Nearest Neighbor Synthesis of CNOT Circuit Based on Matrix Transformation

Author(s):  
Xueyun Cheng ◽  
Mingqiang Zhu ◽  
Xiang Li ◽  
Zhijin Guan
Author(s):  
J. M. Oblak ◽  
W. H. Rand

The energy of an a/2 <110> shear antiphase. boundary in the Ll2 expected to be at a minimum on {100} cube planes because here strue ture is there is no violation of nearest-neighbor order. The latter however does involve the disruption of second nearest neighbors. It has been suggested that cross slip of paired a/2 <110> dislocations from octahedral onto cube planes is an important dislocation trapping mechanism in Ni3Al; furthermore, slip traces consistent with cube slip are observed above 920°K.Due to the high energy of the {111} antiphase boundary (> 200 mJ/m2), paired a/2 <110> dislocations are tightly constricted on the octahedral plane and cannot be individually resolved.


Author(s):  
S. R. Herd ◽  
P. Chaudhari

Electron diffraction and direct transmission have been used extensively to study the local atomic arrangement in amorphous solids and in particular Ge. Nearest neighbor distances had been calculated from E.D. profiles and the results have been interpreted in terms of the microcrystalline or the random network models. Direct transmission electron microscopy appears the most direct and accurate method to resolve this issue since the spacial resolution of the better instruments are of the order of 3Å. In particular the tilted beam interference method is used regularly to show fringes corresponding to 1.5 to 3Å lattice planes in crystals as resolution tests.


Author(s):  
M. Jeyanthi ◽  
C. Velayutham

In Science and Technology Development BCI plays a vital role in the field of Research. Classification is a data mining technique used to predict group membership for data instances. Analyses of BCI data are challenging because feature extraction and classification of these data are more difficult as compared with those applied to raw data. In this paper, We extracted features using statistical Haralick features from the raw EEG data . Then the features are Normalized, Binning is used to improve the accuracy of the predictive models by reducing noise and eliminate some irrelevant attributes and then the classification is performed using different classification techniques such as Naïve Bayes, k-nearest neighbor classifier, SVM classifier using BCI dataset. Finally we propose the SVM classification algorithm for the BCI data set.


2020 ◽  
Vol 17 (1) ◽  
pp. 319-328
Author(s):  
Ade Muchlis Maulana Anwar ◽  
Prihastuti Harsani ◽  
Aries Maesya

Population Data is individual data or aggregate data that is structured as a result of Population Registration and Civil Registration activities. Birth Certificate is a Civil Registration Deed as a result of recording the birth event of a baby whose birth is reported to be registered on the Family Card and given a Population Identification Number (NIK) as a basis for obtaining other community services. From the total number of integrated birth certificate reporting for the 2018 Population Administration Information System (SIAK) totaling 570,637 there were 503,946 reported late and only 66,691 were reported publicly. Clustering is a method used to classify data that is similar to others in one group or similar data to other groups. K-Nearest Neighbor is a method for classifying objects based on learning data that is the closest distance to the test data. k-means is a method used to divide a number of objects into groups based on existing categories by looking at the midpoint. In data mining preprocesses, data is cleaned by filling in the blank data with the most dominating data, and selecting attributes using the information gain method. Based on the k-nearest neighbor method to predict delays in reporting and the k-means method to classify priority areas of service with 10,000 birth certificate data on birth certificates in 2019 that have good enough performance to produce predictions with an accuracy of 74.00% and with K = 2 on k-means produces a index davies bouldin of 1,179.


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