盲源分离在单通道语音增强算法中的应用

提出一种单通道语音增强算法。首先由接收到的单声道语音信号的含噪部分构造一个假想噪声源,将这一噪声源和含噪的信号作为多通道自适应去相关（MAD）盲分离算法的输入,得到增强的语音信号。进一步将这一增强的语音作为输入,利用Daubechies小波对其进行分解,在小波域中选取合适的阈值函数进行滤波,然后合成时域语音信号。根据以上步骤得到的增强语音有较高的信噪比及可懂度。     

A hybrid scheduling scheme for data broadcast over a single channel in mobile environments

Various broadcast schemes have been proposed to reduce the data access time of mobile clients. However, they are based either on the mobile users’ data access frequencies or on the semantic relations of the data. In this paper, we present a hybrid data broadcast scheme based both on semantic relationships and access probabilities. The broadcast scheme we propose generates a broadcast sequence according to the semantic relationships and replicates popular data items several times according to the data access probabilities. The efficiency of our broadcast scheme is shown via performance evaluations.     

A link between dispersion models and monitoring data: The estimate of source term

An important application of real-time atmospheric dispersion models is the link between model results and field measurements to achieve an estimate of the source term of a continous realease. In this paper a method for the evaluation of the emission rate (STEP: Source Term Estimate Program) is presented. STEP doesn't depend on the dispersion model used and is based on few, simple considerations about the cause of the commonly observed scatter between measured and computed concentration values at fixed sample points. The results of two STEP tests are presented: firstly, it has been validated against a set of tracer data collected during two meteorological and diffusion campaigns; secondly, a sensitivity study with respect to meteorological parameters and to the number of monitoring data available was carried out.     

A new fuzzy network data envelopment analysis model for measuring efficiency and effectiveness: assessing the sustainability of railways

Applied Intelligence - Sustainability assessment of organizations in terms of technical efficiency (TE) and service effectiveness (SE) for non-storage goods has always been an interesting topic for...     

GeoNet: An open source software for the automatic and objective extraction of channel heads,channel network,and channel morphology from high resolution topography data

Extracting hydrologic and geomorphic features from high resolution topography data is a challenging and computationally demanding task. We illustrate the new capabilities and features of GeoNet, an open source software for the extraction of channel heads, channel networks, and channel morphology from high resolution topography data. The method has been further developed and includes a median filtering operation to remove roads in engineered landscapes and the calculation of hillslope lengths to inform the channel head identification procedure. The software is now available in both MATLAB and Python, allowing it to handle datasets larger than the ones previously analyzed. We present the workflow of GeoNet using three different test cases; natural high relief, engineered low relief, and urban landscapes. We analyze default and user-defined parameters, provide guidance on setting parameter values, and discuss the parameter effect on the extraction results. Metrics on computational time versus dataset size are also presented. We show the ability of GeoNet to objectively and accurately extract channel features in terrains of various characteristics.     

An analysis of the relation between stream channel sinuosity and stream channel gradient

Existing literature lends credence to the idea that channel sinuosity and channel gradient are independent morphologic elements responding to characteristics of the water and sediment regime of a stream. At the same time, sinuosity and gradient are viewed as closely related variables, since sinuosity is often defined as a ratio of valley gradient to channel gradient over a stream reach. These conceptions of the sinuosity variable are essentially contradictory if viewed from the standpoint of process, since in the latter case, water and sediment characteristics have no direct bearing on the determination of sinuosity, but only the potential of indirect influence operating through the channel gradient. This paper presents an empirical analysis aimed at evaluating the validity of these two conceptions of the sinuosity variable. The results of the analysis strongly support the gradient ratio concept and suggest that the traditional sinuosity variable is not reasonably viewed as an independent element of stream channel morphology, since it is essentially determined by the same process as that which determines the channel gradient. Thus, channel sinuosity is insignificantly influenced by the direct effects of water and sediment discharge. Certain indirect effects of these factors do exist, however, given the role of channel gradient in the determination of sinuosity. A summary of these results is given in the form of a two-equation recursive model.     

Atmospheric corrections of single broadband channel and multidirectional airborne thermal infrared data: Application to the ReSeDA experiment

This study focused on atmospheric corrections of airborne thermal infrared remote sensing data acquired with a multidirectional and single broadband channel sensor during the ReSeDA experiment. For single channel sensors, atmospheric corrections are generally performed using atmospheric radiative transfer models such as MODTRAN 3.5 along with radiosoundings. A sensitivity study was performed using MODTRAN 3.5 simulations to assess the accuracy of the processing regarding the experimental context. It was shown that the local topography and the atmosphere spatial variability could affect significantly the radiosounding representativeness, whereas the fluctuations of the flight altitude around the nominal value induced non-negligible inaccuracies. Moreover, using a broadband sensor induced non-linear effects that required a second order correction and also the use of look-up tables to reduce computation time. A theoretical error was next proposed to account for both the sensor accuracy and the experimental uncertainties considered when performing the sensitivity study. This theoretical error was about 1°C, and agreed well with the results obtained when validating against field measurements.     

An extensive analysis of the interaction between missing data types,imputation methods,and supervised classifiers

When applying data-mining techniques to real-world data, we often find ourselves facing observations that have no value recorded for some attributes. This can be caused by several phenomena, such as a machine’s incapability to record certain characteristics or a person refusing to answer a question in a poll. Depending on that motivation, values gone missing may follow one kind of pattern or another, or describe no regularity at all. One approach to palliate the effect of missing data on machine learning tasks is to replace the missing observations. Imputation algorithms attempt to calculate a value for a missing gap, using information associated with it, i.e., the attribute and/or other values in the same observation. While several imputation methods have been proposed in the literature, few works have addressed the question of the relationship between the type of missing data, the choice of the imputation method, and the effectiveness of classification algorithms that used the imputed data. In this paper we address the relationship among these three factors. By constructing a benchmark of hundreds of databases containing different types of missing data, and applying several imputation methods and classification algorithms, we empirically show that an interaction between imputation methods and supervised classification can be deduced. Besides, differences in terms of classification performance for the same imputation method in different missing data patterns have been found. This points to the convenience of considering the combined choice of the imputation method and the classifier algorithm according to the missing data type.     

From data to knowledge: The interaction between data management systems in educational institutions and the delivery of quality education

No school is an island; it is a part of a continuum or a pipeline of institutions which together form an educational pipeline through which groups of students pass. To turn a body of data into useful information for knowledge-based decision-making at any level, data must be collected, organised, analysed and reflected upon. The purpose of this paper is to discuss how schools and other educational institutions can not only collect better data but learn how to transform that data so that the information held within can be effectively shared among all stakeholders. This process will help to ensure that the school and the entire education system provide a more seamless and effective educational pipeline for students, and ultimately improve the quality of education delivered in the country as a whole.     

From data to knowledge: The interaction between data management systems in educational institutions and the delivery of quality education

No school is an island; it is a part of a continuum or a pipeline of institutions which together form an educational pipeline through which groups of students pass. To turn a body of data into useful information for knowledge-based decision-making at any level, data must be collected, organised, analysed and reflected upon. The purpose of this paper is to discuss how schools and other educational institutions can not only collect better data but learn how to transform that data so that the information held within can be effectively shared among all stakeholders. This process will help to ensure that the school and the entire education system provide a more seamless and effective educational pipeline for students, and ultimately improve the quality of education delivered in the country as a whole.     

Control and data flow compatibility in the interaction between dynamic business processes

In the coming years, one of the challenges for business processes is to obtain a high degree of flexibility and ability to adapt to the changing contexts. Two key elements for achieving this are the use of Semantic Web technologies and the possibility of decoupling the business and the interaction aspects in a business process. Nevertheless, these solutions open up new challenges related to the necessity of checking whether a set of processes can successfully cooperate. Compatibility questions should be considered from a control flow point of view (the order of the interactions should be appropriate) and also from a data flow point of view (the information exchanged should be—semantically—adequate). In this paper, we concentrate on the compatibility of a set of processes executed in DENEB, a platform for the Development and ExecutioN of wEB processes based on the Net‐within‐Nets formalism and that follows a conversational approach. More specifically, this paper examines whether a set of interactions among a set of processes is compatible and also whether a given (imposed) interaction logic is compatible with a given business logic. Processes and their interactions have been semantically enhanced by means of domain ontologies and compatibility questions are studied using standard Petri net analysis techniques. Copyright © 2010 John Wiley & Sons, Ltd.     

FEM-based analysis of the local-plate/distortional mode interaction in cold-formed steel lipped channel columns

This paper reports the results of a numerical investigation concerning the elastic and elastic–plastic post-buckling behaviour of cold-formed steel lipped channel columns affected by local-plate/distortional buckling mode interaction. The results presented and discussed were obtained through analyses performed using the finite element code Abaqus and discretising the columns by means of fine 4-node shell element meshes. The columns analysed (i) are simply supported (end sections locally/globally pinned and free-to-warp), (ii) have cross-section dimensions that ensure equal local-plate and distortional critical buckling stresses, thus maximising the local-plate/distortional mode interaction effects, and (iii) contain critical-mode initial geometrical imperfections that exhibit different shapes but share the same combined amplitude. The numerical post-buckling results reported consist of (i) elastic and elastic–plastic non-linear equilibrium paths, (ii) curves and figures describing how the column deformed configuration (expressed as a linear combination of its local-plate and distortional components) evolves along the elastic post-buckling equilibrium paths and (iii) figures providing a clear visualisation of the (iii₁) evolution of the elastic–plastic column deformed configurations, (iii₂) the growth of the plastic strains and (iii₃) failure mechanisms exhibited by a fairly large portion of the elastic–plastic columns that were analysed in this work.     

An analysis of the C-PODA protocol for a satellite data communication channel

The Contention-Based Priority Oriented Demand Assignment (C-PODA) protocol is analyzed in this paper. The average waiting time of a message is derived by applying results from bulk service queueing systems. Analytical results are validated by simulation and experimentation. The fairness problem associated with the C-PODA protocol is also studied and a fairness control algorithm is proposed.     

A method for the analysis of the interaction between users and objects in 3D navigational space

Along with the improvement of eye-tracking technology, more and more distinct field of researches have introduced movements of the eye in relation to the head to understand user behavior. Most of current researches focus on the perception process of single 2-dimensional images by fixed eye-tracking devices or the head-mount devices. A method of applying eye-tracking on the analysis of the interaction between users and objects in 3D navigational space is proposed in this article. It aims to understand the visual stimulation of 3D objects and the user’s spatial navigational reactions while receiving the stimulation, and proposes the concept of 3D object attention heat map. It also proposes to construct a computational visual attention model for different geometric featured 3D objects by applying the method of feature curves. The VR results of this study also provide future assistance in the incoming immersive world. This study sets to promote eye-tracking from the mainstream of 2D field to 3D spaces and points to a deeper understanding between human and artificial product or natural objects. It would also serve an important role in the field of human-computer interaction, product usability, aids devices for cognition degenerative individuals, and even the field of visual recognition of daily human behavior.     

A rainfall-runoff probabilistic simulation program: 2. Synthetic data analysis

The development of a best-fit unit hydrograph to rainfall-runoff data is an important problem in flood control hydrology. In this paper, a computer program is described that is useful in determining an optimum unit hydrograph to rainfall-runoff data, and the sensitivity of the unit hydrograph to various hydrologic effects. By such an analysis, priority can be placed on fine-tuning data collection where sensitivity is greatest.     

A probabilistic analysis of bias optimality in unichain Markovdecision processes

Focuses on bias optimality in unichain, finite state, and action-space Markov decision processes. Using relative value functions, we present methods for evaluating optimal bias, this leads to a probabilistic analysis which transforms the original reward problem into a minimum average cost problem. The result is an explanation of how and why bias implicitly discounts future rewards