Modeling of Ignition and Combustion of a Coflowing Hydrogen Jet in a Supersonic Air Flow

Combustion, Explosion, and Shock Waves - Results of a numerical study of mixing, ignition, and combustion of a cold hydrogen jet propagating along the lower wall of a channel parallel to a...     

Deep transfer modeling for classification of Maize Plant Leaf Disease

Multimedia Tools and Applications - Currently, Deep Learning is playing an influential role for Image analysis and object classification. Maize’s diseases reduce production that subsequently...     

VLC Enabled Hybrid Wireless Network for B5G/6G Communications

Wireless Personal Communications - In the present scenario, there is a boom in the demand of the users to achieve increased capacity, high data, low latency, and high-performance rates. 5G New...     

A privacy-preserving model based on differential approach for sensitive data in cloud environment

A large amount of data and applications need to be shared with various parties and stakeholders in the cloud environment for storage, computation, and data utilization. Since a third party operates the cloud platform, owners cannot fully trust this environment. However, it has become a challenge to ensure privacy preservation when sharing data effectively among different parties. This paper proposes a novel model that partitions data into sensitive and non-sensitive parts, injects the noise into sensitive data, and performs classification tasks using k-anonymization, differential privacy, and machine learning approaches. It allows multiple owners to share their data in the cloud environment for various purposes. The model specifies communication protocol among involved multiple untrusted parties to process owners’ data. The proposed model preserves actual data by providing a robust mechanism. The experiments are performed over Heart Disease, Arrhythmia, Hepatitis, Indian-liver-patient, and Framingham datasets for Support Vector Machine, K-Nearest Neighbor, Random Forest, Naive Bayes, and Artificial Neural Network classifiers to compute the efficiency in terms of accuracy, precision, recall, and F1-score of the proposed model. The achieved results provide high accuracy, precision, recall, and F1-score up to 93.75%, 94.11%, 100%, and 87.99% and improvement up to 16%, 29%, 12%, and 11%, respectively, compared to previous works.

     

Three dimensional reconstruction of brain tumor along with space occupying in lesions

Multimedia Tools and Applications - The three-dimensional models of brain tumors serve as diagnostic assistance for physicians, surgeons, and radiologists. The proposed system establishes an...     

A Broadband Dual Circularly Polarized Compact Printed Monopole Antenna

Wireless Personal Communications - Now-a-days the most common pretentious disease is the lung cancer, which has become more prevalent in the world that primarily infects the pulmonary nodules of...     

Analysis of energy saving in user equipment in LTE-A using stochastic modelling

Telecommunication Systems - Energy saving in User Equipment (UE) is one of the important issues for limited sources of power in the device. It is critical for the UE to maximize its energy...     

On the Growth of Thin-Film AlGaN/GaN Epitaxial Heterostructures on Hybrid Substrates Containing Layers of Silicon Carbide and Porous Silicon

Semiconductors - Abstract—In our work, we carry out a structural-spectroscopic study of AlGaN/GaN epitaxial layers grown by molecular-beam epitaxy with nitrogen-plasma activation on a hybrid...     

Modern Photodetector IR-Modules

Journal of Communications Technology and Electronics - In recent years, there has been a rapid improvement in photonics products due to the use of multilayer heterostructures grown on the basis of...     

An Adaptive Transmission Mode Selection Scheme for Cellular Underlaid D2D Communication

In this paper, we propose to use Artificial Bee Colony (ABC) optimization to solve the joint mode selection, channel assignment, and power allocation (JMSCPA) problem to maximize system throughput and spectral efficiency. JMSCPA is a problem where the allocation of channel and power depends on the mode selection. Such problems require two step solution and are called bi-level optimization problems. As bi-level optimization increases the complexity and computational time, we propose a modified version of single-level ABC algorithm aided with the adaptive transmission mode selection algorithm to allocate the cellular, reuse, and dedicated modes to the DUs along with channel and power allocation based on the network traffic load scenarios. A single variable, represented by the users (CUs and DUs) is used to allocate mode selection, and channel allocation to solve the JMSCPA problem, leading to a simpler solution with faster convergence, and significant reduction in the computational complexity which scales linearly with the number of users. Further, the proposed solution avoids premature stagnation of conventional ABC into local minima by incorporating a modification in its update procedure. The efficacy of the ABC-aided approach, as compared to the results reported in the literature, is validated by extensive numerical investigations under different simulation scenarios.