System Verilog Assertions (SVA) is widely used by hardware designers and verification engineers to apply Assertion Based Verification (ABV) methodology on their hardware designs. However, the complexity in understanding different protocol standards in general and JEDEC memory protocol standards in specific imposes numerous difficulties on designers and verification engineers when translating design specifications into SVA. This motivated us to devise new techniques that can be used to automatically generate SVA for DDR memory protocols with no ambiguity when capturing design requirements from

Purpose: Tagged and cine magnetic resonance imaging (tMRI and cMRI) techniques are used for evaluating regional and global heart function, respectively. Measuring global function parameters directly from tMRI is challenging due to the obstruction of the anatomical structure by the tagging pattern. The purpose of this study was to develop a method for processing the tMRI images to improve the myocardium-blood contrast in order to estimate global function parameters from the processed images. Materials and methods: The developed method consists of two stages: (1) removing the tagging pattern

The aim of this paper is to develop a functional approach to optimize the engagement effectiveness of the tactical homing missiles and air defense systems by utilizing the differential geometric concepts. In this paper the engagement geometry of the interceptor and the target is developed and expressed in differential geometric terms in order to demonstrate the possibilities of the impact triangles and specify the earliest interception based on the direct intercept geometry. Optimizing the missile heading angle and suitable missile velocity against the target velocity is then examined to

Abstract: Based on statistical thermal approaches, the transverse momentum distribution of the well-identified produced particles, π+, π–, K+, K–, p, and (Fromula presented.), is studied. We aim at introducing a novel almost entirely empirical estimation for the inclusive chemical potential μ. From the partition function of a grand-canonical ensemble, we propose a generic expression for the dependence of μ on the rapidity y. Then, by fitting this expression with the experimental results of the most central p⊥ and d2N/2πp⊥dp⊥dy, at 7.7, 11.5, 19.6, 27, 39, 130, 200 GeV, we introduce a generic

The proposed correspondence between the Hawking-Unruh radiation mechanism in rotating, electrically-charged, and electrically-charged-rotating black holes and the hadronization process in high-energy collisions is assumed here. This allows us to determine the well-profound freezeout parameters characterizing the heavy-ion collisions. Furthermore, black holes thermodynamics is found analogous to a to that of the high-energy collisions. We also introduce a relation expressing the dependence of the angular momentum and the angular velocity deduced from rotating black holes on the chemical

Background: Lung cancer is a leading cause of cancer-related death worldwide and is the most commonly diagnosed cancer. Like other cancers, it is a complex and highly heterogeneous disease involving multiple signaling pathways. Identifying potential therapeutic targets is critical for the development of effective treatment strategies. Methods: We used a systems biology approach to identify potential key regulatory factors in smoking-induced lung cancer. We first identified genes that were differentially expressed between smokers with normal lungs and those with cancerous lungs, then integrated

In the era of digital transformation, a mass disruption in the global industries have been detected. Big data, the Internet of Things (IoT) and Artificial Intelligence (AI) are just examples of technologies that are holding such digital disruptive power. On the other hand, retailing is a high-intensity competition and disruptive industry driving the global economy and the second largest globally in employment after the agriculture. AI has large potential to contribute to global economic activity and the biggest sector gains would be in retail. AI is the engine that is poised to drive the

Purpose - The purpose of this paper is to present a dynamic model to measure the degree of system's leanness under dynamic demand conditions using a novel integrated metric. Design/methodology/approach - The multi-stage production system model is based on a system dynamics approach. The leanness level is measured using a new developed integrated metric that combines efficiency,WIP performance as well as service level. The analysis includes design of experiment technique at the initial analysis to examine the most significant parameters impacting the leanness score and then followed by

In the field of pattern recognition multiple classifier systems based on the combination of outputs from different classifiers have been proposed as a method of high performance classification systems. The objective of this work is to develop a fuzzy Gaussian classifier for combining multiple learners, we use a fuzzy Gaussian model to combine the outputs obtained from K-nearest neighbor classifier (KNN), Fuzzy K-nearest neighbor classifier and Multi-layer Perceptron (MLP) and then compare the results with Fuzzy Integral, Decision Templates, Weighted Majority, Majority Naïve Bayes, Maximum

Numerous commercial tools like Xamarin, React Native and PhoneGap utilize the concept of cross-platform mobile applications development that builds applications once and runs it everywhere opposed to native mobile app development that writes in a specific programming language for every platform. These commercial tools are not very efficient for native developers as mobile applications must be written in specific language and they need the usage of specific frameworks. In this paper, a suggested approach in TCAIOSC tool to convert mobile applications from Android to iOS is used to develop the