In this paper, a new method to model and simulate a wireless communication system based on System on Chip design methodology will be presented. The network performance effected by the amount of detail in the simulation model. Hence there is a need to develop suitable abstractions that maintain the accuracy of the simulation while keeping the computational resource requirements low. The integration of communication modelling into the design modelling has been shown by modelling a noisy communication channel in SystemC. The channel supports different modulation techniques such as, Amplitude-shift keying, Phase-shift keying, Quadrature amplitude modulation. It supports the setting of different Signal to noise ratio and different types of interference for Point-to-Point and Point-to-Multipoint platforms based on SystemC design methodology.
Brain tumors diagnosis in children is a scientific concern due to rapid anatomical, metabolic, and functional changes arising in the brain and non-specific or conflicting imaging results. Pediatric brain tumors diagnosis is typically centralized in clinical practice on the basis of diagnostic clues such as, child age, tumor location and incidence, clinical history, and imaging (Magnetic resonance imaging MRI / computed tomography CT) findings. The implementation of deep learning has rapidly propagated in almost every field in recent years, particularly in the medical images’ evaluation. This review would only address critical deep learning issues specific to pediatric brain tumor imaging research in view of the vast spectrum of other applications of deep learning. The purpose of this review paper is to include a detailed summary by first providing a succinct guide to the types of pediatric brain tumors and pediatric brain tumor imaging techniques. Then, we will present the research carried out by summarizing the scientific contributions to the field of pediatric brain tumor imaging processing and analysis. Finally, to establish open research issues and guidance for potential study in this emerging area, the medical and technical limitations of the deep learning-based approach were included.
This paper presents an RTL-level model of an 8B/10B encoder/decoder block in SystemC. The use of 8B/10B coding is an important technique in the construction of high performance serial interfaces. These are particularly suitable for alleviating the I/O bottleneck of state of the art systems (which are pinout, rather than bandwidth limited). SystemC has been chosen because it provides a homogeneous design flow for complex designs (i.e. SoC and IP based design), where system modeling at the early stages of the design becomes increasingly important.
Abstract:In modern distributed systems, replication receives particular attention for providing high data availability, fault tolerance and enhance the performance of the system. It is an important mechanism because it enables organizations to provide users with access to current data where and when they need it. However, this way of data organization introduces low data consistency and data coherency as more than one replicated copies need to be updated. Expensive synchronization mechanisms are needed to maintain the consistency and integrity of data among replicas when changes are made by the transactions. In this paper, we present Neighbor Replication on Grid (NRG) daemon in order to manage replication and transactions in distributed system. NRG Transaction Model has been implemented in order to preserve the data consistency and availability. Based on experiment and result, it shows that NRG daemon guarantees consistency and obey serializability through the synchronization approach.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.