Key performance requirement of future next wireless networks (6G)

Given the massive potentials of 5G communication networks and their foreseeable evolution, what should there be in 6G that is not in 5G or its long-term evolution? 6G communication networks are estimated to integrate the terrestrial, aerial, and maritime communications into a forceful network which would be faster, more reliable, and can support a massive number of devices with ultra-low latency requirements. This article presents a complete overview of potential 6G communication networks. The major contribution of this study is to present a broad overview of key performance indicators (KPIs) of 6G networks that cover the latest manufacturing progress in the environment of the principal areas of research application, and challenges

Potential key challenges for terahertz communication systems

The vision of 6G communications is an improved performance of the data rate and latency limitations and permit ubiquitous connectivity. In addition, 6G communications will adopt a novel strategy. Terahertz (THz) waves will characterize 6G networks, due to 6G will integrate terrestrial wireless mobile communication, geostationary and medium and low orbit satellite communication and short distance direct communication technologies, as well as integrate communication, computing, and navigation. This study discusses the key challenges of THz waves, including path losses which is considered the main challenge; transceiver architectures and THz signal generators; environment of THz with network architecture and 3D communications; finally, Safety and health issues

Sand cat swarm optimizer with CatBoost for Sarcoidosis diagnosis

In the last few years, machine learning has increased in popularity across many disciplines. This paper aims to comprehensively analyze the CatBoost classification algorithm in the context of Sarcoidosis. Analysis was undertaken to evaluate the performance of the CatBoost classification algorithm in comparison to other classifiers. The CatBoost algorithm outperformed other classifiers exploited in this study to identify and differentiate Sarcoidosis. Previous scholarly works ignored missing data observations or filled them with mean values; on the other hand, this study has uncovered that the SIL-2R feature holds significant importance in predicting the occurrence of Sarcoidosis, which improved the selection of treatment and its efficacy. A comprehensive understanding of Sarcoidosis is essential to accurately differentiating symptoms associated with this illness from those associated with other conditions. It is strongly recommended that the CatBoost algorithm be used for sarcoidosis prediction.</p

Evaluating the mixing performance in a planar passive micromixer with t-shape and SAR mixing chambers: comparative study

In Microfluidic devices have gained significant interest in various fields, including biomedical diagnostics, environmental preservation, animal epidemic avoidance, and food safety regulation. Micromixing phenomena are crucial for these devices' functionality, as they accurately and efficiently manipulate fluids within microchannels. The process aims to blend samples accurately and swiftly within these scaled-down devices, governed by the promotion of dispersion among distinct fluid species or particles. Advancements in passive and active micromixers have led to innovative designs incorporating diverse processes to enhance mixing efficiency. Examples include two-dimensional impediments, controlled imbalanced collisions, and complex configurations like spiral and convergence-divergence structures. Active micromixers use external cues to initiate and regulate mixing processes, including thermal, magnetic, sound, pressure, and electrical fields. The trajectory of micromixing technologies is significantly influenced by current developments in microfluidics. One notable advancement is the incorporation of micromixers into 3D printing methodologies, facilitating the development of adaptable microfluidic systems. Additionally, the incorporation of microfluidic principles into paper-based channels creates opportunities for the development of cost-effective and portable diagnostic devices. The process of micro-mixing is critical in boosting the functionalities of these devices.</p

Assessment of mixing efficiency in a planar passive micromixer With t-shaped configuration

Microfluidic devices have garnered considerable interest owing to their prospective utilization in diverse domains, encompassing chemical synthesis, biological analysis, and medicinal research. Micromixers are critical in adequate fluid mixing at a microscale within the array of devices under consideration. This study aims to offer a comprehensive analysis of the efficacy of the T-shaped micromixer configuration in scenarios that necessitate accurate and expeditious mixing. This study examines the performance of a T micromixer through simulation and analysis. The findings demonstrate that T micromixers exhibit some drawbacks that result in suboptimal mixing efficiency. The attainment of a desirable level of mixing efficiency can be accomplished by utilizing splitting-recombination and chaotic advection mechanisms. The study's outcomes indicate that the T micromixer demonstrates its maximum mixing effectiveness, roughly 60% when the Reynolds number (Re) is at or below 0.5. Nevertheless, it has been observed that the T micromixer encounters a decrease in mixing effectiveness as the Reynolds number escalates within the range of 0.5 to 15.</p

A low-complexity equalizer for video broadcasting in cyber-physical social systems through handheld mobile devices

In Digital Video Broadcasting-Handheld (DVB-H) devices for cyber-physical social systems, the Discrete Fractional Fourier Transform-Orthogonal Chirp Division Multiplexing (DFrFT-OCDM) has been suggested to enhance the performance over Orthogonal Frequency Division Multiplexing (OFDM) systems under time and frequency-selective fading channels. In this case, the need for equalizers like the Minimum Mean Square Error (MMSE) and Zero-Forcing (ZF) arises, though it is excessively complex due to the need for a matrix inversion, especially for DVB-H extensive symbol lengths. In this work, a low complexity equalizer, Least-Squares Minimal Residual (LSMR) algorithm, is used to solve the matrix inversion iteratively. The paper proposes the LSMR algorithm for linear and nonlinear equalizers with the simulation results, which indicate that the proposed equalizer has significant performance and reduced complexity over the classical MMSE equalizer and other low complexity equalizers, in time and frequency-selective fading channels. © 2013 IEEE

Evaluation of the mixing performance in a planar passive micromixer with T micromixer with square chamber mixing units (SAR)

Microscale mixing methods are crucial in various disciplines, encompassing chemical reactions and biological investigations. The present study used simulation methodologies to investigate the operational efficiency of splitting recombination (SAR) micromixers. The study demonstrates that SAR micromixers offer a notable advantage in enhancing mixing efficiency. The advantage above is a consequence of the effective combination of splitting-recombination and chaotic advection processes within the micromixer architecture. An in-depth analysis of the micromixer's behavior demonstrates that its performance is supported by intricate fluid dynamics, which provide remarkably high mixing efficiency. It is worth noting that the micromixer exhibits its maximum mixing efficiency, which is roughly 99% when the Reynolds number (Re) is at or below 0.5. Nevertheless, it is seen that as the Reynolds number grows, there is a steady decrease in mixing efficiency. At a Reynolds number of 70, the measurement of mixing efficiency yields a value of 75%. However, when the Reynolds number is further increased to a range of 90-100, the efficiency decreases to its lowest value of approximately 60%. The results above highlight the exceptional mixing ability of the SAR micromixer, hence stressing its potential for various applications that demand improved mixing capabilities. The results emphasize the promise of SAR micromixers as a reliable solution for complex mixing processes in many applications, providing valuable insights that may contribute to future developments in microscale mixing technologies.</p

Synthetic generation of multidimensional data to improve classification model validity

This article aims to compare Generative Adversarial Network (GAN) models and feature selection methods for generating synthetic data in order to improve the validity of a classification model. The synthetic data generation technique involves generating new data samples from existing data to increase the diversity of the data and help the model generalize better. The multidimensional aspect of the data refers to the fact that it can have multiple features or variables that describe it. The GAN models have proven to be effective in preserving the statistical properties of the original data. However, the order of data augmentation and feature selection is crucial to build robust and accurate predictive models. By comparing the different GAN models with feature selection methods on multidimensional datasets, this article aims to determine the best combination to support the validity of a classification model in multidimensional data.</p

Automatic Correction of Indonesian Grammatical Errors Based on Transformer

Grammatical error correction (GEC) is one of the major tasks in natural language processing (NLP) which has recently attracted great attention from researchers. The performance of universal languages such as English and Chinese in the GEC system has improved significantly. This could be attributed to the large number of powerful applications supported by neural network models and pretrained language models. Referring to the satisfactory results of the universal language in the GEC task and the lack of research on the GEC task for low-resource languages, especially Indonesian, this paper proposes an automatic model for Indonesian grammar correction based on the Transformer architecture which can be applied to other low-resource language texts. Furthermore, we build a large corpus of the Indonesian language that can be utilized for evaluating the next Indonesian GEC task. We evaluate the models in this dataset, and the results show that the Transformer-based automatic error correction model achieved significant and satisfactory results compared with the results of previous research models