LED is an ultra-lightweight block cipher that is mainly used in devices with limited resources. Currently, the software and hardware structure of this cipher utilize a complex logic operation to generate a sequence of random numbers called round constant and this causes the algorithm to slow down and record low throughput. To improve the speed and throughput of the original algorithm, the Fast Lightweight Encryption Device (FLED) has been proposed in this paper. The key size of the currently existing LED algorithm is in 64-bit & 128-bit but this article focused mainly on the 64-bit key (block size=64-bit). In the proposed FLED design, complex operations have been replaced by LFSR left feedback technology to make the algorithm perform more e

The current research aims to find out (the effectiveness of teaching TRIZ theory in the expressive performance and the development of creative thinking among preparatory school students)
To achieve this, the researcher adopted on an experimental design is located in women with partial seizure experimental designs field in order to achieve the goals of the research, has sample consisted of two divisions seminars Mentzmtin in junior high school Diyala for Boys, and divided the sample of (60) called on the two groups, the first pilot of ( 30) student, and the other officer and number (30), student, and studied researchers experimental group theory TRIZ, while he studied the officer in the traditional manner, the researcher conducted a pa

Within the framework of big data, energy issues are highly significant. Despite the significance of energy, theoretical studies focusing primarily on the issue of energy within big data analytics in relation to computational intelligent algorithms are scarce. The purpose of this study is to explore the theoretical aspects of energy issues in big data analytics in relation to computational intelligent algorithms since this is critical in exploring the emperica aspects of big data. In this chapter, we present a theoretical study of energy issues related to applications of computational intelligent algorithms in big data analytics. This work highlights that big data analytics using computational intelligent algorithms generates a very high amo

Carbonate reservoirs are an essential source of hydrocarbons worldwide, and their petrophysical properties play a crucial role in hydrocarbon production. Carbonate reservoirs' most critical petrophysical properties are porosity, permeability, and water saturation. A tight reservoir refers to a reservoir with low porosity and permeability, which means it is difficult for fluids to move from one side to another. This study's primary goal is to evaluate reservoir properties and lithological identification of the SADI Formation in the Halfaya oil field. It is considered one of Iraq's most significant oilfields, 35 km south of Amarah. The Sadi formation consists of four units: A, B1, B2, and B3. Sadi A was excluded as it was not filled with h

In the presence of deep submicron noise, providing reliable and energy‐efficient network on‐chip operation is becoming a challenging objective. In this study, the authors propose a hybrid automatic repeat request (HARQ)‐based coding scheme that simultaneously reduces the crosstalk induced bus delay and provides multi‐bit error protection while achieving high‐energy savings. This is achieved by calculating two‐dimensional parities and duplicating all the bits, which provide single error correction and six errors detection. The error correction reduces the performance degradation caused by retransmissions, which when combined with voltage swing reduction, due to its high error detection, high‐energy savings are achieved. The res

Due to the exceedingly high integration density of VLSI circuits and the resulting high power density, thermal integrity became a major challenge. One way to tackle this problem is Dark silicon. Dark silicon is the amount of circuitry in a chip that is forced to switch off to insure thermal integrity of the system and prevent permanent thermal-related faults. In many-core systems, the presence of Dark Silicon adds new design constraints, in general, and on the communication fabric of such systems, in particular. This is due to the fact that system-level thermal-management systems tend to increase the distance between high activity cores to insure better thermal balancing and integrity. Consequently, a designing dilemma is created wh

Longitudinal data is becoming increasingly common, especially in the medical and economic fields, and various methods have been analyzed and developed to analyze this type of data.

In this research, the focus was on compiling and analyzing this data, as cluster analysis plays an important role in identifying and grouping co-expressed subfiles over time and employing them on the nonparametric smoothing cubic B-spline model, which is characterized by providing continuous first and second derivatives, resulting in a smoother curve with fewer abrupt changes in slope. It is also more flexible and can pick up on more complex patterns and fluctuations in the data.

The longitudinal balanced data profile was compiled into subgroup

The manufacturing industry in Iraq has faced, during the time stages, several obstacles that have had devastating effects on the Iraqi economy. These obstacles are represented by political events and wars that have led to the depletion of most human and material resources and the suspension of most vital industrial facilities from working, And the occurrence of this major deviation in the process of economic development, For the same reasons, the contributions of the manufacturing sector to the gross domestic product varied fluctuatingly, indicating instability in the growth rates of this sector, On the other hand, the supremacy of the belief that the dominance of oil resources as a main source for creating economic growth and achieving a h

In this research an Artificial Neural Network (ANN) technique was applied for the prediction of Ryznar Index (RI) of the flowing water from WTPs in Al-Karakh side (left side) in Baghdad city for year 2013. Three models (ANN1, ANN2 and ANN3) have been developed and tested using data from Baghdad Mayoralty (Amanat Baghdad) including drinking water quality for the period 2004 to 2013. The results indicate that it is quite possible to use an artificial neural networks in predicting the stability index (RI) with a good degree of accuracy. Where ANN 2 model could be used to predict RI for the effluents from Al-Karakh, Al-Qadisiya and Al-Karama WTPs as the highest correlation coefficient were obtained 92.4, 82.9 and 79.1% respectively. For