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Controlled islanding often acts as the last resort against a severe blackout. Generator coherency is the primary constraint to determine an effective controlled islanding strategy. This paper proposes a scheme to identify the dynamic coherency of generators for controlled islanding. The generator coherency is identified based on the Phase-plane Trajectory Vectors (PTVs) on the Phase Plane for Generators (PPG). Then a Phase Plane for Buses (PPB) is proposed to assign the non-generator buses to coherent generator groups following the minimum distance principle. The separated islands are formed by disconnecting certain transmission lines according to the identified coherent generators and areas. The case studies in IEEE 39-bus 10-machine power system show that the proposed scheme can not only adapt to different disturbances and changes of system conditions and network topology but also succeed in identifying the generator coherency at different times and developing proper islanding strategy according to current system states.

Internet of Things (IoT) defines as internetworks of physical smart devices embedded with electronic software, sensors, actuators, and network connectivity. Due to an increase in the numbe...

Standard vector autoregressions (VARs) often find puzzling effects of monetary policy shocks. Is this due to an invalid (recursive) identification scheme, or because the underlying small‐scale VAR neglects important information? I employ factor methods and external instruments to answer this question and provide evidence that the root cause is missing information. In particular, while a recursively identified dynamic factor model yields conventional monetary policy effects across the board, a small‐scale VAR identified via external instruments does not. Importantly, the discrepancy between both models largely disappears once the information set of the VAR is augmented via factors. This finding is comforting news for the recent monetary literature. Two leading empirical advances with different underlying assumptions—namely external instruments (applied to a factor‐augmented VAR) and dynamic factor models (identified recursively)—find very similar effects of monetary policy shocks, cross‐verifying each other.

In this paper, brain storm optimization BSO-based efficient identification approach has been applied to different types of stable and practically useful Nonlinear Auto Regressive Moving Average with exogenous noise NARMAX Hammerstein models with various performance criteria-based assessments. Different performance measures of the estimation process like accuracy, precision and consistency have been established to ensure the general applicability and practical usefulness of the proposed approach. The accuracy and the precision of the parameter estimation are established with the corresponding bias and variance information, while the consistency has been justified with the help of hypothesis test results. BSO-based optimum values of the output mean square errors and the parameters and their corresponding convergences ensure the stability and robustness of the proposed identification scheme. The comparative studies of the performance of the BSO algorithm with the other basic evolutionary algorithms have been reported with optimum values of the mean square errors, estimated values of the parameters, corresponding computational times and hypothesis test outcomes. Copyright © 2016 John Wiley & Sons, Ltd.

Summary This paper presents a set of single layer low complexity nonlinear adaptive models for efficient identification of dynamic systems in the presence of outliers in the training signal. The weights of the new models have been updated using a new robust learning algorithm. The proposed robust algorithm is based on adaptive minimization of Wilcoxon norm of errors. The computational complexity associated with the new models has further been reduced by processing the input in block form and using a newly derived robust block learning algorithm. Through exhaustive simulation study of many benchmark identification examples, it has been shown that in all cases, the new models provide enhanced and robust identification performance compared with that provided by the corresponding conventional squared error-based approaches. Copyright © 2014 John Wiley & Sons, Ltd.

In 2013, Dehkordi and Alimoradi proposed a certificateless identification scheme using supersingular elliptic curves. This proposal came independent of the parallel work of Chin et al. in proposing the first known security models for certificateless identification with provable security. In this paper, we show that there are some design flaws in the Dehkordi-Alimoradi scheme, which lead one to conclude that their scheme is insecure. Copyright © 2014 John Wiley & Sons, Ltd.

SUMMARY In this paper, the problem of continuous and discrete state estimation for a class of linear switched systems with additive faults is studied. The class of systems under study can contain non-minimum phase zeroes in some of their ‘operating modes’. The conditions for exact reconstruction of the discrete state are given using structural properties of the switched system. The state space is decomposed into the strongly observable part, the non-strongly observable part, and the unobservable part, to analyze the effect of the unknown inputs. State observers based on high-order sliding mode to exactly estimate the strongly observable part and Luenberger-like observers to estimate the remaining parts are proposed. For the case when the exact estimation of the state cannot be achieved, the ultimate bounds on the estimation errors are provided. The proposed strategy includes a high-order sliding-mode-based fault detection and a fault identification scheme via the solution of a Volterra integral equation. The feasibility of the proposed method is illustrated by simulations. Copyright © 2013 John Wiley & Sons, Ltd.

Summary An indoor localization technology is increasingly critical as location-aware applications evolve. Researchers have proposed several indoor localization technologies. Because most of the proposed indoor localization technologies simply involve using the received signal strength indicator value of radio-frequency identification (RFID) for indoor localization, radio-frequency interference, and environmental factors often limit the accuracy of localization results. Therefore, this study proposes an accurate RFID localization based on the neural network (ARL-N2), a passive RFID indoor localization scheme for identifying tag positions in a room, combining a location identification based on dynamic active RFID calibration algorithm with a backpropagation neural network (BPN). The proposed scheme composed of two phases: in the training phase, an appropriate BPN architecture is constructed using the training data derived from the coordinates of reference tags and the coordinates obtained using the localization algorithm. By contrast, the online phase involves calculating the tracking tag coordinates and using these values as BPN inputs, thereby enhancing the estimated location. A performance evaluation of the ARL-N2 schemes confirms its high localization accuracy. The proposed method can be used to locate critical objects in difficult-to-find areas by creating minimal errors and applying and economical technique. Copyright © 2013 John Wiley & Sons, Ltd.

SUMMARY Non-line-of-sight (NLOS) identification is a critical issue in wireless location system. The traditional method only considers the probability of false alarm to obtain the single threshold to identify the wireless propagation environment as line of sight (LOS) or NLOS. However, the probability of missed detection is rarely discussed. In this paper, firstly, the optimal single threshold is derived through minimizing the total error probability, which is the sum of the probability of false alarm and the probability of missed detection. Further, if the prior probabilities for the LOS and NLOS environment are available, a novel double threshold method based on the optimal single threshold is proposed to perform NLOS identification. By comparing the total error probability, we show through simulation results that the performance of the optimal single threshold is better than that of the traditional single threshold. Moreover, the novel double threshold NLOS identification scheme is feasible and better than the optimal single threshold scheme. It is also shown that the analytical results are consistent with the simulated ones.Copyright © 2012 John Wiley & Sons, Ltd.

This article studies the dynamic response of labor input to neutral technology shocks. It uses benchmark dynamic, stochastic, general equilibrium models enriched with labor market search and matching frictions and investment-specific technological progress that enables a new, agnostic, identification scheme based on sign restrictions on a structural vector autoregression (SVAR). The estimation supports an increase of labor input in response to neutral technology shocks. This finding is robust across different perturbations of the SVAR model.

Fuzzy identity-based identification (FIBI) scheme is a recently proposed cryptographic identification protocol. The scheme utilizes user biometric trait as public keys. The authentication is deemed success in the presence of the genuine query biometric together with the valid private key. Because of the fuzziness nature of biometrics, FIBI does not correct the errors on the query biometric with respect to the public key; instead, it tolerates the errors using Lagrange polynomial interpolation. Therefore, FIBI requires the biometric trait to be represented in a discrete (binary or integer) array that is fixed in length. In this paper, we report the first realization of FIBI scheme by means of fingerprint biometrics using minutia representation where our technique integrates the security features of both biometric and cryptography effectively. The simulation shows that the entire protocol can be completed within 1 s where false acceptance rate (FAR) = 0% and false reject rate (FRR) = 0.25% in FVC2002 DB1, and FAR = 0% and FRR = 0.125% in FVC2002 DB2. Our integration technique may also be applied on other fuzzy identity-based cryptosystems. Copyright © 2012 John Wiley & Sons, Ltd.

The human species is again becoming nomadic. Each year, about two billion persons move across large geographic distances (not to mention people in “virtual mobility” through information and communication technology). Many of these people have weak or unreliable identification documents—and many poorer people in developing countries do not even have these documents. In 2000, the United Nations Children's Fund (UNICEF) calculated that 50 million babies (41% of births worldwide) were not registered at birth. In this scenario, a personal identification scheme based on birth registration and state-issued passports is less and less tenable. Biometrics appears to offer a viable technological solution. However, the technology itself is subject to popular critique, warning of dystopian futures of overwhelming surveillance and loss of privacy. The best answer to those who fear an Orwellian future is to engage with the technology and seek to ensure that biometric identification systems are developed in positive ways. We suggest that identification schemes become problematic when the reciprocity of identification goes unnoticed, forgotten, or (what is worse) is intentionally bypassed. The dynamics of identification should be reciprocal, dialogical, and involving mutual recognition. In the traditional political domain, this is the recognition by the state of a citizen and by the citizen of the state. In the digital age, identification systems must increasingly transcend geopolitical borders. A globally recognized identification scheme is therefore a necessity. However, it is merely the nature of the borders that has changed here—not the nature of identification. Our call will be: no identification without representation.

Biometrics make human identification possible with a sample of a biometric trait and an associated database. Classical identification techniques lead to privacy concerns. This paper introduces a new method to identify someone using his biometrics in an encrypted way. Our construction combines Bloom Filters with Storage and Locality-Sensitive Hashing. We apply this error-tolerant scheme, in a Hamming space, to achieve biometric identification in an efficient way. This is the first non-trivial identification scheme dealing with fuzziness and encrypted data. Copyright © 2010 John Wiley & Sons, Ltd.

The feasibility of using the topology design method for structural damage identification was investigated. For efficient damage identification in a structure, we used not only resonances but also anti-resonances as the damage identifying modal parameters and set up a formulation suitable for damage identification. The use of anti-resonances as well as resonances made it possible to identify damage location more effectively because changes in mode shapes due to any damage can be indirectly represented by the changes in anti-resonances. Point-frequency response functions were used to facilitate the extraction of the anti-resonances of a damaged structure. A finite element model of an undamaged structure was assumed to be given. Since considerably many resonances and antiresonances were used for damage identification, they were stated as constraint equations in the present formulation. An explicit penalty function designed to suppress intermediate design variables was used as the objective function because it may be otherwise difficult to obtain clear black-andwhite images at the end of the identification process. When damage extent is not severe, it may be difficult to identify the damage location only with a single-stage application of the present topology optimization-based method. To overcome this difficulty, a multi-stage damage location identification scheme, which reduces the number of candidate damaged elements over several topology optimization stages, was proposed. With the multi-stage technique, relatively small-sized damages were identified accurately as compared with a single-stage application. Through numerical examples, the identification performance improvement by the additional consideration of anti-resonances was demonstrated and the effectiveness of the multi-stage identification technique was also confirmed.

Summary Coagulase-negative staphylococci (CNS), mainly isolated from bovine mastitis (n = 89, representing 11 different species), were used to evaluate two commercial identification systems: ID 32 Staph and Staph-Zym. The level of agreement between the ID 32 Staph and Staph-Zym systems and conventional methods was 77 and 94 %, respectively. An alternative method, based on solid biochemical substrates, is also presented. This can be used for identifying novobiocin-sensitive CNS strains from bovine mastitis.

A visual secret sharing scheme [1] permits a secret to be shared among participants using transparencies. In this paper, we consider an extended scheme for visual secret sharing. We propose an improved method of constructing the visual secret sharing scheme that can conceal some images in a series of transparencies, in such a way that different images are seen as the number of stacking transparencies increases. Furthermore, we describe applications of the visual secret sharing scheme to copy machines and human identification schemes. In the identification scheme, users recognize messages from an identification terminal by stacking their transparencies on the display. A great advantage of this scheme is that users can validate the authenticity of the terminal without consulting a computer or calculator. © 1998 Scripta Technica. Electron Comm Jpn Pt 3, 81(7): 55–63, 1998

A parallel fixed-point implementation of a general predictive controller is derived. It is based on the concepts of predictive control outlined by Chisci, Zappa and Mosca. These controllers use parallel identification arrays as the basic building blocks. In this paper the largest part of the standard information filter array is replaced with a similar array which uses normalized data suitable for fixed-point VLSI implementation. The normalization ensures that all the data are within the range [ - 1, 1]. The controller includes an effective regularization scheme which allows a priori information about the plant and the controller to be included and kept permanently present in the identification scheme. Users can select the level of the influence of this a priori information on the controller adaptation relative to the effect of the measured data. The resultant architecture is suitable for fixed-point VLSI or DSP application aiming for low power and minimal complexity or maximal speed.

User identification plays an important role for access control in networks. Recently, Hsu and Chuang proposed a user identification scheme for distributed computer networks, which can also provide key agreement and user anonymity. However, Tsai pointed out the weakness of Hsu-Chuang's scheme and proposed an improved scheme. In this paper, we present two attacks to examine that some user identification schemes have a serious security loophole. Finally, we propose a new user identification scheme, which is more secure than the existing schemes.Copyright © 2013 John Wiley & Sons, Ltd.

This article describes a coherent strategy for the intelligent monitoring of structures and systems. All the relevant features of the strategy are discussed in detail. These encompass (i) a taxonomy for the relevant concepts, i.e., a precise definition of what, for example, constitutes a fault. (ii) a specification for operational evaluation that makes use of a hierarchical damage identification scheme, (iii) an approach to sensor prescription and optimization, and (iv) a data-processing methodology based on a data fusion model. A number of recently proposed “axioms” are summarized in the hope that they will shed light on the design of monitoring systems; a number of possible barriers to progress are also identified and discussed. Keywords: intelligent fault detection; holistic design; pattern recognition; axioms for health monitoring; barriers to implementation

The development phase of the optical photolithography process has long been considered the most crucial, as it is the final image-forming step. Process monitoring methods have focused primarily on end point detection and have not used other inferable on-line information. This paper examines the use of mathematical models in conjunction with on-line development penetration data to determine process changes. An on-line sequential parameter identification scheme is used to calculate a current rate parameter value for the development model, and a Kalman filter is used to reduce erroneous observations caused by measurement noise. A powerful development monitor system results from the combination of real-time data, and on-line parameter and state estimation theory.

In the simulation and design of piezoelectric transducers the exact knowledge of the entries in the material tensors - the elastic, dielectric and piezoelectric coupling coefficients - is an important prerequisite. Our task is the identification of these coefficients from indirect measurements, namely electric impedance data at different frequencies. This leads to a parameter identification problem for a system of coupled PDEs, which we solve by regularized Newton iterations. A crucial issue is the selection of frequencies at which measurements are taken. Here, we discuss the problem of choosing these frequencies in an optimal way to preserve efficiency of our identification scheme while improving reliability of the reconstruction results. For this purpose, we formulate this task as an optimization problem with PDE constraints and propose two approaches for its solution.

In an effort to study the dynamic characteristics of an arch dam system from the vibration test results, a systematic method of frequency-domain system identification is developed. The governing equations for system identification are based on a non-classical modal superposition method. The non-classical model is shown to be derivable from a general matrix formulation of the dam system. The conventional classical modal formulation becomes a special case of the general non-classical formulation. The modal parameters of the non-classical and the classical formulation are to be identified. The system identification method includes a single-mode sweep procedure for initial parameter estimation and a progressive multiple-mode parameter identification scheme that contains an information criterion for the determination of the optimal number of modes to be included in the identification process. The method is applicable to data measured at more than one point on the dam and to data that include both the amplitude response and the phase response. The method is applied to the vibration test data of two dams. Based on the results of these applications, the adequacy of the classical model and the non-classical model is compared and the effect of the phase data on the parameter determination is discussed.

An identification scheme for surface-active agents is given which enables these agents or their mixtures to be detected in commercial products. Use is made of the acid resistance of the various types, which make it possible to separate the different compounds step by step from the mixture.

This paper reports on an investigation of the effect of adaptive control on a closed-loop chemical plant. The plant controlled was a simple closed-loop feedback system, the elements of which were a proportional controller and an elementary continuous stirred-tank reactor. The reaction involved was an exothermic, single-reactant decomposition, with the control criterion being the integral of the square of the deviation of the output composition from a value determined by a reference model. The adaptive control system incorporated an automatic identification scheme and a decision process, and operated in the presence of disturbances in cooling water temperature and/or catalyst activity. The adaptive control system yielded excellent results. For all disturbances, the output of the adaptive controlled plant remained much closer to the reference model output than did the output of the simply controlled plant. Inclusion of an adaptive capability in a control system thus appears to be desirable and often feasible.