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This article introduces a new, low cost and complexity, wideband Ku/K‐band combined low‐noise amplifier (LNA) Filter designed for large satellite phased array systems in advanced 22 nm Fully Depleted Silicon on Insulator Technology. The LNA achieves the required 20 dB gain through a two‐stage configuration using the cascode configuration. To effectively reject the transmitter (TX) signal, the LNA integrates 4 distributed parallel LC notch filters. Measured IP1dB at 29 GHz (TX band) demonstrates a 25 dB increase compared to IP1dB at 19 GHz (RX Band), with a remarkable 15 dB enhancement over the LNA without the filter. The 1‐dB gain bandwidth spans from 16 to 21 GHz, representing a 27% fractional bandwidth. Over the entire bandwidth, input/output return losses exceed 10 dB, maintaining a low noise figure (NF) of less than 3.5 dB. Inclusion of two filters at the input and middle of the first stage results in approximately 0.6 dB of increase in NF when compared to the LNA without the filter. [ABSTRACT FROM AUTHOR]

Metacognitive reading strategy awareness plays a significant role in reading comprehension and educational process. In spite of its importance, metacognitive strategy has long been the ignored skill in English language teaching, research, learning, and assessment. This lack of good metacognitive reading strategy skill is exacerbated by the central role of reading comprehension in education success. One solution to the problem of poor reading comprehension is the learning of metacognitive reading strategy skills. Metacognitive reading strategy ability needs to be focused in language learning and teaching. The present study is an attempt to find out whether "meta-cognitive reading strategy awareness" enhances EFL students' reading comprehension. Furthermore, it attempts to detect the relationship between metacognitive reading strategy awareness and reading comprehension. This paper focuses on the four main issues. First, it discusses the definition of metacognitive reading strategy, the significance of metacognitive reading strategy. Second, it reviews the process of metacognitive reading strategy. Third, definition of reading comprehension and different models of reading comprehension are reviewed. Fourth, the relationship between metacognitive reading strategy and reading comprehension will be discussed. Findings based on the review of the literature along with analysis of the data are of great significance and can be advantageous to improve EFL learners' metacognitive reading comprehension skill. Metacognitive reading comprehension skill has a positive effect on learning a second language and learners can gain the skills they need for effective communication in English.

In many English language classrooms, teaching pronunciation is granted the least attention. When ESL teachers defend the poor pronunciation skills of their students, their arguments could either be described as a cop-out with respect to their inability to teach their students proper pronunciation or they could be regarded as taking a stand against linguistic influence. If we learn a second language in childhood, we learn to speak it fluently and without a "foreign accent"; if we learn in adulthood, it is very unlikely that we will attain a native accent. In this study, the researchers first review misconceptions about pronunciation, factors affecting the learning of pronunciation. Then, the needs of learners and suggestions for teaching pronunciation will be reviewed. Pronunciation has a positive effect on learning a second language and learners can gain the skills they need for effective communication in English.

MapReduce algorithm inspired by the map and reduces functions commonly used in functional programming. The use of this model is more beneficial when optimization of the distributed mappers in the MapReduce framework comes into the account. In standard mappers, each mapper operates independently and has no collaborative function or content relationship with other mappers. We propose a new technique to improve performance of the interprocessing tasks in MapReduce functions. In the proposed method, the mappers are connected and collaborated through a shared coordinator with a distributed metadata store called DMDS. In this new structure, a parallel and coevolutionary genetic algorithm has been used to optimize and match the matrix processes simultaneously. The proposed method uses a genetic algorithm with a parallel and evolutionary executive structure in the mapping process of the mappers program to allocate resources, transfer and store data. The co-evolutionary MapReduce mappers can simplify and optimize relational data processing in the large clusters. MapReduce using a co-evolutionary mapper, provide successful convergence and better performance. Our experimental evaluation shows that collaborative techniques improves performance especially in the big size computations, and dramatically improves processing time across the MapReduce process. Even though the execution time in MapReduce varies with data volume, in the proposed method the overhead processing in low volume data is considerable where in high volume data shows more competitive advantage. In fact, with increasing the data volume, advantage of the proposed method becomes more considerable. [ABSTRACT FROM AUTHOR]