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The fifth generation of cellular networks (5G) is seeing a rapid expansion, and energy efficiency (EE) is a hot topic of discussion. It has been found that both EE and maximum spectral efficiency (SE) are desired. They are conflicting objectives, meaning that maximizing one will decrease the other. To tackle this issue, strategies for spectrum and energy optimization have been proposed, as well as green communication plans that aim to minimize the tradeoff between SE and EE. Research has been conducted on EE-oriented resource allocations to reduce energy usage while ensuring high-quality results. To do this, the Crow Search Optimization Algorithm (CSA) has been used. Simulation results have demonstrated that this proposed method is effective in finding the most suitable solution. [ABSTRACT FROM AUTHOR]

In cloud computing, resources are used to communicate instead of local servers or individual devices. However, sharing resources among several users is a difficult issue in cloud communication. Cryptography and steganography techniques are used for cloud storage to address data security challenges. This paper presents a novel method for securely encrypting image data for transmission and link exchange with a cloud storage service. There are two phases to accomplish the encryption process, the first phase encrypts the image file by XORing it with a random key that is generated by a new hybrid of the chaotic map. The second phase converts the encrypted image format to audio format to add another layer of security and improve secure image data transfer. The random key is generated using a hybrid chaotic map and has the benefit of having more than 10256 key spaces and the necessary level of security. Based on a statistical analysis of the encryption, the quality of the image is evaluated using several criteria, and the results demonstrate the algorithm's ability to accomplish resist encryption. [ABSTRACT FROM AUTHOR]

Watermarking is widely used in multimedia preservation and communication, which comprises, and is therefore not limited to, data security and validation. Security, readability, imperceptibility, and resilience are some of the key advantages of this technology. However, there are still certain issues that need to be addressed, such as the ability to withstand a variety of assaults without substantially affecting the quality and value of embedded data. Based on its operational domain, the watermarking technology may be divided into two groups: spatial and frequency watermarking. An index mapping-based watermarking approach for copyright protection of multi-media color videos is presented in this paper. We offer a hybrid discrete wavelet transform and discrete cosine transform (DCT) watermarking algorithm for digital video watermarking of a color video watermark. Peak signal to noise ratio (PSNR), similarity structure index measure (SSIM), have been used to analyze the distortion produced by watermarking. It is suggested that the proposed video watermarking method provides greater imperceptibility in conjunction with each other with the human visual system and it offers higher robustness against different attacks. [ABSTRACT FROM AUTHOR]

Cyber security is a term utilized for describing a collection of technologies, procedures, and practices that try protecting an online environment of a user or an organization. For medical images among most important and delicate data kinds in computer systems, the medical reasons require that all patient data, including images, be encrypted before being transferred over computer networks by healthcare companies. This paper presents a new direction of the encryption method research by encrypting the image based on the domain of the feature extracted to generate a key for the encryption process. The encryption process is started by applying edges detection. After dividing the bits of the edge image into (3x3) windows, the diffusions on bits are applied to create a key used for encrypting the edge image. Four randomness tests are passed through NIST randomness tests to ensure whether the generated key is accepted as true. This process is reversible in the state of decryption to retrieve the original image. The encryption image that will be gained can be used in any cyber security field such as healthcare organization. The comparative experiments prove that the proposed algorithm improves the encryption efficiency has a good security performance, and the encryption algorithm has a higher information entropy 7.42 as well as a lower correlation coefficient 0.653. [ABSTRACT FROM AUTHOR]

This research is aimed at planning the manner in which the secure 5G communication can be controlled based on traffic floods. To accomplish excellent administration execution of organization observing and 5G directing calculation is inescapable, dynamic steering in actual organization equipment isn't reasonable for practical plans of action. Accordingly, to bring down functional and capital consumption, we propose a strategy called versatile steering made do with the help of 5G Quality of Service and MANET (Mobile specially appointed Network). A practical 5G steering model which will help with fulfilling the needs of the customers and simultaneously gives huge investment funds in item cost and convenience was presented in this paper. To perform versatile 5G steering, we planned geography in a virtualized climate. We customized CHAOS for network traffic flood the board which goes about as a consistent northward API in 5G directing. Network traffic is infused dynamically from 1MB up to 10MB (connect b/w) in a progressive way for similar organization traffic with 10 organization occurrences. In conclusion, we performed versatile 5G steering applying the control hypothetical method with the assistance of CHAOS and MANET calculations. By looking at two directing situations, we noticed a prominent distinction in throughput for controlling organization traffic applications in MANETs. Network traffic flood data is refreshed after clockwork. [ABSTRACT FROM AUTHOR]

Diabetic Retinopathy (DR) is a serious consequence of diabetes that seriously impact on the eyes and is a leading cause of blindness. If the lesions in DR arise in the central portion of the fundus, they may result in significant vision loss, which we refer to as Diabetic Macular Edema (DME). Deep learning (DL) techniques are commonly used utilized in ophthalmology for discriminative tasks such as diabetic retinopathy or age-related macular degeneration (AMD) diagnosis. Deep learning techniques typically need huge picture data sets for deep convolutional neural networks (DCNNs) training, it should be graded by human specialists. According to international protocol, it is classified into five severity categories. However, improving a grading model for high generality needs a significant quantity of balanced training data, which is challenging to obtain, especially at high levels of severity. Typical techniques for data augmentation, in many applications of deep learning in the retinal image processing domain, the difficulty of access to huge annotated datasets and legal concerns about patient privacy are limiting issues. As a result, the concept of creating synthetic retinal pictures that are indistinguishable from actual data has garnered more attention. GANs have been certain to be an effective framework for creating synthetic databases of anatomically accurate retinal fundus pictures. GANs, in particular, have garnered increasing attention in ophthalmology. in this article, we present a loss-less generative adversarial network (DR-LL GAN) to generate good resolution fundus pictures that May be adjusted to include random grading and information about the lesion. As a result, large-scale generated data may be used to train a DR grading and lesion segmentation model with more appropriate augmentation. Our model experiments evaluated on IDRID and MESSIDOR datasets, it's obtained a discrimination loss of 0.69374 and a generation loss of 1.10438, as well as a segmentation accuracy of 0.9840 in our tests. This might support in the optimization techniques of the neural network design and in computer-aided screening of medical picture, thus increasing diagnostic reliability for clinical assessment in the future of sophisticated technological healthcare. [ABSTRACT FROM AUTHOR]

Due to the raising number of using Internet of Things (I O T) for personal and commercial devices and applications, as well as the continues needs for improving the quality of the performance for the internet -- connected devices enhance the researchers to investigate solutions for managing the data through the network Because of the fact that the internet-connected devices needs addresses for each sensor node uses the IP-network and a large number of electronic modules is fabricated to be compatible with IPv4 only like Node Mcu, ESP8266, Arduino WIFI, and ESP32 with knowing that the IPv4 has a limited addresses number that will not be enough for the needs of IOT developments, Many researchers turned to IPv6. In the proposed system, another solution is suggested instead of the IPV6. The proposed idea is based on Non-IP Wireless Sensor Network (WSN) by connecting many sensing nodes to the sink-node that has an IP to forward the data to the server to be visualized in a web-portal. By this method, it is able to connect more than one node to the internet over only one IP, there for the data rate that are needed will be decreased. In addition, by using the non-IP network, the data rate and the power consuming by the sensor nodes have been reduced, the practical results are discussed for connecting four nodes over one IP4 and how it will reduce the data rate and the power consuming. In this work, the esp33 has been used as a Sink-node, and the wireless transceiver module ( NRF24) has been utilized to transmit the data from nodes to esp32. [ABSTRACT FROM AUTHOR]