A regression model based on the nearest centroid neighborhood

The renowned k-nearest neighbor decision rule is widely used for classification tasks, where the label of any new sample is estimated based on a similarity criterion defined by an appropriate distance function. It has also been used successfully for regression problems where the purpose is to predict a continuous numeric label. However, some alternative neighborhood definitions, such as the surrounding neighborhood, have considered that the neighbors should fulfill not only the proximity property, but also a spatial location criterion. In this paper, we explore the use of the k-nearest centroid neighbor rule, which is based on the concept of surrounding neighborhood, for regression problems. Two support vector regression models were executed as reference. Experimentation over a wide collection of real-world data sets and using fifteen odd different values of k demonstrates that the regression algorithm based on the surrounding neighborhood significantly outperforms the traditional k-nearest neighborhood method and also a support vector regression model with a RBF kernel.     

A stochastic neighborhood conditional autoregressive model for spatial data

A spatial process observed over a lattice or a set of irregular regions is usually modeled using a conditionally autoregressive (CAR) model. The neighborhoods within a CAR model are generally formed deterministically using the inter-distances or boundaries between the regions. An extension of CAR model is proposed in this article where the selection of the neighborhood depends on unknown parameter(s). This extension is called a Stochastic Neighborhood CAR (SNCAR) model. The resulting model shows flexibility in accurately estimating covariance structures for data generated from a variety of spatial covariance models. Specific examples are illustrated using data generated from some common spatial covariance functions as well as real data concerning radioactive contamination of the soil in Switzerland after the Chernobyl accident.     

邻近交叉路口交通灯数学模型

提出了一种新的邻近交叉路口交通数学模型,并用线性规划解决了邻近交叉路口中间路段容纳车辆有限的情况下,如何确定每个路口的交通灯时间分配以及邻近交叉路口交通灯的相位差,实现单位时间内路口车辆的总积累队长最少,从而缓解交通堵塞。     

A single model for process improvement

The FAA has spent many years evaluating and combining models and methods to establish and monitor IT process improvement. In 1997, it released the integrated Capability Maturity Model (iCMM), which blended three of the Capability Maturity Models - software, systems engineering, and software acquisition - developed by Carnegie Mellon University's Software Engineering Institute. iCMM version 2, released in 2001, updated and expanded version 1's set of engineering disciplines to better accommodate the IT processes associated with the agency's air-traffic-control business, as well as IT system deployment, transition, operation, maintenance, and retirement. It also included some processes that govern IT, such as leadership, strategic planning, and investment decision-making. With this breadth of coverage, we believe the iCMM is the most comprehensive model available for improving the performance of an organization that relies on complex IT systems to provide services. The iCMM also has a flexible structure that lets organizations use it to benchmark processes from other process improvement models in terms of either maturity or capability level. Finally, the model offers various appraisal methods so that organizations can understand current practice in relation to iCMM's best practices or measure process performance characteristics. Lessons have come from many years of iCMM application at FAA, and many have broad application to the IT community. Overall, using one model to cover processes that span many disciplines has clear advantages.     

基于领域关系广义混合模型图像分割的研究

针对高斯混合模型不能有效处理复杂噪声图像分割问题,提出了基于领域关系广义混合模型.在高斯混合模型基础上引入形状参数r提高混合模型对不同噪声适应能力,另外该方法结合图像中像素点邻域关系,融入像素点间的互动信息.与混合模型通常采用EM算法估计参数不同,该模型参数估计采用梯度方法,通过最小化负似然对数优化参数.实验结果表明,广义混合模型在处理高斯噪声,重尾噪声,混合噪声以及脉冲噪声图像分割问题都取得了很好的效果.     

Deciding word neighborhood with universal neighborhood automata

Given some form of distance between words, a fundamental operation is to decide whether the distance between two given words w and v is within a given bound. In earlier work, we introduced the concept of a universal Levenshtein automaton for a given distance bound n. This deterministic automaton takes as input a sequence χ of bitvectors computed from w and v. The sequence χ is accepted iff the Levenshtein distance between w and v does not exceed n. The automaton is called universal since the same automaton can be used for arbitrary input words w and v, regardless of the underlying input alphabet. Here, we extend this picture. After introducing a large abstract family of generalized word distances, we exactly characterize those members where word neighborhood can be decided using universal neighborhood automata similar to universal Levenshtein automata. Our theoretical results establish several bridges to the theory of synchronized finite-state transducers and dynamic programming. For small neighborhood bounds, universal neighborhood automata can be held in main memory. This leads to very efficient algorithms for the above decision problem. Evaluation results show that these algorithms are much faster than those based on dynamic programming.     

A continuous stirred tank heater simulation model with applications

This article presents a first principles simulation of a continuous stirred tank heater pilot plant at the University of Alberta. The model has heat and volumetric balances, and a very realistic feature is that instrument, actuator and process non-linearities have been carefully measured, for instance to take account of the volume occupied by heating coils in the tank. Experimental data from step testing and recordings of real disturbances are presented. The model in Simulink and the experimental data are available electronically, and some suggestions are given for their application in education, system identification, fault detection and diagnosis.     

A non-sequential just-in-time simulation model

Non-sequential Just-in-Time discrete-event simulation logic is presented. This logic allows for batches of parts to be routed from any operation to any other operation within the same facility or manufacturing cell. In addition, this logic is able to accommodate large batch-to-batch variations in processing times. Some initial results based on data collected from a manufacturer of industrial lift equipment are presented.     

Hierarchical simulation model with animation

There are many issues in computer simulation such as verifying model code, validating models, understanding the dynamics of systems and training the personnel. The developers of simulation tool have been interested in the animation, since it can help solve theproblems related to the above listed issues. Trying to display all the graphic objects representing the dynamics of the models being simulated, however, causes the distractionof focus, which results in solving the above listed problems difficult. The redundant graphic objects also increase the computer computation overhead. This paper presents a hierarchical animation environment in which the users can have better focus on the dynamics of system components by selectively choosing the hierarchical level and components within a level of the hierarchically structured model. When the model is large and complex in particular, the selection of observation level is needed. The design of the hierarchical animation is based on the DEVS (Discrete EVent system Specification) formalism, which is theoretically well grounded means of expressing modular and hierarchical models.     

A trust model for popular smart home devices

International Journal of Information Security - Nowadays, smart home devices like Amazon Echo and Google Home have reached mainstream popularity. Being in the homes of users, these devices are...     

Control improvement and approximately optimal synthesis in the neighborhood of a support trajectory

We consider problems of optimal control improvement and synthesis for continuous and discrete processes with a unified scheme that includes searching for an, at least, locally optimal process and implementing it via an approximately optimal positional control with Krotov’s estimate. For regular problems, this scheme is based on local approximation of the well-known Krotov-Bellman relations; for degenerate problems, on the corresponding generalized relations. We show how this scheme relates to the A.M. Letov’s ACOC theory and give specific examples.     

A compliant contact model with nonlinear damping for simulation ofrobotic systems

Contact modeling is an important aspect of simulation of many robotic tasks. In the paper, a compliant contact model with nonlinear damping is investigated, and many previously unknown characteristics of the model are developed. Compliance is used to eliminate many of the problems associated with using rigid body models with Coulomb friction, while the use of nonlinear damping eliminates the discontinuous impact forces and most sticky tensile forces which arise in Kelvin-Voigt linear models. Two of the most important characteristics of the model are the dependence of the coefficient of restitution on velocity and damping in a physically meaningful manner, and its computational simplicity. A full mathematical development for an impact response is given, along with the effects of the system and model parameters on energy loss. A quasistatic analysis gives results which are consistent with energy loss characteristics of a more complex distributed foundation model under sustained contact conditions. A foot contact example for a walking machine is given which demonstrates the applicability of the model for impact on foot placement, sustained contact during the support phase, and the breaking of the contact upon liftoff of the foot     

Variable neighborhood search for a planning problem with resource constraints in a health simulation center

Applied Intelligence - In this paper we propose the Variable Neighborhood Search (VNS) algorithm SimULS to solve a planning problem in the Health Simulation Center SimUSanté. This center...     

Cliques with maximum/minimum edge neighborhood and neighborhood density

Given a graph G=(V,E) and a clique C of G, the edge neighborhood of C can be defined as the total number of edges running between C and V?C, being denoted by N(C). The density of the edge neighborhood N(C) can be set as the ratio (|N(C)|/(|C|·|V?C|)).This paper addresses maximum/minimum edge neighborhood and neighborhood density cliques in G. Two versions will be undertaken, by fixing, or not, the size of the cliques.From an optimization point of view these problems do not bring much novelty, as they can be seen as particular or special versions of weighted clique problems. However, from a practical point of view, they concentrate on certain kinds of properties of cliques, rather than their size, revealing clique's engagement in the graph. In fact, a maximum edge neighborhood clique should be strongly embraced in the graph, while a minimum edge neighborhood clique should reveal an almost isolated strong component. In particular, special versions of the new problems allow to distinguish among cliques of the same size, namely among possible tied maximum cliques in the graph.We propose node based formulations for these edge based clique related problems. Using these models, we present computational results and suggest applications where the new problems can bring additional insights.     

A positivity-preserving zero-inertia model for flood simulation

Zero-Inertia Models (ZIMs), or Diffusion-Wave Models (DWMs), have been widely used in flood modelling in the last decade. In this work, an alternative formulation is proposed based on a new depth-positivity-preserving condition to solve the zero-inertia governing equation. The new condition does not use a flux limiter and is practical for flood simulations with wetting and drying over complex domain topographies. Two time stepping methods are considered and studied along with the proposed numerical model. The first one is based on the Courant-Friedrichs-Lewy (CFL) condition, which is widely used to control the time step for the explicit shallow water equation solvers; the second one is the adaptive time stepping (ATS) reported by Hunter et al. [1], which was specifically designed for a DWM. Numerical results and root-mean-square-error (RMSE) analysis show that the new model is able to provide stable and accurate solutions without the necessity for a flux limiter. Computational efficiency is significantly improved under the CFL constraint.     

A wideband data link computer simulation model

This paper describes a computer simulation model capable of predicting the performance of a high data rate end-to-end communication system for biphase and quadriphase CPSK transmission. Simulation results are compared with laboratory measurements in order to verify the simulation procedure. Ultimately, the simulation model is utilized to conduct a parameter sensitivity analysis for the purpose of evaluating the effect of different signal distortion phenomena on link performance.     

智能家居示范工程中的家庭组网问题分析

如今,单纯的智能家居应用演示已无法对物联网产业的发展形成持续的推动力,加快智能家居示范工程建设势在必行。家庭组网是智能家居应用示范建设中的关键环节,为此,文中对应用示范工程中所采用的家庭组网技术从业务应用需求、家庭内部建筑结构等方面进行了分析研究,认为家庭组网不仅要从家庭组网技术本身来进行理论性分析,更要从示范工程的实际需求与后续运营维护升级的角度来考虑。     

A change detection model based on neighborhood correlation image analysis and decision tree classification

This study introduces a change detection model based on Neighborhood Correlation Image (NCI) logic. It is based on the fact that the same geographic area (e.g., a 3 × 3 pixel window) on two dates of imagery will tend to be highly correlated if little change has occurred, and uncorrelated when change occurs. Computing the piecewise correlation between two data sets provides valuable information regarding the location and numeric change value derived using contextual information within the specified neighborhood. Various neighborhood configurations (i.e., multi-level NCIs) were explored in the study using high spatial resolution multispectral imagery: smaller neighborhood sizes provided some detailed change information (such as a new patios added to an existing building) at the cost of introducing some noise (such as changes in shadows). Larger neighborhood sizes were useful for removing this noise but introduced some inaccurate change information (such as removing some linear feature changes). When combined with image classification using a machine learning decision tree (C5.0), classifications based on multi-level NCIs yielded superior results (e.g., using a 3-pixel circular radius neighborhood had a Kappa of 0.94), compared to the classification that did not incorporate NCIs (Kappa = 0.86).     

A word extraction algorithm for machine-printed documents using a 3D neighborhood graph model

Automatic character recognition and image understanding of a given paper document are the main objectives of the computer vision field. For these problems, a basic step is to isolate characters and group words from these isolated characters. In this paper, we propose a new method for extracting characters from a mixed text/graphic machine-printed document and an algorithm for distinguishing words from the isolated characters. For extracting characters, we exploit several features (size, elongation, and density) of characters and propose a characteristic value for classification using the run-length frequency of the image component. In the context of word grouping, previous works have largely been concerned with words which are placed on a horizontal or vertical line. Our word grouping algorithm can group words which are on inclined lines, intersecting lines, and even curved lines. To do this, we introduce the 3D neighborhood graph model which is very useful and efficient for character classification and word grouping. In the 3D neighborhood graph model, each connected component of a text image segment is mapped onto 3D space according to the area of the bounding box and positional information from the document. We conducted tests with more than 20 English documents and more than ten oriental documents scanned from books, brochures, and magazines. Experimental results show that more than 95% of words are successfully extracted from general documents, even in very complicated oriental documents. Received August 3, 2001 / Accepted August 8, 2001