An embedded audio–visual tracking and speech purification system on a dual-core processor platform

Design of an embedded audio–visual tracking and speech purification system is described in this paper. The system is able to perform human face tracking, voice activity detection, sound source direction estimation, and speech enhancement in real-time. Estimating the sound source directions helps to initialize the human face tracking module when the target changes the direction. The implementation architecture is based on an embedded dual-core processor, Texas Instruments DM6446 platform (Davinci), which contains an ARM core and a DSP core. For speech signal processing, an eight-channel digital microphone array is developed and the associated pre-processing and interfacing features are designed using the Altera Cyclone II FPGA. All the experiments are conducted in a real environment and the experimental results show that this system can execute all the audition and vision functions in real-time.     

Design and Performance Evaluation of Residual Generators for the FDI of an Aircraft

In this work, several procedures for the fault detection and isolation （FDI） on general aviation aircraft sensors are presented. In order to provide a comprehensive wide-pectrum treatment, both linear and nonlinear, model-based and data-driven methodologies are considered. The main contributions of the paper are related to the development of both FDI polynomial method （PM） and FDI scheme based on the nonLinear geometric approach （NLGA）. As to the PM, the obtained results highlight a good trade-off between solution complexity and resulting performances. Moreover, the proposed PM is especially useful when robust solutions are required for minimising the effects of modelling errors and noise, while maximising fault sensitivity. As to the NLGA, the proposed work is the first development and robust application of the NLGA to an aircraft model in flight conditions characterised by tight-oupled longitudinal and lateral dynamics. In order to verify the robustness of the residual generators related to the previous FDI techniques, the simulation results adopt a typical aircraft reference trajectory embedding several steady-tate flight conditions, such as straight flight phases and coordinated turns. Moreover, the simulations are performed in the presence of both measurement and modelling errors. Finally, extensive simulations are used for assessing the overall capabilities of the developed FDI schemes and a comparison with neural networks （NN） and unknown input Kalman filter （UIKF） diagnosis methods is performed.     

Evaluation and Choice of Various Branch Predictors for Low-Power Embedded Processor

Power is an important design constraint in embedded computing systems.To meet the power constraint,microarchitecture and hardware designed to achieve high performance need to be revisited,from both performance and power angles.This paper studies one of them:branch predictor.As well known,branch prediction is critical to exploit instruction level parallelism effectively,but may incur additional power consumption due to the hardware resource dedicated for branch prediction and the extra power consumed on mispredicted branches.This paper explores the design space of branch prediction mechanisms and tries to find the most beneficial one to realiz elow-power embedded processor.The sample processor studied is Godson-like processor,which is adual-issue,out-of-order processor with deep pipeline,supporting MIPS instruction set.     

On various types of decoupling for time-varying systems†

This paper deals with the problem of decoupling a class of linear time-varying multi-variable systems, based on the defining property that the impulse response matrix of a decoupled system is diagonal. Depending on the properties of the coefficient matrices of the vector differential equation of the open-loop system, the system may be uniformly or totally decoupled. The necessary and sufficient conditions that permit a system to be uniformly or totally decoupled by state variable feedback are given. The main contribution of this paper is the precise definition of these two classes of decoupling and a rigorous derivation of the necessary and sufficient conditions which show the necessity of requiring that the system be of constant ordered rank with respect to observability. A simple example illustrates the importance of having several definitions of decoupling. Finally, the results are specialized to the case of time invariant systems.     

Can We Talk? Methods for Evaluation and Training of Spoken Dialogue Systems

There is a strong relationship between evaluation and methods for automatically training language processing systems, where generally the same resource and metrics are used both to train system components and to evaluate them. To date, in dialogue systems research, this general methodology is not typically applied to the dialogue manager and spoken language generator. However, any metric for evaluating system performance can be used as a feedback function for automatically training the system. This approach is motivated with examples of the application of reinforcement learning to dialogue manager optimization, and the use of boosting to train the spoken language generator.     

Integration Framework and Key Technology of Big Earth Datafor SDGs and Beautiful China Evaluation

Construction of UN Sustainable Development Goals(SDGs) and Beautiful Chinashare the same meaning.Both of them endeavor to achieve national and regional social,environment and economy sustainable development.Accurate,reliable,timely and well classified data is the key for accurate evaluation of sustainable development.In order to address issues such as single data source,poor timeliness,lack of high accuracy and evaluation results unreliable,we puts forward the integration framework and standardization of the bigearth data which includes big network data,big remote sensing data,and big socioeconomic data facing to the evaluation of SDGs and Beautiful China.Then,the key technologies of network data acquisition and analysis,remote sensing data information intelligent extraction and socioeconomic data spatialization are analyzed from different perspectives.Taking the water contamination accident of SDG 6,forest information extraction of SDG 15,population spatialization of common requirements in SDGs as examples,the application of technological routes in supporting sustainable development evaluation based on big earth data are studied consequently.     

Retrieval of atmospheric and oceanic properties from MERIS measurements: A new Case‐2 water processor for BEAM

A freely available data processor for the B asic E RS & ENVISAT ( A )ATSR and M ERIS Toolbox (BEAM) was developed to retrieve atmospheric and oceanic properties above and of Case‐2 waters from Medium Resolution Imaging Spectrometer (MERIS) Level1b data. The processor was especially designed for European coastal waters and uses MERIS Level1b Top‐Of‐Atmosphere (TOA) radiances to retrieve atmospherically corrected remote sensing reflectances at the Bottom‐Of‐Atmosphere (BOA), spectral aerosol optical thicknesses (AOT) and the concentration of three water constituents, namely chlorophyll‐a (CHL), total suspended matter (TSM) and the absorption of yellow substance at 443 nm (YEL). The retrieval is based on four separate artificial neural networks which were trained on the basis of the results of extensive radiative transfer (RT) simulations by taking various atmospheric and oceanic conditions into account. The accuracy of the retrievals was acquired by comparisons with concurrent in situ ground measurements and was published in full detail elsewhere. For the remote sensing reflectance product a mean absolute percentage error (MAPE) of 18% was derived within the spectral range 412.5–708.75 nm while the accuracy of the AOT at 550 nm in terms of MAPE was calculated to be 40%. The accuracies for CHL, TSM and YEL were derived from match‐up analysis with MAPEs of 50%, 60% and 71%, respectively.     

The FEAST indices—realistic evaluation of modern software components and processor technologies

We examine the computational efficiency of linear algebra components in iterative solvers for grid-oriented simulations of PDEs. While the standard sparse matrix-vector (MV) techniques show significant losses of performance, especially on modern processors, our sparse banded components have the potential to exploit today's high computing power. We explain the major concepts of the FEAST software which contains such highly tuned numerical linear algebra basic components (Sparse Banded Blas) up to complete multigrid solvers, all being optimized with respect to the actual hardware platform. Based on algorithmic and computational studies, we present the FEAST indices which are indicators for the true performance of many modern processors, depending on the underlying FEM space, the problem size and the implementation style. These indices allow a new rating of the various hardware platforms with regard to different mathematical solution strategies, for academic and realistic numerical problems and ranging from ‘low cost’ PCs up to supercomputers.     

Jeffrey’s rule of conditioning with various forms for uncertainty

We first introduce Jeffrey’s rule of conditioning and explain how it allows us to determine the probability of an event related to one variable from information about a collection of conditional probabilities of that event conditioned on the state another variable. We note that in the original Jeffrey paradigm we have the uncertainty about the state of the conditioning variable expressed as a probability distribution. Here we extend this by allowing alternative formulations for the uncertainty about the conditioning variable. We first consider the case where our uncertainty is expressed in terms of a measure. This allows us to consider the case where our uncertainty is a possibility distribution. We next consider the case where our uncertainty about the conditioning variable is expressed in terms of a Dempster–Shafer belief structure. Finally we consider the case where we are ignorant about the underlying distribution and must use the decision maker’s subjective attitude about the nature of uncertainty to provide the necessary information to use in the Jeffrey rule.     

Graph Traversal and Top-Down Evaluation of Logic Queries

In this paper,an optimal method to handle cyclic and acyclic data relations in the linear recursive queries is proposed.High efficiency is achieved by integrating graph traversal mechanisms into a top-down evaluation.In such a way,the subsumption checks and the identification of cyclic data can be done very efficiently.First,based on the subsumption checks,the search space can be reduced drastically by avoiding any redundant expansion operation.In fact,in the case of non-cyclic data,the proposed algorithm requires only linear time for evaluating a linear recursive query.On the other hand,in the case of cyclic data,by using the technique for isolaiting strongly connected components a lot of answers can be generatded directly in terms of the intermediate results and the relevant path information instead of evaluating them by performing algebraic operations.Since the cost of generating an answer in much less than that of evaluating an answer by algebraic operations,the bime consumption for cyclic data can be reduced by an order of magnitude or more.     

HumanEva: Synchronized Video and Motion Capture Dataset and Baseline Algorithm for Evaluation of Articulated Human Motion

While research on articulated human motion and pose estimation has progressed rapidly in the last few years, there has been no systematic quantitative evaluation of competing methods to establish the current state of the art. We present data obtained using a hardware system that is able to capture synchronized video and ground-truth 3D motion. The resulting HumanEva datasets contain multiple subjects performing a set of predefined actions with a number of repetitions. On the order of 40,000 frames of synchronized motion capture and multi-view video (resulting in over one quarter million image frames in total) were collected at 60 Hz with an additional 37,000 time instants of pure motion capture data. A standard set of error measures is defined for evaluating both 2D and 3D pose estimation and tracking algorithms. We also describe a baseline algorithm for 3D articulated tracking that uses a relatively standard Bayesian framework with optimization in the form of Sequential Importance Resampling and Annealed Particle Filtering. In the context of this baseline algorithm we explore a variety of likelihood functions, prior models of human motion and the effects of algorithm parameters. Our experiments suggest that image observation models and motion priors play important roles in performance, and that in a multi-view laboratory environment, where initialization is available, Bayesian filtering tends to perform well. The datasets and the software are made available to the research community. This infrastructure will support the development of new articulated motion and pose estimation algorithms, will provide a baseline for the evaluation and comparison of new methods, and will help establish the current state of the art in human pose estimation and tracking.     

Minimum–Maximum regret redundancy allocation with the choice of redundancy strategy and multiple choice of component type under uncertainty

This paper deals with a redundancy allocation problem in series–parallel systems with the choice of redundancy strategy, including active and cold standby strategies in which component’s time to failure follows an Erlang distribution. The scale parameter of Erlang distribution and consequently the reliability of each component are imprecise in terms of interval data, and only the lower and upper bounds are known. This problem, for the first time, is formulated through Min–Max regret criterion, which is commonly used to define robust solutions. The resulting problem formulation contains an unlimited number of constraints, and a Benders’ decomposition method is implemented to deal with the given problem. This method is compared with an enumeration method to show its effectiveness. The performance of the proposed model using the Benders’ decomposition method is examined over different problem sizes, and the associated results are analyzed.     

An approach to design and implementation of on-chip clock generator for the switched capacitor based embedded DC–DC converter

Here, the design and implementation of an on-chip clock generator which is needed for a switched capacitor based embedded DC–DC converter is described. The strategies that should be taken during making the design by predicting the occurrence of the parasitic issues at the time of implementation to keep the performance of the clock generator at per in silicon are also elaborated. The reported measurement results closely match with the simulation results in clock generation. It can be a helpful tutorial paper to design and implement an on-chip clock generator suitable for mid-frequency, real time applications.     

Predictive control,embedded cyberphysical systems and systems of systems – A perspective

Today’s world is changing rapidly due to advancements in information technology, computation and communication. Actuation, communication, sensing, and control are becoming ubiquitous. These technological advancements have led to the widespread availability of information and the possibility to connect systems in unforeseen manner. There is a strong desire for smart(er) cities, buildings, devices, factories, health monitoring – a smarter world. However, designing such a smarter world requires addressing also many challenges resulting from the emerging complex interactions and interoperation of systems. How is it possible to handle the increasing complexity during design and maintenance of such systems? How can one guarantee safety and performance of systems operating over networks which are subject to erroneous communication, delays, and failures of sensors and actuators? Is it possible to design control systems which allow for easy reconfiguration or even self-organization, for example by letting subsystems join and leave larger systems via plug and play strategies? Can one guarantee privacy of the controlled subsystems while exchanging information, which is necessary for maintaining overall system performance? We believe that predictive control is a well suited control approach to tackle some of these challenges due to its flexibility with respect to the formulation of the problem and the possibility to directly take constraints, preview information, as well as models of different complexity of the physical world into account. In this perspective we limit our attention to three areas we believe predictive control methods can provide a basis to tackle the appearing challenges: the efficient and easy implementation of predictive control on omnipresent embedded computation hardware, the question of resource and network aware control, as well as control on the network level of systems of systems. We briefly summarize results from these fields and outline some ideas on challenges, which arise.     

Design and Simulative Evaluation of Architectural Physical Environment with Ecotect

1 Introduction Design and pre-estimate of architectural physical environment engineering is one of important research context in architectural engineering. Nowadays, living environment has been the focus as the government promotes sustainable development vigorously. And the quality of human’s living environment is closely linked with architectural physical environment especially under the situation of energy shortage. Architecture is the main reason of energy consumption and the waste is also…     

The Realization and Discussion of the Credit Risk Evaluation System

This paper introduces a credit risk evaluation system of financial organization based on CBR （Case-Based Reasoning） and RBR （Rule-Based Reasoning）, which combines the advantages of the two reasoning approaches. It focuses on the realization and improvement of CBR in this system, and introduces the algorithm of case matching similarity and the improvement of the case base maintenance approach, Meanwhile, it points out some questions of this system and brings forward the further study directions.     

Save the best for last? The treatment of dominant predictors in financial forecasting

We study forecasting applications where the response variable is heavily correlated with one or a small set of covariates which we term dominant predictors. Dominant predictors commonly occur in financial forecasting where future market prices are heavily influenced by current prices, and to a much lesser degree, by many other, more subtle factors such as weather or calendar effects. We hypothesize that dominating predictors may mask the influence of the subtle factors, reducing forecasting accuracy. Consequently, we argue that it is crucial to find means of accurately accounting for the effect of the subtle factors on the response variable. To achieve this we present a two-stage modeling methodology which postpones the introduction of dominating predictors into the model building process until all predictive value from the other covariates has been extracted. To confirm our hypothesis and to test the effectiveness of the two-stage approach, we conduct an empirical study related to forecasting the outcome of sports events, which are well known to exhibit dominating predictors. Our results confirm that especially complex, nonlinear models are vulnerable to the masking effect and benefit from the two-stage paradigm. Our findings have important implications for forecasters who operate in environments where the influence of some predictors on the variable being forecast exceeds those of other covariates by a wide margin and we demonstrate appropriate ways to approach such forecasting tasks.     

A Form Evaluation System and Its Data Structure for Brush-Written Chinese Characters

A form evaluation system for brush-written Chinese characters is developed.Calligraphic knowledge used in the system is represented in the form of rules with the help of a data structure proposed in this paper.Reflecting the specific hierarchical relations among radicals and strokes of Chinese characters,the proposed data structure is based upon a character model that can generate brush-written Chinese characters on a computer.Through evaluation experiments using the developed system,it is shown that representation of calligraphic knowledge and form evaluation of Chinese characters can be smoothly realized if the data structure is utilized.     

Improving performance and energy efficiency of embedded processors via post-fabrication instruction set customization

Encapsulating critical computation subgraphs as application-specific instruction set extensions is an effective technique to enhance the performance and energy efficiency of embedded processors. However, the addition of custom functional units to the base processor is required to support the execution of custom instructions. Although automated tools have been developed to reduce the long design time needed to produce a new extensible processor for each application, short time-to-market, significant non-recurring engineering and design costs are issues. To address these concerns, we introduce an adaptive extensible processor in which custom instructions are generated and added after chip-fabrication. To support this feature, custom functional units (CFUs) are replaced by a reconfigurable functional unit (RFU). The proposed RFU is based on a matrix of functional units which is multi-cycle with the capability of conditional execution. To generate more effective custom instructions, they are extended over basic blocks and hence, multiple-exits custom instruction and intuition behind it are introduced. Conditional execution capability has been added to the RFU to support the multi-exit feature of custom instructions. Because the proposed RFU has limitations on hardware resources (i.e., connections and processing elements), an integrated mapping-temporal partitioning framework is proposed to guarantee that the generated custom instructions can be mapped on the RFU (mappable custom instructions). Experimental results show that multi-exit custom instructions enhance the performance and energy efficiency by an average of 32% and 3% compared to custom instructions limited to one basic block, respectively. A maximum speedup of 4.9, compared to a single-issue embedded processor, and an average speedup of 1.9 was achieved on MiBench benchmark suite. The maximum and average energy saving are 56% and 22%, respectively. These performance and energy efficiency are obtained at the cost of 30% area overhead.