Dynamic Bayesian networks provide a compact and natural representation for complex dynamic systems. However, in many cases, there is no ex­ pert available from whom a model can be elicited. Learning provides an alternative approach for constructing models of dynamic systems. In this paper, we address some of the crucial compu­ tational aspects of learning the structure of dy­ namic systems, par...

This paper presents the design of ZOMBIE, a dependently-typedprogramming language that uses an adaptation of a congruenceclosure algorithm for proof and type inference. This algorithm al-lows the type checker to automatically use equality assumptionsfrom the context when reasoning about equality. Most dependently-typed languages automatically use equalities that follow from ...

Determining the structure of the world and the motion of the observer from image changes has been a central problem in computer vision for over fteen years Since the early work on Structure from Motion SFM by Longuet Higgins and Pradzny several techniques have been developed to compute the motion of the camera the shape of moving objects or distances to points in the world However the image cha...

w e ppose a new algorithm for enhancing noisy speech which have been degraded by statistically independent additive noise. The al p rithm is based upon modeling the clean speech as a hidden Markov process with mixtures of Gaussian autoregressive (AR) output processes, and the noise process as a sequence of stationary, statistically independent, Gaussian AR vectors. The parameter sets of the mod...

this paper presents a genetic algorithm (ga) for solving a generalized model of single-item resource-constrained aggregate production planning (app) with linear cost functions. app belongs to a class of pro-duction planning problems in which there is a single production variable representing the total production of all products. we linearize a linear mixed-integer model of app subject to hiring...

In this paper, we introduce and study a mixed variational inclusion problem involving infinite family of fuzzy mappings. An iterative algorithm is constructed for solving a mixed variational inclusion problem involving infinite family of fuzzy mappings and the convergence of iterative sequences generated by the proposed algorithm is proved. Some illustrative examples are also given.

In this paper we extend our previous work on model variety analysis of a signal processing algorithm with respect to the class of all input signals that may po tentially arise in a given signal understanding appli cation This analysis has two related objectives The rst objective is to partition the set of all possible sig nals in the application domain into two sets according to whether each si...

Abstract A 62 year old man arrived in PS for typical chest pain radiating to the jugular and associated with sweating about three hours. History of arterial hypertension untreated dyslipidemia, family history CVD. ECG: sinus rithm at rate 50 bpm first degree AVB. Inferior ST elevation inferior leads depression V2–V3. Echocardiogram: depressed systolic function (EF 48%) relation hypo–akinesia mi...

Medical image processing involves using and examining 3D human body images, which are most frequently acquired through a computed tomography scanner, to diagnose disorders. process- ing helps radiologists, engineers, clinicians better comprehend the anatomy of specific patients or groups patients. Due recent advancements in deep learn techniques, study medical analysis is now quickly expanding ...

In this paper, we consider the collaborative data publishingproblem for anonymizing horizontally partitioned data atmultiple data providers. We consider a new type of “in-sider attack” by colluding data providers who may use theirown data records (a subset of the overall data) in addition tothe external background knowledge to infer the data recordscontributed by other d...