The L1/2 regularization method for variable selection in the Cox model

In this paper, we investigate to use the L_1/2 regularization method for variable selection based on the Cox's proportional hazards model. The L_1/2 regularization can be taken as a representative of L_q (0 < q < 1) regularizations and has been demonstrated many attractive properties. To solve the L_1/2 penalized Cox model, we propose a coordinate descent algorithm with a new univariate half thresholding operator which is applicable to high-dimensional biological data. Simulation results based on standard artificial data show that the L_1/2 regularization method can be more accurate for variable selection than Lasso and SCAD methods. The results from real DNA microarray datasets indicate the L_1/2 regularization method performs competitively.     

State derivative feedback for adaptive cancellation of unmatched disturbances in unknown strict-feedback LTI systems

Solutions exist for the problem of canceling sinusoidal disturbances by the measurement of the state or by the measurement of an output for linear and nonlinear systems. In this paper, an adaptive backstepping controller is designed to cancel sinusoidal disturbances forcing an unknown linear time-invariant system in controllable canonical form which is augmented by a linear input subsystem with unknown system parameters. The state-derivatives of the original subsystem and the state of the input subsystem are the only measurements that are used in the design of the controller. The design is based on four steps, (1) parametrization of the sinusoidal disturbance as the output of a known feedback system with an unknown output vector that depends on unknown disturbance parameters, (2) design of an adaptive disturbance observer for both disturbance and its derivative, (3) design of an adaptive controller for the virtual control input, and (4) design of the final adaptive controller by using the backstepping procedure. It is proven that the equilibrium of the closed-loop adaptive system is stable and the state of the considered original subsystem converges to zero as t→∞$t\to \infty$ with perfect disturbance estimation. The effectiveness of the controller is illustrated with a simulation example of a third order system.     

并联混合有源电力滤波器自适应L2增益鲁棒控制

为了抑制外界未知扰动和参数摄动对并联混合有源电力滤波器(SHAPF) 系统性能的影响, 提出一种新型的自适应L₂ 增益鲁棒控制策略. 首先建立含有扰动和参数摄动的SHAPF 欧拉-拉格朗日(EL) 数学模型, 得到了SHAPF 在dq 坐标系下的误差动态模型; 然后通过构造适当的Lyapunov 函数设计参数自适应控制率, 实现了对系统参数摄动的补偿, 进而利用阻尼注入方法设计系统的L₂增益鲁棒控制器, 以保证闭环系统的 gamma  耗散性. 仿真实验验证了所提出策略的正确性和有效性.

     

CBA-neural network control of a non-linear full vehicle model

In this paper, the dynamic behavior of a non-linear eight degrees of freedom vehicle model having active suspensions and passenger seat controlled by a neural network (NN) controller is examined. A robust NN structure is established by using principle design data from the Matlab diagrams of system functions. In the NN structure, Classic Back-Propagation Algorithm (CBA) is employed. The user inputs a set of x₁ − x₁₆ while the output from the NN consists of f₁ − f₁₆ non-linear functions. Further, the Permanent Magnet Synchronous Motor (PMSM) controller is also determined using the same NN structure. According to various tests of the NN structure it is demonstrated that the model is able to give highly sensitive outputs for vibration condition, even using a more restricted input data set. The non-linearity occurs due to dry friction on the dampers. The vehicle body and the passenger seat using PMSM are fully controlled at the same time. The time responses of the non-linear vehicle model due to road disturbance and the frequency responses are obtained. Finally, uncontrolled and controlled cases are compared. It is seen that seat vibrations of a non-linear full vehicle model are controlled by NN based system exactly.     

Some Applications of Magma in Designs and Codes: Oval Designs,Hermitian Unitals and Generalized Reed–Muller Codes

We describe three applications of Magma to problems in the area of designs and the associated codes:  •  Steiner systems, Hadamard designs and symmetric designs arising from an oval in an even-order plane, leading in the classical case to bent functions and difference-set designs;  •  the Hermitian unital as a 2-(q³ +  1, q +  1, 1) design, and the code overF_p where p divides q +  1;  •  a basis of minimum-weight vectors for the code over F_pof the design of points and hyperplanes of the affine geometry AG_d(F_p), where p is a prime.     

Fuzzy model tuning using simulated annealing

This paper presents the use of simulated annealing metaheuristic for tuning Mamdani type fuzzy models. Structure of the Mamdani fuzzy model is learned from input–output data pairs using Wang and Mendel’s method and fuzzy c-means clustering algorithm. Then, parameters of the fuzzy system are tuned through simulated annealing. In this paper, we perform experiments to examine effects of (a) initial solution generated by Wang and Mendel’s method and fuzzy c-means clustering method, (b) membership function update procedure, (c) probability parameter for the calculation of the initial temperature, (d) temperature update coefficient used for cooling schedule, and (e) randomness level in the disturbance mechanism used in simulated annealing algorithm on the tuning of Mamdani type fuzzy models. Experiments are performed with Mackey–Glass chaotic time series. The results indicate that Wang and Mendel’s method provides better starting configuration for simulated annealing compared to fuzzy c-means clustering method, and for the membership function update parameter, MFChangeRate ∈  (0, 1], and the probability parameter for the calculation of the initial temperature, P₀ ∈  (0, 1), values close to zero produced better results.     

Characterization of Al–Ni intermetallics around 30–60 at% Al for TLPB application

Interest on the Al–Ni equilibrium diagram along the latest years is associated with the attractive properties of its intermetallic phases, such as high thermal stability, high corrosion resistance and high strength to density ratio. The Transient Liquid Phase Bonding (TLPB) is a technological process which can be applied to manufacture new pieces and to perform reparations. Morphology, composition profiles, growth kinetic and hardness as a function of temperature and composition of the Intermetallic Layers (ILs) were analyzed, especially focused on solid–solid interactions during isothermal annealing in reactive diffusion couples Ni/Al (800–1170 °C). The study yields to the following association of the Al–Ni Intermetallic Phases (IPs) to the ILs: L₁ (Al₃Ni), L₂ (Al₃Ni₂), L₃ (Ni-poor AlNi), L₄ (Ni-rich AlNi) and L₅ (AlNi₃). The composition ranges of L₃ and L₄ are 36–46 and 53–58 at% Al, respectively. Martensitic transformation was found in the half thickness of L₄ (L_4M and L_4S) at 1170 °C. Kinetics show diffusion controlled growth for L₂ and L₅ and interface reaction control for L₄ at 800–1170 °C, while L₃ revealed a mixed kinetic behavior: parabolic at 800–1000 °C and linear at 1170 °C. The growth rate constants presented temperature dependence according to the Arrhenius model. Vickers microhardness values decrease with annealing temperature and Ni concentration for ILs, and put in evidence different mechanical properties of L₃, L_4M and L_4S.     

Design of high speed gate driver employing IZO TFTs

This paper presents a new bi-side gate driver integrated by indium-zinc-oxide thin film transistors (IZO TFTs). Our optimized operate method can achieve high speed performance by employing a lower duty ratio (25%) CK2 with its pulse located in the middle of the pulse of CK2L to fully use the bootstrapped high voltage of node Q. In addition, the size of devices is optimized by calculation and simulation, and the function of the proposed gate driver is predicted by the circuit simulation. Furthermore, the proposed gate driver with 20 stages is fabricated by the IZO TFTs process. It is shown that a 2.6 μs width pulse with good noise-suppressed characteristic can be successfully output at the condition of R_load = 6 kΩ and C_load = 150 pF. The power consumption of the proposed gate driver with 20 stages is measured as 1 mW. Hence, the proposed gate driver may be applied to the display of 4K resolution (4096 × 2160) at a frame rate of 120 Hz. Moreover, there is a good stability for the proposed gate driver under 48 h operation.     

Electrochemical determination of ascorbic acid in fruits on a vanadium oxide polypropylene carbonate modified electrode

A novel vanadium oxide polypropylene carbonate modified glassy carbon electrode was developed and used for the measurement of ascorbic acid (AA). The electrode was prepared by casting a mixture of vanadium tri(isopropoxide) oxide (VO(OC₃H₇)₃) and poly(propylene carbonate) (PPC) onto the surface of a glassy carbon electrode. The electrochemical behavior of the VO(OC₃H₇)₃–PPC film modified glassy carbon electrode was investigated by cyclic voltammetry and amperometry. This modified electrode exhibited electrocatalytic response to the oxidation of ascorbic acid. Compared with a bare glassy carbon electrode, the modified electrode exhibits a 220 mV shift of the oxidation potential of ascorbic acid in the cathodic direction and a marked enhancement of the current response. The response current revealed a good linear relationship with the concentration of ascorbic acid in the range of 4 × 10⁻⁸ and 1 × 10⁻⁴ mol L⁻¹ and the detection limit of 1.5 × 10⁻⁸ mol L⁻¹ (S/N = 3) in the pH 8.06 Britton–Robinson solution. Quantitative recovery of the ascorbic acid in synthetic samples has been obtained and the interferences from different species have been studied. The method has been successfully applied to the determination of ascorbic acid in fruits. The concentrations of ascorbic acid measured by this method are in good agreement with the literature value. It is much promising for the modified films to be used as an electrochemical sensor for the detection of ascorbic acid.     

Extended filtering high‐gain output feedback controller for a class of uncertain nonlinear systems subject to external disturbances

In this article, an extended filtering high‐gain output feedback controller is developed for a class of uncertain nonlinear systems subject to external disturbances. The nonlinearities under consideration satisfy a semiglobal Lipschitz condition. The proposed control architecture integrates the extended state observer (ESO), high gain, and low‐pass filter together. None of them is used alone. The ESO can not only estimate the unknown internal state, but also deliver a good property of disturbance rejection simultaneously due to the presence of high gain. Since the high gain deteriorates the robustness of the system, a low‐pass filtering mechanism is added in the control law to filter away aggressive signals and recover the robustness. The filtering control law is designed to compensate the nonlinear uncertainties and deliver a good tracking performance with guaranteed stability. The matched uncertainties are canceled directly by adopting their opposite in the control signal, whereas a dynamic inversion of the system is required to eliminate the effect of the mismatched uncertainties on the output. Since the virtual reference system defines the best performance that can be achieved by the closed‐loop system, the uniform performance bounds are derived for the states and control signals via comparison. Numerical examples are provided to illustrate the effectiveness of the novel design via comparisons with the model reference adaptive control method and L₁ adaptive controller.     

Designing of potential inhibitors against Staphylococcus aureus sortase A: Combined analogue and structure based approach with in vitro validation

Staphylococcus aureus sortase A is an attractive target of Gram-positive bacteria that plays a crucial role in anchoring of surface proteins to peptidoglycan present in bacterial cell wall. Inhibiting sortase A is an elementary and essential effort in preventing the pathogenesis. In this context, in silico virtual screening of in-house database was performed using ligand based pharmacophore model as a filter. The developed pharmacophore model AAHR 11 consists of two acceptors, one hydrophobic and one ring aromatic feature. Top ranked molecule KKR1 was docked into the active site of the target. After profound analysis, it was analyzed and optimized based on the observations from its binding pose orientation. Upgraded version of KKR1 was KKR2 and has improved docking score, binding interactions and best fit in the binding pocket. KKR1 along with KKR2 were further validated using 100 ns molecular dynamic studies. Both KKR1 and KKR2 contain Indole-thiazolidine moiety and were synthesized. The disk diffusion assay has good initial results (ZI of KKR1, KKR2 were 24, 38 mm at 10 μg/mL and ZI of Ampicillin was 22 at 10 μg/mL) and calculated MICs of the molecules (KKR1 5.56 ± 0.28 μg/mL, KKR2 1.32 ± 0.12 μg/mL, Ampicillin 8 ± 1.1 μg/mL) were in good agreement with standard drug Ampicillin. KKR1 has shown IC₅₀ of 1.23 ± 0.14 μM whereas the optimized lead molecule KKR2 show IC₅₀ of 0.008 ± 0.07 μM. Results from in silico were validated by in vitro studies and proved that indole-thiazolidine molecules would be useful for future development as lead molecules against S. aureus sortase A.     

Adaptive local tracking of a temperature profile in tubular reactor with partial measurements

In this work, a local constrained adaptive output feedback is presented for a class of exothermic tubular reactors models described by a nonlinear partial differential equations. The considered output is the measured temperature in a fixed zone of the reactor to regulate the temperature throughout the reactor to a ball with radius λ (arbitrarily small) centered at the fixed temperature profile. For a given measurement zone with length given in terms of the desired profile and λ and for initial temperature in a fixed domain, it is shown that the tracking error through the reactor tends asymptotically to a ball of arbitrary prescribed radius λ > 0, centered at the given temperature profile. Numerical simulations have been performed to illustrate the performance of the proposed approach.     

Active noise control in a forced-air cooling system

This paper discusses the design methodology for the active noise control of sound disturbances in a forced-air cooling system. The active sound cancellation algorithm uses the framework of output-error based optimization of a linearly parametrized filter for feedforward sound compensation to select microphone location and demonstrate the effectiveness of active noise cancellation in a small portable data projector. Successful implementation of the feedforward based active noise controller on a NEC LT170 data projector shows a 20–40 dB reduction per frequency point in the spectrum of external noise of the forced-air cooling system can be obtained over a broad frequency range from 1 to 5 kHz. A total noise reduction (unweighted) of 9.3 dB is achieved.     

Computing Local Artin Maps,and Solvability of Norm Equations

Let L = K(α) be an Abelian extension of degree n of a number field K, given by the minimal polynomial of α over K. We describe an algorithm for computing the local Artin map associated with the extension L / K at a finite or infinite prime v of K. We apply this algorithm to decide if a nonzero a ∈ K is a norm from L, assuming that L / K is cyclic.     

Modal analysis and modified cascade neural networks in identification of geometrical parameters of circular arches

A hybrid computational system, composed of the finite element method (FEM) and cascade neural network system (CNNs), is applied to the identification of three geometrical parameters of elastic arches, i.e. span l, height f and cross-sectional thickness h. FEM is used in the direct (forward) analysis, which corresponds to the mapping α = {l, f, h} → {ω_j}, where: α – vector of control parameters, ω_j – arch eigenfrequencies. The reverse analysis is related to the identification procedure in which the reverse mapping is performed {ω_j} → {α_i}. For the identification purposes a recurrent, three level CNNs of structure (D^k-H^k-1)_s was formulated, where: k – recurrence step, s = I, II, III-levels of cascade system. The Semi-Bayesian approach is introduced for the design of CNNs applying the MML Maximum Marginal Likelihood) criterion. The computation of hyperparameters is performed by means of the Bayesian procedure evidence. The numerical analysis proves a great numerical efficiency of the proposed hybrid approach for both the perfect (noiseless) values of eigenfrequencies and noisy ones simulated by an added artificial noise.     

A geometric approach to multivariable control system design of a distillation column

A multivariable control problem of a distillation column is considered, where the object is to maintain two output variables, the compositions of the distillate and the bottom product at some desired values by manipulating the reflux flow rate and the boil-up rate.Based on a linearized model, a geometric approach is applied to the design problem of disturbance rejection control. In other words, a feedback control strategy is desired which enables the complete rejection of the effect of disturbances on both output variables.In obtaining the feedback control, the problem of how many and what state variables are to be measured and fed back has been made clear. In this control strategy, only five state variables are fed back. Thus, only five columns of the feedback gain matrix have non-zero values. Furthermore, two out of these five columns are uniquely determined, and the other three columns can be assigned arbitrary values and used for pole assignment of the controlled system.For the disturbances in composition and flow rate of the feed stream, Δx_F and ΔL_F, the effect of the disturbance Δx_F is completely rejected by the feedback controller, but the effect of the disturbance ΔL_F can only be eliminated from the output Δx_D.A digital simulation of a distillation column composed of nine plates, a condenser and a reboiler was carried out to confirm these results and to show that the linearized model used in this paper is valid for fairly large step changes.     

Curves of Genus 2 with (N,N) Decomposable Jacobians

Let C be a curve of genus 2 and ψ₁: C  −  → E ₁  a map of degree n, from C to an elliptic curveE₁ , both curves defined over C. This map induces a degree n map φ₁:P¹  −  → P ¹  which we call a Frey–Kani covering. We determine all possible ramifications for φ₁. If ψ₁:C  −  → E ₁  is maximal then there exists a maximal map ψ₂: C  −  → E ₂  , of degree n, to some elliptic curveE₂ such that there is an isogeny of degree n²from the JacobianJ_C to E₁ × E₂. We say thatJ_C is (n, n)-decomposable. If the degree n is odd the pair (ψ₂, E₂) is canonically determined. For n =  3, 5, and 7, we give arithmetic examples of curves whose Jacobians are (n, n)-decomposable.     

A robust output-feedback adaptive dynamic surface control for linear systems with input disturbance

In this paper, a robust output-feedback adaptive control is proposed for linear time-invariant (LTI) singleinput single-output (SISO) plants with unmeasurable input disturbance. Using dynamic surface control (DSC) technique, it is shown that the explosion of complexity problem in backstepping control can be eliminated. Furthermore, the proposed adaptive DSC scheme has the following merits: 1) by introducing an initialization technique, the L∞ performance of system tracking error can be guaranteed even if the plant high-frequency gain is unknown and the input disturbance exists, and 2) the adaptive law is necessary only at the first design step, which significantly reduces the design procedure. It is proved that with the proposed scheme, all the closed-loop signals are semiglobally uniformly ultimately bounded. Simulation results are presented to demonstrate the effectiveness of the proposed scheme.     

Data driven nonparametric identification and model based control of glucose-insulin process in type 1 diabetics

Closed loop control of glucose homeostasis via subcutaneous insulin infusion and continuous glucose monitoring system can give better living to a type 1 diabetic patient. This paper deals with the real time implementation of internal model control (IMC) of subcutaneous insulin infusion. The model based control is applied on the nonparametric model of the patient identified in real time from input–output data. Meal simulation model of the glucose-insulin system of type 1 diabetic patient based on the work of Dalla Man et. al. is considered. This model is constructed in hardware platform that acts as the virtual patient. The data-driven nonparametric model of the virtual patient is identified in real time by computing Volterra kernels. The kernels are solved up to second order using recursive least squares (RLS) algorithm with short memory length of M = 2. The validation results of the identified model output and the actual output have shown good fit in both simulation and real time environments. The frequency domain kernels are used in internal model control to generate insulin dosage. The control algorithm is developed in simulation and implemented in real time with hardware in loop on dSPACE platform. The closed loop system yields good meal disturbance rejection, less undershoots, settling time and more profoundly smaller requirement of insulin infusion as compared to the earlier reported data.