Enhanced moments of Eu in single crystals of the metallic helical antiferromagnet EuCo2 yAs2

The compound EuCo{2-y}As2 with the tetragonal ThCr2Si2 structure is known to contain Eu{+2} ions with spin S = 7/2 that order below a temperature TN = 47 K into an antiferromagnetic (AFM) proper helical structure with the ordered moments aligned in the tetragonal ab plane, perpendicular to the helix axis along the c axis, with no contribution from the Co atoms. Here we carry out a detailed investigation of the properties of single crystals. Enhanced ordered and effective moments of the Eu spins are found in most of our crystals. Electronic structure calculations indicate that the enhanced moments arise from polarization of the d bands, as occurs in ferromagnetic Gd metal. Electrical resistivity measurements indicate metallic behavior. The low-field in-plane magnetic susceptibilities chi{ab}(T < TN) for several crystals are reported that are fitted well by unified molecular field theory (MFT), and the Eu-Eu exchange interactions Jij are extracted from the fits. High-field magnetization M data for magnetic fields H||ab reveal what appears to be a first-order spin-flop transition followed at higher field by a second-order metamagnetic transition of unknown origin, and then by another second-order transition to the paramagnetic (PM) state. For H||c, the magnetization shows only a second-order transition from the canted AFM to the PM state, as expected. The critical fields for the AFM to PM transition are in approximate agreement with the predictions of MFT. Heat capacity Cp measurements in zero and high H are reported. Phase diagrams for H||c and H||ab versus T are constructed from the high-field M(H,T) and Cp(H,T) measurements. The magnetic part Cmag(T, H = 0) of Cp(T, H = 0) is extracted and is fitted rather well below TN by MFT, although dynamic short-range AFM order is apparent in Cmag(T) up to about 70 K, where the molar entropy attains its high-T limit of R ln8.Comment: 29 pages, 30 figures including 62 subfigures, 8 tables, 84 reference

Implementation of Deduplication on Encrypted Big-data using Signcryption for cloud storage applications

As Big Data Cloud storage servers are getting widespread the shortage of disc space within the cloud becomes a major concern. The elimination of duplicate or redundant data, particularly in computer data is named deduplication. Data deduplication is a method to regulate the explosive growth of information within the cloud storage, most of the storage providers are finding more secure and efficient methods for their sensitive method. Recently, a noteworthy technique referred to as signcryption has been proposed, in which both the properties of signature (ownership) and encryption are simultaneously implemented with better performance According to deduplication, we introduce a method that can eliminate redundant encrypted data owned by different users. Furthermore, we generate a tag which will be the key component of big data management. We propose a technique called digital signature for ownership verification. Convergent encryption also called for a content hash key cryptosystem. Convergent encryption is an encryption approach that supports deduplication. With this encryption technique, the encryption key is generated out of a hash of plain text. Therefore applying this technique, identical plaintexts would turn out the same ciphertext

Implementation of Deduplication on Encrypted Big-data using Signcryption for cloud storage applications

As Big Data Cloud storage servers are getting widespread the shortage of disc space within the cloud becomes a major concern. The elimination of duplicate or redundant data, particularly in computer data is named deduplication. Data deduplication is a method to regulate the explosive growth of information within the cloud storage, most of the storage providers are finding more secure and efficient methods for their sensitive method. Recently, a noteworthy technique referred to as signcryption has been proposed, in which both the properties of signature (ownership) and encryption are simultaneously implemented with better performance According to deduplication, we introduce a method that can eliminate redundant encrypted data owned by different users. Furthermore, we generate a tag which will be the key component of big data management. We propose a technique called digital signature for ownership verification. Convergent encryption also called for a content hash key cryptosystem. Convergent encryption is an encryption approach that supports deduplication. With this encryption technique, the encryption key is generated out of a hash of plain text. Therefore applying this technique, identical plaintexts would turn out the same ciphertext

Bipolar Neutrosophic Convolutional Neural Networks For Child Malnutrition Prediction Through Neutrosophic Set Domain.

Specifically, epistemic uncertainty, which reflects the model's lack of knowledge about the data, is the sort of uncertainty that has a significant impact on the performance of deep learning models employed for malnutrition prediction. The uncertainty in malnutrition dataset must be successfully resolved by enhancing deep learning architecture. To solve the issue of uncertainty information’s in malnutrition, Bipolar Neutrosophic Convolutional Neural Networks (BNCNN) is developed for extracting different deep features to generate predictive uncertainty estimates.&nbsp; A bipolar neutrosophic set is characterized by the positive-membership degree, where is a truth-membership function, indeterminacy-membership function, and falsity-membership function, and the negative-membership degree, where is a truth-membership function, indeterminacy-membership function, and falsity-membership function. Compared to Convolutional Neural Networks, the Bipolar neutrosophic is produced more accuracy results