The presence of different noise sources and continuous increase in crosstalk in the deep submicrometer technology raised concerns for on-chip communication reliability, leading to the incorporation of crosstalk avoidance techniques in error control coding schemes. This brief proposes joint crosstalk avoidance with adaptive error control scheme to reduce the power consumption by providing appropriate communication resiliency based on runtime noise level. By switching between shielding and duplication as the crosstalk avoidance technique and between hybrid automatic repeat request and forward error correction as the error control policies, three modes of error resiliencies are provided. The results show that, in reduced mode, the scheme achie

The penalized least square method is a popular method to deal with high dimensional data ,where  the number of explanatory variables is large than the sample size . The properties of  penalized least square method are given high prediction accuracy and making estimation and variables selection

 At once. The penalized least square method gives a sparse model ,that meaning a model with small variables so that can be interpreted easily .The penalized least square is not robust ,that means very sensitive to the presence of outlying observation , to deal with this problem, we can used a robust loss function to get the robust penalized least square method ,and get robust penalized estimator and

Many image processing and machine learning applications require sufficient image feature selection and representation. This can be achieved by imitating human ability to process visual information. One such ability is that human eyes are much more sensitive to changes in the intensity (luminance) than the color information. In this paper, we present how to exploit luminance information, organized in a pyramid structure, to transfer properties between two images. Two applications are presented to demonstrate the results of using luminance channel in the similarity metric of two images. These are image generation; where a target image is to be generated from a source one, and image colorization; where color information is to be browsed from o

This work focused on principle of higher order mode excitation using in- line Double Clad Multi-Mode Mach-Zehnder Interferometer (DC-MM-MZI). The DC-MM-MZI was designed with 50 cm etched MMF. The etching length is 5cm. The tenability of this interferometer was studied using opt grating ver.4.2.2 and optiwave
ver. 7 simulator. After removing (25, 35, 45, 55) μm from MMF and immersing this segment of MMF with water bath contained distilled water and ethanol, in addition to, air. Pulsed laser source  centered at 1546.7nm ,pulse width 10ns and peak power 1.33mW was propagated via this interferometer Maximum modes were obtained in case of air surrounded media which are 9800 and 25 um removed cladding layer, with peak power 49.800 m

The study aims to use the European Excellence Model (EFQM) in assessing the institutional performance of the National Center for Administrative Development and Information Technology in order to determine the gap between the actual reality of the performance of the Center and the standards adopted in the model, in order to know the extent to which the Center seeks to achieve excellence in performance to improve the level of services provided and the adoption of methods Modern and contemporary management in the evaluation of its institutional performance.

The problem of the study was the absence of an institutional performance evaluation system at the centre whereby weaknesses (areas of improvement) and st

The current research involves psychological pressure (educational,environment andemotionly) for secondary level to 2013-2014.This research includes comparison among students who are trained and not trained  in physical education .The sample is(126) students from each gender from first education.Al-Karkh and the research found out that physical education  has an effect in lessing emotional and educational in a big degree in student in secondary  which affect them  positively in their  study.                                     &n

Big data analysis is essential for modern applications in areas such as healthcare, assistive technology, intelligent transportation, environment and climate monitoring. Traditional algorithms in data mining and machine learning do not scale well with data size. Mining and learning from big data need time and memory efficient techniques, albeit the cost of possible loss in accuracy. We have developed a data aggregation structure to summarize data with large number of instances and data generated from multiple data sources. Data are aggregated at multiple resolutions and resolution provides a trade-off between efficiency and accuracy. The structure is built once, updated incrementally, and serves as a common data input for multiple mining an

With the proliferation of both Internet access and data traffic, recent breaches have brought into sharp focus the need for Network Intrusion Detection Systems (NIDS) to protect networks from more complex cyberattacks. To differentiate between normal network processes and possible attacks, Intrusion Detection Systems (IDS) often employ pattern recognition and data mining techniques. Network and host system intrusions, assaults, and policy violations can be automatically detected and classified by an Intrusion Detection System (IDS). Using Python Scikit-Learn the results of this study show that Machine Learning (ML) techniques like Decision Tree (DT), Naïve Bayes (NB), and K-Nearest Neighbor (KNN) can enhance the effectiveness of an Intrusi