Ensuring reliable data transmission in Network on Chip (NoC) is one of the most challenging tasks, especially in noisy environments. As crosstalk, interference, and radiation were increased with manufacturers' increasing tendency to reduce the area, increase the frequencies, and reduce the voltages. So many Error Control Codes (ECC) were proposed with different error detection and correction capacities and various degrees of complexity. Code with Crosstalk Avoidance and Error Correction (CCAEC) for network-on-chip interconnects uses simple parity check bits as the main technique to get high error correction capacity. Per this work, this coding scheme corrects up to 12 random errors, representing a high correction capacity compared with many other code schemes. This candidate has high correction capability but with a high codeword size. In this work, the CCAEC code is compared to another well-known code scheme called Horizontal-Vertical-Diagonal (HVD) error detecting and correcting code through reliability analysis by deriving a new accurate mathematical model for the probability of residual error Pres for both code schemes and confirming it by simulation results for both schemes. The results showed that the HVD code could correct all single, double, and triple errors and failed to correct only 3.3 % of states of quadric errors. In comparison, the CCAEC code can correct a single error and fails in 1.5%, 7.2%, and 16.4% cases of double, triple, and quadric errors, respectively. As a result, the HVD has better reliability than CCAEC and has lower overhead; making it a promising coding scheme to handle the reliability issues for NoC.
The present paper discusses one of the most important Russian linguistic features of Arabic origin Russian lexes denoting some religious worship or some political and social positions like Qadi, Wally, Sultan, Alam, Ruler, Caliph, Amir, Fakih, Mufti, Sharif, Ayatollah, Sheikh.. etc. A lexical analysis of the two of the most efficient and most used words of Arabic origin Russian lexes that are “Caliph and Sheikh” is considered in the present study. The lexicographic analysis of these words makes it possible to identify controversial issues related to their etymology and semantic development.
The study is conducted by the use of the modern Russian and Arabic dictionary, specifically, (Intermediate lexicon Dictionary
... Show MoreThe research aims to identify the extent to which Iraqi private banks practice profit management motivated by reducing the taxable base by increasing the provision for loan losses by relying on the LLP it model, which consists of a main independent variable (net profit before tax) and independent sub-variables (bank size, total debts to total equity, loans granted to total obligations) under the name of the variables governing the banking business. (Colmgrove-Smirnov) was used to test the normal distribution of data for all banks during the period 2017-2020, and then find the correlation between the main independent variable sub and the dependent variable by means of the correlation coefficient person, and then using the multiple
... Show MoreArab translators have always paid great attention to the translation of the Persian literary genres, in particular, contemporary Iranian novels. They have always translated for the most prominent Iranian novelists such as Jalal Al Ahmad, Sadiq Hidayat, Mahmoud Dowlatabadi, Bozorg Alavi, Ismail Fasih, Houshang Golshiri, Gholam-Hossein Saedi, Simin Daneshvar, Sadiq Chubak, Samad Behrangi and others that have succeeded in perfectly picturing the Iranian society.
Within the perspectives of Arab translators and by using the descriptive - analytical approach, the present study provides an analytical study of the translation into Arabic some of the modern Persian novels. Moreove
... Show MoreThis study is dedicated to solving multicollinearity problem for the general linear model by using Ridge regression method. The basic formulation of this method and suggested forms for Ridge parameter is applied to the Gross Domestic Product data in Iraq. This data has normal distribution. The best linear regression model is obtained after solving multicollinearity problem with the suggesting of 10 k value.
The current work concerns preparing cobalt manganese ferrite (Co0.2Mn0.8Fe2O4) and decorating it with polyaniline (PAni) for supercapacitor applications. The X-ray diffraction findings (XRD) manifested a broad peak of PAni and a cubic structure of cobalt manganese ferrite with crystal sizes between 21 nm. The pictures were taken with a field emission scanning electron microscope (FE-SEM), which evidenced that the PAni has nanofibers (NFs) structures, grain size 33 – 55 nm, according to the method of preparation, where the hydrothermal method was used. The magnetic measurements (VSM) that were conducted at room temperature showed that the samples had definite magnetic properties. Additionally, it was noted that the saturation magnetizatio
... Show MoreSuperconducting compound Bi2Sr2-xYxCa2Cu3O10+δ were Synthesized by method of solid state reaction, at 1033 K for 160 hours temperature of the sintering at normal atmospheric pressure where substitutions Yttrium oxide with Strontium. When Y2O3 concentration (0.0, 0.1, 0.2, 0.3, 0.4 and 0.5). All specimens of Bi2Sr2Ca2Cu3O10+δ superconducting compounds were examined. The resistivity of electrical was checked by the four point probe technique, It was found th
six specimens of the Hg0.5Pb0.5Ba2Ca2Cu3-y
In this paper, integrated quantum neural network (QNN), which is a class of feedforward
neural networks (FFNN’s), is performed through emerging quantum computing (QC) with artificial neural network(ANN) classifier. It is used in data classification technique, and here iris flower data is used as a classification signals. For this purpose independent component analysis (ICA) is used as a feature extraction technique after normalization of these signals, the architecture of (QNN’s) has inherently built in fuzzy, hidden units of these networks (QNN’s) to develop quantized representations of sample information provided by the training data set in various graded levels of certainty. Experimental results presented here show that
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