obtained, revealing that the absolute value of the relative errors is lower than 2% within all the spectrum of flow rates considered (from 0.2 to 150 $\text{m}^{3}$ /h). Results demonstrate that the algorithm provides high-precision measurements within a wide dynamic range. The algorithm is portable and versatile: it can be adapted to different types of transducers without the need of additional measurements, allowing adjusting parameters on-the-fly for an optimal performance of the ultrasonic flowmeter (UFM) system. [ABSTRACT FROM AUTHOR]

In order to improve the reliability and availability of the converters of wind turbines, condition monitoring and fault diagnosis are considered crucial means to achieve these goals. In this text, according to the current variation characteristics of the converter, this paper presents a novel approach for real-time diagnostics of open-switch faults in back-to-back converters of a doubly fed wind turbine. The average value of the normalized converter phase currents and the absolute normalized currents are used as principal quantities to formulate the diagnostic variables. The proposed fault-diagnostic variables prove to be carrying information about multiple open-switch faults. In addition to, by the combination of these variables with the average absolute values of the normalized converter phase currents, an adaptive fault-diagnostic threshold is proposed, which ensures the robustness of the diagnosis of single and double open-switch faults. Finally, through the diagnostic variables and the adaptive threshold, the dynamic fault-diagnostic method for open-switch faults in the back-to-back converter of a doubly fed wind turbine is formed. The simulation and experimental results also indicate that the fault-diagnostic method can not only diagnose the multiple open-circuit faults of a back-to-back converter, but also have a better robustness. [ABSTRACT FROM PUBLISHER]