Energy and Distance Based Multi-Objective Red Fox Optimization Algorithm in Wireless Sensor Network.

In modern trends, wireless sensor networks (WSNs) are interesting, and distributed in the environment to evaluate received data. The sensor nodes have a higher capacity to sense and transmit the information. A WSN contains low-cost, low-power, multi-function sensor nodes, with limited computational capabilities, used for observing environmental constraints.

Effective CBMIR System Using Hybrid Features-Based Independent Condensed Nearest Neighbor Model.

In recent times, a large number of medical images are generated, due to the evolution of digital imaging modalities and computer vision application. Due to variation in the shape and size of the images, the retrieval task becomes more tedious in the large medical databases. So, it is essential in designing an effective automated system for medical image retrieval.

Collision-Aware Routing Using Multi-Objective Seagull Optimization Algorithm for WSN-Based IoT.

In recent trends, wireless sensor networks (WSNs) have become popular because of their cost, simple structure, reliability, and developments in the communication field. The Internet of Things (IoT) refers to the interconnection of everyday objects and sharing of information through the Internet. Congestion in networks leads to transmission delays and packet loss and causes wastage of time and energy on recovery.

Implementation of Speed-Efficient Key-Scheduling Process of AES for Secure Storage and Transmission of Data.

Nowadays, a large number of digital data are transmitted worldwide using wireless communications. Therefore, data security is a significant task in communication to prevent cybercrimes and avoid information loss. The Advanced Encryption Standard (AES) is a highly efficient secure mechanism that outperforms other symmetric key cryptographic algorithms using message secrecy.

Dynamic Bargain Game Theory in the Internet of Things for Data Trustworthiness.

Smart home and smart building systems based on the Internet of Things (IoT) in smart cities currently suffer from security issues. In particular, data trustworthiness and efficiency are two major concerns in Internet of Things (IoT)-based Wireless Sensor Networks (WSN). Various approaches, such as routing methods, intrusion detection, and path selection, have been applied to improve the security and efficiency of real-time networks.

Prediction of muscular paralysis disease based on hybrid feature extraction with machine learning technique for COVID-19 and post-COVID-19 patients.

Many Coronavirus disease 2019 (COVID-19) and post-COVID-19 patients experience muscle fatigues. Early detection of muscle fatigue and muscular paralysis helps in the diagnosis, prediction, and prevention of COVID-19 and post-COVID-19 patients. Nowadays, the biomedical and clinical domains widely used the electromyography (EMG) signal due to its ability to differentiate various neuromuscular diseases.

Crystal structure and Hirshfeld surface analysis of 2-(4-nitro-phen-yl)-2-oxoethyl 2-chloro-benzoate.

The title compound, CHClNO, is relatively planar with the two aromatic rings being inclined to each other by 3.56 (11)°. The central -C(=O)-C-O-C(=O)- bridge is slightly twisted, with a C-C-O-C torsion angle of 164.

Crystal structure and Hirshfeld surface analysis of 2-(4-nitro-phen-yl)-2-oxoethyl benzoate.

The title com-pound, CHNO, is relatively planar, with the planes of the two aromatic rings being inclined to each other by 3.09 (5)°. In the crystal, mol-ecules are linked by a pair of C-H⋯O hydrogen bonds, forming inversion dimers, which enclose an (16) ring motif.