Abstract 

For sparse system identification,recent suggested algorithms are  -norm Least Mean Square (  -LMS), Zero-Attracting LMS (ZA-LMS), Reweighted Zero-Attracting LMS (RZA-LMS), and p-norm LMS (p-LMS) algorithms, that have modified the cost function of the conventional LMS algorithm by adding a constraint of coefficients sparsity. And so, the proposed algorithms are named  -ZA-LMS, 

In aspect-based sentiment analysis ABSA, implicit aspects extraction is a fine-grained task aim for extracting the hidden aspect in the in-context meaning of the online reviews. Previous methods have shown that handcrafted rules interpolated in neural network architecture are a promising method for this task. In this work, we reduced the needs for the crafted rules that wastefully must be articulated for the new training domains or text data, instead proposing a new architecture relied on the multi-label neural learning. The key idea is to attain the semantic regularities of the explicit and implicit aspects using vectors of word embeddings and interpolate that as a front layer in the Bidirectional Long Short-Term Memory Bi-LSTM. First, we

The concept of rehabilitation provided an essential richness in the conservation philosophy through sustaining buildings life and adapting them to the contemporary use through a vision which looks at the present and future . In Iraq , the existence of historical buildings and the traditional fabric in the cities required the urban development which enhanced the interests of planning and architectural fields especially the building rehabilitation which requires the architectural intervention , and all that led to elaborate the problem of research which is " The confusion in the concepts of monumental, historical and traditional buildings in Iraq, As well as The insufficient knowledge about rehabilitation and the acts related to it through

Abstract

The aim of this research is to identify the general level of teachers’ curriculum expectations in (geography subject as a model), as well as the significance of the difference in the level of teachers’ curriculum expectations in light of the gender variables (male, female), the years of service (10 years or less - more than 10 years), the level of attitudes of fourth-grade literary students towards geography, the level of congruence between teachers’ curriculum expectations and the attitudes of fourth-grade literary students towards geography in light of the variables, the general level of congruence and the level of congruence between teachers’ curriculum expectations and the attitudes of studen

By driven the moment estimator of ARMA (1, 1) and by using the simulation some important notice are founded, From the more notice conclusions that the relation between the sign   and moment estimator for ARMA (1, 1) model that is: when the sign is positive means the root      gives invertible model and when the sign is negative means the root      gives invertible model. An alternative method has been suggested for ARMA (0, 1) model can be suitable when

The theory of probabilistic programming  may be conceived in several different ways. As a method of programming it analyses the implications of probabilistic variations in the parameter space of linear or nonlinear programming model. The generating mechanism of such probabilistic variations in the economic models may be due to incomplete information about changes in demand, pro­duction and technology, specification errors about the econometric relations presumed for different economic agents, uncertainty of various sorts and the consequences of imperfect aggregation or disaggregating of economic variables. In this Research we discuss the probabilistic programming problem when the coefficient b_i is random variable

     Binary relations or interactions among bio-entities, such as proteins, set up the essential part of any living biological system. Protein-protein interactions are usually structured in a graph data structure called "protein-protein interaction networks" (PPINs). Analysis of PPINs into complexes tries to lay out the significant knowledge needed to answer many unresolved questions, including how cells are organized and how proteins work. However, complex detection problems fall under the category of non-deterministic polynomial-time hard (NP-Hard) problems due to their computational complexity. To accommodate such combinatorial explosions, evolutionary algorithms (EAs) are proven effective alternatives to heuristics in solvin

Many approaches of different complexity already exist to edge detection in
color images. Nevertheless, the question remains of how different are the results
when employing computational costly techniques instead of simple ones. This
paper presents a comparative study on two approaches to color edge detection to
reduce noise in image. The approaches are based on the Sobel operator and the
Laplace operator. Furthermore, an efficient algorithm for implementing the two
operators is presented. The operators have been applied to real images. The results
are presented in this paper. It is shown that the quality of the results increases by
using second derivative operator (Laplace operator). And noise reduced in a good