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Training-based transmission over Rayleigh block-fading multiple-input multiple-output (MIMO) channels is investigated. As a training method a combination of a pilot-assisted scheme and a biased signaling scheme is considered. The ...
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Training-based transmission over Rayleigh block-fading multiple-input multiple-output (MIMO) channels is investigated. As a training method a combination of a pilot-assisted scheme and a biased signaling scheme is considered. The achievable rates of successive decoding (SD) receivers based on the linear minimum mean-squared error (LMMSE) channel estimation are analyzed in the large-system limit, by using the replica method under the assumption of replica symmetry. It is shown that negligible pilot information is best in terms of the achievable rates of the SD receivers in the large-system limit. The obtained analytical formulas of the achievable rates can improve the existing lower bound on the capacity of the MIMO channel with no channel state information (CSI), derived by Hassibi and Hochwald, for all SNRs. The comparison between the obtained bound and a high-SNR approximation of the channel capacity, derived by Zheng and Tse, implies that the high-SNR approximation is unreliable unless quite high SNR is considered. Energy efficiency in the low-SNR regime is also investigated in terms of the power per information bit required for reliable communication. The required minimum power is shown to be achieved at a positive rate for the SD receiver with no CSI, whereas it is achieved in the zero-rate limit for the case of perfect CSI available at the receiver. Moreover, numerical simulations imply that the presented large-system analysis can provide a good approximation for not so large systems. The results in this paper imply that SD schemes can provide a significant performance gain in the low-to-moderate SNR regimes, compared to conventional receivers based on one-shot channel estimation.
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A century of revolutionary growth in aviation has made global travel a reality of daily life. Aircraft and air transport overcame a number of formidable challenges and hostilities in the physical world. Success in this arduous pur...
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A century of revolutionary growth in aviation has made global travel a reality of daily life. Aircraft and air transport overcame a number of formidable challenges and hostilities in the physical world. Success in this arduous pursuit was not without leveraging advances of the “cyber” layer, i.e., digital computing, data storage and networking, and software, in hardware, infrastructures, humans, and processes, within the airframe, in space, and on the ground. The physical world, however, is evolving continuously in the 21st century, contributing traffic growth and diversity, fossil fuel and ozone layer depletion, demographics and economy dynamics, as some major factors in aviation performance equations. In the next 100 years, apart from breakthrough physical advances, such as aircraft structural and electrical designs, we envision aviation's progress will depend on conquering cyberspace challenges and adversities, while safely and securely transitioning cyber benefits to the physical world. A tight integration of cyberspace with the physical world streamlines this vision. This paper proposes a novel cyber-physical system (CPS) framework to understand the cyber layer and cyber-physical interactions in aviation, study their impacts, and identify valuable research directions. This paper presents CPS challenges and solutions for aircraft, aviation users, airports, and air traffic management.
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Evolutionary multi-objective optimization algorithms are widely used for solving optimization problems with multiple conflicting objectives. However, basic evolutionary multi-objective optimization algorithms have shortcomings, su...
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Evolutionary multi-objective optimization algorithms are widely used for solving optimization problems with multiple conflicting objectives. However, basic evolutionary multi-objective optimization algorithms have shortcomings, such as slow convergence to the Pareto optimal front, no efficient termination criterion, and a lack of a theoretical convergence proof. A hybrid evolutionary multi-objective optimization algorithm involving a local search module is often used to overcome these shortcomings. But there are many issues that affect the performance of hybrid evolutionary multi-objective optimization algorithms, such as the type of scalarization function used in a local search and frequency of a local search. In this paper, we address some of these issues and propose a hybrid evolutionary multi-objective optimization framework. The proposed hybrid evolutionary multi-objective optimization framework has a modular structure, which can be used for implementing a hybrid evolutionary multi-objective optimization algorithm. A sample implementation of this framework considering NSGA-II, MOEA/D, and MOEA/D-DRA as evolutionary multi-objective optimization algorithms is presented. A gradient-based sequential quadratic programming method as a single objective optimization method for solving a scalarizing function used in a local search is implemented. Hence, only continuously differentiable functions were considered for numerical experiments. The numerical experiments demonstrate the usefulness of our proposed framework.
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This paper provides a foundation for decision making with bounded rationality in economic entities from the viewpoint of evolutionary theory. To this end, first, we conducted an investment test with participants to extract a behav...
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This paper provides a foundation for decision making with bounded rationality in economic entities from the viewpoint of evolutionary theory. To this end, first, we conducted an investment test with participants to extract a behavioral learning model for activities with bounded rationality. We found that the decision-making model obtained from this behavioral science approach has characteristics that are frequently seen in the results of observations of instances of bounded rationality. Furthermore, the model presents some well-known biases in decision making, such as profit-and-loss asymmetry in risk avoidance, reference point dependence, and the asset effect. Next, using agent-based simulations, we examined whether our behavioral-learning model for activities had the capacity to become a stable strategy in a market environment where selection pressure exists. When, in response to maximum loss, a drawdown is set as an evaluation criterion for selection, the results of our simulations imply the following: 1) our decision-making model with bounded rationality has the capacity to become a stable evolutionary strategy and 2) entities with bounded rationality can survive in a competitive market. These results are antithetical to the evolutionary explanations used as a basis for rationality in traditional economics, and they indicate the possibility that many well-known biases in decision making can be derived evolutionarily from a single criterion.
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We are now developing a prototype of a 3000-m class underwater glider for virtual mooring. The vehicle glides back and forth between the sea surface and the seabed collecting ocean data at a specific point. Hydrodynamic forces act...
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We are now developing a prototype of a 3000-m class underwater glider for virtual mooring. The vehicle glides back and forth between the sea surface and the seabed collecting ocean data at a specific point. Hydrodynamic forces acting on the half-size model were measured to determine the optimal wing shape. Next, to obtain the dynamical–hydrodynamic coefficients, forced oscillation tests were carried out using the optimally shaped model. Finally, the motions of the glider were simulated using the hydrodynamic coefficients obtained from these model experiments. The experimental and calculated results are shown in this paper.
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Research problem: Tutorials and user manuals are important forms of impersonal support for using software applications, including electronic medical records (EMRs). Differences between user- and vendor-generated documentation may ...
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Research problem: Tutorials and user manuals are important forms of impersonal support for using software applications, including electronic medical records (EMRs). Differences between user- and vendor-generated documentation may indicate support needs, which are not sufficiently addressed by the official documentation, and reveal new elements that may inform the design of tutorials and user manuals. Research question: What are the differences between user-generated tutorials and manuals for an EMR and the official user manual from the software vendor? Literature review: Effective design of tutorials and user manuals requires careful packaging of information, balance between declarative and procedural texts, an action and task-oriented approach, support for error recognition and recovery, and effective use of visual elements. No previous research compared these elements between formal and informal documents. Methodology: We conducted a mixed-methods study. Seven tutorials and two manuals for an EMR were collected from three family health teams and compared with the official user manual from the software vendor. Documents were qualitatively analyzed using a framework analysis approach in relation to the principles of technical documentation described before. Subsets of the data were quantitatively analyzed using cross-tabulation to compare the types of error information and visual cues in screen captures between user- and vendor-generated manuals. Results and discussion: The user-developed tutorials and manuals differed from the vendor-developed manual in that they contained mostly procedural and not declarative information; were customized to the specific workflow, user roles, and patient characteristics; contained more error information related to work processes than software usage; and used explicit visual cues on screen captures to help users identify window elements. These findings imply that to support EMR implementation, tutorials and manuals need to be custo- ized and adapted to specific organizational contexts and workflows. The main limitation of the study is its generalizability. Future research should address this limitation and may explore alternative approaches to software documentation, such as modular manuals or participatory design.
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We propose a new framework for joint multichannel speech source separation and acoustic noise reduction. In this framework, we start by formulating the minimum-mean-square error (MMSE)-based solution in the context of multiple sim...
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We propose a new framework for joint multichannel speech source separation and acoustic noise reduction. In this framework, we start by formulating the minimum-mean-square error (MMSE)-based solution in the context of multiple simultaneous speakers and background noise, and outline the importance of the estimation of the activities of the speakers. The latter is accurately achieved by introducing a latent variable that takes $N+1$ possible discrete states for a mixture of $N$ speech signals plus additive noise. Each state characterizes the dominance of one of the $N+1$ signals. We determine the posterior probability of this latent variable, and show how it plays a twofold role in the MMSE-based speech enhancement. First, it allows the extraction of the second order statistics of the noise and each of the speech signals from the noisy data. These statistics are needed to formulate the multichannel Wiener-based filters (including the minimum variance distortionless response). Second, it weighs the outputs of these linear filters to shape the spectral contents of the signals' estimates following the associated target speakers' activities. We use the spatial and spectral cues contained in the multichannel recordings of the sound mixtures to compute the posterior probability of this latent variable. The spatial cue is acquired by using the normalized observation vector whose distribution is well approximated by a Gaussian-mixture-like model, while the spectral cue can be captured by using a pre-trained Gaussian mixture model for the log-spectra of speech. The parameters of the investigated models and the speakers' activities (posterior probabilities of the different states of the latent variable) are estimated via expectation maximization. Experimental results including - omparisons with the well-known independent component analysis and masking are provided to demonstrate the efficiency of the proposed framework.
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In this paper, a novel force-sensing method is proposed for a high-performance force control system based on friction-free and noise-free force observation. A periodic signal is inserted into the control system for friction reduct...
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In this paper, a novel force-sensing method is proposed for a high-performance force control system based on friction-free and noise-free force observation. A periodic signal is inserted into the control system for friction reduction. A combination of a high-order disturbance observer (DOB) (HDOB) and a Kalman filter is constructed to perform the force sensing. The HDOB is designed to estimate the force and reject oscillatory disturbances in the estimation. The force-sensing bandwidth is improved through effective noise suppression by the Kalman filter. Additionally, this paper proposes the application of the HDOB to the bilateral control system of a different master–slave mechanism. All the control algorithms are implemented in a field-programmable gate array with a high sampling rate that also enables the widening of the bandwidth of the force control system. The effectiveness of the proposed method is verified by experimental results.
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This paper presents a comparative analysis of different energy management schemes for a fuel-cell-based emergency power system of a more-electric aircraft. The fuel-cell hybrid system considered in this paper consists of fuel cell...
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This paper presents a comparative analysis of different energy management schemes for a fuel-cell-based emergency power system of a more-electric aircraft. The fuel-cell hybrid system considered in this paper consists of fuel cells, lithium-ion batteries, and supercapacitors, along with associated dc/dc and dc/ac converters. The energy management schemes addressed are state of the art and are most commonly used energy management techniques in fuel-cell vehicle applications, and they include the following: the state machine control strategy, the rule-based fuzzy logic strategy, the classical proportional–integral control strategy, the frequency decoupling/fuzzy logic control strategy, and the equivalent consumption minimization strategy. The main criteria for performance comparison are the hydrogen consumption, the state of charges of the batteries/supercapacitors, and the overall system efficiency. Moreover, the stresses on each energy source, which impact their life cycle, are measured using a new approach based on the wavelet transform of their instantaneous power. A simulation model and an experimental test bench are developed to validate all analysis and performances.
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Although the behavior of dielectric materials has been known since 1939 when R.D. Richtmyer showed that unmetalized dielectrics can operate as microwave resonators [1], it was only in the 1970s when real breakthroughs occurred in ...
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Although the behavior of dielectric materials has been known since 1939 when R.D. Richtmyer showed that unmetalized dielectrics can operate as microwave resonators [1], it was only in the 1970s when real breakthroughs occurred in ceramic technology, and low loss and temperature stable ceramics were developed. In 1975 the first practical dielectric resonator (DR) loaded microwave filter was reported at the IEEE MTT-S International Microwave Symposium [2]. Significant advancements in ceramic technology and the progress in satellite and mobile communications in the 1990s revived interest in DR applications for a wide variety of microwave components. A number of new materials such as zirconium-tin titanate, ZST ((Zr ? Sn)TiO4), barium zinc tantalate, BZT (Ba(Zn,Ta)O3), and barium magnesium tantalate, BMT (Ba(Mg,Ta)O3), with high-dielectric constant, high-quality factor and low-temperature coefficient were developed [3]. These new materials, along with the application of rigorous full-wave modeling and analysis methods, fueled the development of new DR filter configurations such as single and dual mode filters with elliptic transfer function. Today, DR filters and output multiplexers (OMUXs) are widely used in satellite communications because of their superior characteristics, such as smaller size, better temperature stability, and higher unloaded Q compared to conventional cavity-based OMUXs. A number of papers have been published on DR filters and OMUXs [4]?[6], [8], [9], but no comprehensive paper on the design of a DR-based OMUX has been reported. The large interchannel interaction (due to contiguity of channel filter frequencies, performance of one channel filter is effected by the presence of other channel filters), wide spurious free frequency band, and stringent in-band and out-of-band (OOB) specifications (such as large near band and far band rejections, small passband group delay and flatness), along with the requirement of high Q, low frequency drift with tem- erature, and high power handling capability, make the design of DR OMUXs extremely challenging. This article presents a practical approach to the design of C-band high power OMUXs based on single mode DR filters for space application (Figures 1 and 2), making extensive use of present day simulation capabilities. All the major steps involved in the design of a DR OMUX such as the concept of a singly terminated filter, conversion of doubly terminated filters to singly terminated filters using a series L-C circuit, modeling of the DR OMUX in a circuit simulator incorporating full wave effects, and the OMUX optimization sequence are explained in detail. A successful design of the DR filter is crucial to the eventual design of the DR OMUX.
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