Deep submicron technologies continue to develop according to Moore’s law allowing hundreds of processing elements and memory modules to be integrated on a single chip forming multi/many-processor systems-on-chip (MPSoCs). Network on chip (NoC) arose as an interconnection for this large number of processing modules. However, the aggressive scaling of transistors makes NoC more vulnerable to both permanent and transient faults. Permanent faults persistently affect the circuit functionality from the time of their occurrence. The router represents the heart of the NoC. Thus, this research focuses on tolerating permanent faults in the router’s input buffer component, particularly the virtual channel state fields. These fields track packets from the moment they enter the input component until they leave to the next router. The hardware redundancy approach is used to tolerate the faults in these fields due to their crucial role in managing the router operation. A built-in self-test logic is integrated into the input port to periodically detect permanent faults without interrupting router operation. These approaches make the NoC router more reliable than the unprotected NoC router with a maximum of 17% and 16% area and power overheads, respectively. In addition, the hardware redundancy approach preserves the network performance in the presence of a single fault by avoiding the virtual channel closure.
Abstract
The aim of the current research is to identify the effect of the effective reading strategy on the achievement of second-middle students in biology, as well as the imaginative thinking skills of students. The researcher adopted the experimental design with partial control to achieve the goal of the research. The current research community identified the second-middle students in the government schools of the Baghdad Education Directorate / Rusafa I for the academic year (2021-2022 AD). The Safina Intermediate School for Girls was chosen to be the research sample in the form of intentionally, two classes were randomly selected from a total of four classes, one of them is experimental and the other is con
... Show MoreThe energy density state are the powerful factor for evaluate the validity of a material in any application. This research focused on examining the electrical properties of the Se6Te4- xSbx glass semiconductor with x=1, 2 and 3, using the thermal evaporation technique. D.C electrical conductivity was used by determine the current, voltage and temperatures, where the electrical conductivity was studied as a function of temperature and the mechanical electrical conduction were determined in the different conduction regions (the extended and localized area and at the Fermi level). In addition, the density of the energy states in these regions is calculated using the mathematical equations. The constants of energy density states are det
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تتناول هذه الورقة مخططات وسياسات الاستيطان في الضفة الغربية والقدس الشرقية منذ العام 1967، عبر سياسات قادها حزب العمل وأكملها حزب الليكود وكاديما وبقية الأحزاب الإسرائيلية، تلك السياسات التي استهدفت فرض السيطرة السياسية الكاملة على الأرض، وما نتج عن ذلك من سيطرة حصرية على الأرضوتقييد استخداماتها، ومحاصرة الوجود الفلسطيني والتضييق عليه، وتحويل مراكز ال
... Show MoreThe traditional centralized network management approach presents severe efficiency and scalability limitations in large scale networks. The process of data collection and analysis typically involves huge transfers of management data to the manager which cause considerable network throughput and bottlenecks at the manager side. All these problems processed using the Agent technology as a solution to distribute the management functionality over the network elements. The proposed system consists of the server agent that is working together with clients agents to monitor the logging (off, on) of the clients computers and which user is working on it. file system watcher mechanism is used to indicate any change in files. The results were presente
... Show MoreIn this research Artificial Neural Network (ANN) technique was applied to study the filtration process in water treatment. Eight models have been developed and tested using data from a pilot filtration plant, working under different process design criteria; influent turbidity, bed depth, grain size, filtration rate and running time (length of the filtration run), recording effluent turbidity and head losses. The ANN models were constructed for the prediction of different performance criteria in the filtration process: effluent turbidity, head losses and running time. The results indicate that it is quite possible to use artificial neural networks in predicting effluent turbidity, head losses and running time in the filtration process, wi
... Show MoreImage Fusion Using A Convolutional Neural Network
This paper explores VANET topics: architecture, characteristics, security, routing protocols, applications, simulators, and 5G integration. We update, edit, and summarize some of the published data as we analyze each notion. For ease of comprehension and clarity, we give part of the data as tables and figures. This survey also raises issues for potential future research topics, such as how to integrate VANET with a 5G cellular network and how to use trust mechanisms to enhance security, scalability, effectiveness, and other VANET features and services. In short, this review may aid academics and developers in choosing the key VANET characteristics for their objectives in a single document.
With the continuous progress of image retrieval technology, the speed of searching for the required image from a large amount of image data has become an important issue. Convolutional neural networks (CNNs) have been used in image retrieval. However, many image retrieval systems based on CNNs have poor ability to express image features. Content-based Image Retrieval (CBIR) is a method of finding desired images from image databases. However, CBIR suffers from lower accuracy in retrieving images from large-scale image databases. In this paper, the proposed system is an improvement of the convolutional neural network for greater accuracy and a machine learning tool that can be used for automatic image retrieval. It includes two phases
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