Sixth Generation Research Articles

Aerodynamic Simulation of Small Airway Resistance: A New Imaging Biomarker for Chronic Obstructive Pulmonary Disease.

To develop a novel method for calculating small airway resistance using computational fluid dynamics (CFD) based on CT data and evaluate its value to identify COPD. 24 subjects who underwent chest CT scans and pulmonary function tests between August 2020 and December 2020 were enrolled retrospectively. Subjects were divided into three groups: normal (10), high-risk (6), and COPD (8). The airway from the trachea down to the sixth generation of bronchioles was reconstructed by a 3D slicer. The small airway resistance (RSA) and RSA as a percentage of total airway resistance (RSA%) were calculated by CFD combined with airway resistance and FEV1 measured by pulmonary function test. A correlation analysis was conducted between RSA and pulmonary function parameters, including FEV1/FVC, FEV1% predicted, MEF50% predicted, MEF75% predicted and MMEF75/25% predicted. The RSA and RSA% were significantly different among the three groups (p<0.05) and related to FEV1/FVC (r = -0.70, p < 0.001; r = -0.67, p < 0.001), FEV1% predicted (r = -0.60, p = 0.002; r = -0.57, p = 0.004), MEF50% predicted (r = -0.64, p = 0.001; r = -0.64, p = 0.001), MEF75% predicted (r = -0.71, p < 0.001; r = -0.60, p = 0.002) and MMEF 75/25% predicted (r = -0.64, p = 0.001; r = -0.64, p = 0.001). Airway CFD is a valuable method for estimating the small airway resistance, where the derived RSA will aid in the early diagnosis of COPD.

Enabling Space-Air integration: A Satellite-UAV networking authentication scheme

One of the goals of sixth-generation mobile networks (6G) is to achieve a larger network coverage area. Satellite networks enable global coverage and aerial nodes such as Unmanned Aerial Vehicle (UAV) can serve as a supplement to ground networks in remote environments. Therefore, 6G networks are gradually evolving towards Space-Air-Ground integrated networks. The combination of UAV networks and satellite networks is a research hotspot in the field of Space-Air integrated networks. However, the combination of UAV networks and satellite networks currently faces many challenges in terms of security. The characteristics of large propagation delay and unstable communication links in satellite networks make them vulnerable to various attacks, including eavesdropping, tampering, and impersonation. Meanwhile, existing research on UAV networks mainly focuses on UAV-Ground networking authentication mechanisms, which are not suitable for resource-constrained nodes in the Space-Air integration scenario. Therefore, based on elliptic curve public key cryptography and Chebyshev polynomial, we propose a secure networking authentication scheme for satellite nodes and UAV nodes in the Space-Air integration scenario. The security analysis indicates that our scheme possesses security attributes such as mutual authentication, key agreement, identity anonymity, unlinkability, perfect forward-backward security, and resistance against various protocol attacks, among other security properties. Performance analysis also indicates certain advantages of our scheme over existing schemes in terms of signaling, bandwidth, and computational overhead.

NVM-enhanced Machine Learning Inference in 6G Edge Computing

With the increasing popularization of smart terminals and real-time interactive applications, fast growing technical requirements push both academia and industry to look beyond 5G and conceptualize the sixth generation (6G) mobile network. Artificial intelligence (AI) with machine learning capacities at the edge is one crucial component of a 6G mobile network which makes various time-sensitive and high-stake services possible, e.g., smart security, virtual reality, self-driving vehicles. However, resource constraints, especially the memory limitation of edge servers, become major obstacles to deploying machine learning services at the edge. Fortunately, the new generation of non-volatile memory (NVM) provides new affordable memory resources that can be easily attached to existing edge servers. In this paper, we propose a novel machine learning application placement scheme using the NVM technology at the edge to reduce the end-to-end latency. Specifically, the proposed NVM-enhanced placement scheme takes into consideration the latency of various machine learning applications over NVM devices and the network. The corresponding optimization problem is exceedingly challenging, i.e., NP-hard. Therefore, we developed a novel approximation algorithm with both low computational complexity and theoretical guarantees. Experiments and extensive simulations using real-world applications highlight that our scheme provides significantly lower end-to-end latency compared with existing baselines.

The effect of immediate dentin sealing on the bond strength of resin composite to dentin bonded with universal bonding agent: An in vitrostudy

Background:Dentin hypersensitivity is a common scenario encountered in dental practice. This issue can be treated by reducing dentin permeability and dentinal fluid flow. However, the desensitizing agents used may adversely affect the bonding of composite restorations to dentin.Aim:To evaluate the shear bond strength of restorative composites to dentin treated with silver diamine fluoride and self-etch bonding agent bonded using a universal bonding agent.Materials and methods:A total of 30 teeth were selected, and their occlusal surfaces were ground to expose a flat dentin surface. The teeth were then embedded in cold cure resin blocks. Depending on the treatment, the samples were randomly divided into three groups, with 10 in each. The samples in the group were untreated, in group 2 were treated with Silver Diamine Fluoride (SDF), and in group 3 with the sixth generation bonding agent (self-etch primer). After the treatment, the composite is bonded to the dentin surfaces and subjected to shear bond strength using the universal testing machine (UTM). The specimen was mounted on the custom-made jig and placed over the UTM. The load was applied at a cross-head speed of 1mm/min until debonding occurred at the dentin and composite interface, and the bond strength was computed in MPa. Overall comparisons were analyzed using the Kruskal-Wallis test. The Mann-Whitney U-test was used for pair-wise comparisons, and the significance level was set at p &lt; 0.05.Results:The lowest bond strength was observed with the dentin surfaces treated with silver diamine fluoride (Group 2), and the highest bond strength was for dentin treated with self-etchbonding agent (Group3). Significant differences (p=0.003) were observed between the groups. In pair-wise comparisons, group 3 showed significant difference with group 1 (p=0.007) and group 2 (p=0.002). However, no significant difference was observed between groups 1 and 2 (p=0.197).Conclusion:The shear bond strength varies with different desensitizing treatments. This study reported more SBS with sixth-generation bonding agent followed by untreated dentin and SDF.

Performance Evaluation of OTFS-NOMA Scheme for High Mobility Users

Orthogonal Time Frequency Space (OTFS) is a promising approach which is widely employed in sixth generation (6G) wireless network systems. Because of its superior performance in high-mobility environments, OTFS modulation has received a lot of attention lately. Due to OTFS modulation works in the delay-Doppler (DD) domain rather than the conventional time-frequency (TF) domain, it works effectively in such circumstances. The idea of non-orthogonal multiple access (NOMA) is integrated into OTFS as an important approach to improve the spectral efficiency (SE) to investigate the efficiency potential and performance. In this research, we study OTFS modulated NOMA system for two destination users in the high mobility environment. The message passing detection algorithm is utilized to examine bit error rate (BER) performance for both near and far users in the proposed OTFS modulated NOMA system. The BER simulation results demonstrate that the power allocation (PA) coefficient, delays, and Doppler effects significantly impact the performance of the system.

6G – NETWORK OF THE FUTURE

&amp;lt;p class=&amp;quot;MsoNormal&amp;quot; style=&amp;quot;text-align: justify; line-height: 150%;&amp;quot;&amp;gt;&amp;lt;span style=&amp;quot;font-size: 12.0pt; line-height: 150%; font-family: 'Times New Roman',serif;&amp;quot;&amp;gt;6G stands for the sixth generation of mobile networks, which represents the future of wireless communication. While 5G networks are still being developed and expanded around the world, the industry is already thinking about the next generation to meet the needs of the accelerated digital transformation and the demands of modern society. 6G networks will be even faster, more reliable, with lower latency and higher capacity than their predecessors. It is expected to deliver incredible data transfer speeds of terabytes per second, enabling instant downloads of large files and supporting technologies such as virtual and augmented reality, artificial intelligence, autonomous vehicles, Internet of Things (IoT) devices and other advanced applications.. One key features of 6G networks will be greater connectivity between people, machines and things, creating an intelligent network that will enable highly sophisticated communication scenarios. 6G networks are expected to provide the possibility of continuous connectivity with high quality of service, even in difficult environments such as rural areas, inside buildings or in motion. 6G networks will use multiple frequency bands, including terahertz frequencies, which will allow for greater capacity and higher data transfer speeds. It will also require advanced use of antenna systems, such as massive multiplexed antennas (Massive MIMO), in order to achieve a high degree of wireless efficiency. However, it is important to note that the 6G network is still in the research and development phase. Standardization and commercial implementation are expected only after 2030. Industry,&amp;lt;/span&amp;gt;&amp;lt;/p&amp;gt; &amp;lt;p class=&amp;quot;MsoNormal&amp;quot; style=&amp;quot;text-align: justify; line-height: normal;&amp;quot;&amp;gt;&amp;lt;strong&amp;gt;&amp;lt;i&amp;gt;&amp;lt;span style=&amp;quot;font-size: 12.0pt; font-family: 'Times New Roman',serif;&amp;quot;&amp;gt;Keywords&amp;lt;/span&amp;gt;&amp;lt;/i&amp;gt;&amp;lt;/strong&amp;gt;&amp;lt;i&amp;gt;&amp;lt;span style=&amp;quot;font-size: 12.0pt; font-family: 'Times New Roman',serif;&amp;quot;&amp;gt;: 6G, networks, future, IoT, transfer, industry, standardization&amp;lt;/span&amp;gt;&amp;lt;/i&amp;gt;&amp;lt;/p&amp;gt;

A novel enhanced security architecture for sixth generation (6G) cellular networks using authentication and acknowledgement (AA) approach

The sixth generation (6G) of cellular transmission is extremely adaptable. 6G will equip everyone with pervasive wireless connectivity and meet the needs of a fully connected world. It is anticipated that revolutionary ideas will increase in support for a fast-expanding variety of smart devices and applications. The sophisticated characteristics of 5G portable cellular network infrastructures produce novel threats and requirements. Comparing 6G cellular network technologies to 5G cellular networks, this paper discusses various security and privacy issues in 6G cellular networks based numerous security services. Proposes AA approach to evaluate the effectiveness of the methodology. Propose a new 6G wireless security architecture based on the analysis of secret key authentication and flexible position based identification, which serves as the foundation for an examination of identity management and flexible authentication. Demonstrates the benefits of the proposed architecture, analyzes BER against SINR and Measure Throughput Against various SINR values. Finally, Limitations and future recommendation for 6G cellular network security is presented.

ADJUSTING THE PARAMETERS OF MACHINE LEARNING ALGORITHMS TO IMPROVE THE SPEED AND ACCURACY OF TRAFFIC CLASSIFICATION

Background. Telecommunications developments lead to new mobile network technologies and especially 5G, which has only recently been launched, sixth generation of which is already under active development. The development of new technologies influence on both types of mobile traffic (V2V, IoT) and leads to the significant increase in the volume of existing traffic types. Currently, existing methods of traffic processing are not adapted to such changes, which may lead to a deterioration in the quality of service.&#x0D; Objective. The purpose of the paper is to analyze the effectiveness of machine learning algorithms to solve the task of traffic classification in mobile networks in real time.&#x0D; Methods. The method of solving the problem of increasing the efficiency of information processing is the introduction of new algorithms for traffic classification and prioritization. In this regard, the paper presents the urgent task of analyzing the effectiveness of machine learning algorithms to solve the task of traffic classification in mobile networks in real time.&#x0D; Results. Comparison indicated the best accuracy of the ANN algorithm that was achieved with the number of hidden layers of the network equal to 200. Also, the research results showed that different applications have different recognition accuracy, which does not depend on the total number of packets in the dataset.&#x0D; Conclusions. This proceeding solves the urgent problem of increasing the efficiency of the mobile communication system through the use of machine learning algorithms for traffic classification. In this regard, it can be concluded that the most promising is the application of algorithms based on ANN. In future the aspect of anomaly detection based on traffic classification and traffic pattern preparation should be investigated, as this process allows detecting attacks to network infrastructure and increase mobile network security.

A Survey on the Impact of Intelligent Surfaces in the Terahertz Communication Channel Models.

Terahertz (THz) band will play an important role in enabling sixth generation (6G) envisioned applications. Compared with lower frequency signals, THz waves are severely attenuated by the atmosphere temperature, pressure, and humidity. Thus, designing a THz communication system must take into account how to circumvent or diminish those issues to achieve a sufficient quality of service. Different solutions are being analyzed: intelligent communication environments, ubiquitous artificial intelligence, extensive network automation, and dynamic spectrum access, among others. This survey focuses on the benefits of integrating intelligent surfaces (ISs) and THz communication systems by providing an overview of IS in wireless communications with the scanning of the recent developments, a description of the architecture, and an explanation of the operation. The survey also covers THz channel models, differentiating them based on deterministic and statistical channel modeling. The IS-aided THz channels are elucidated at the end of the survey. Finally, discussions and research directions are given to help enrich the IS field of research and guide the reader through open issues.

Multi-Wavelength Path Loss Model for Indoor VLC with Mobile Human Blockage

Visible light communication (VLC) is one of the candidate technologies for the sixth generation (6G) networks. The path loss model is particularly important for link budget estimation and network planning in VLC. Due to the wideband nature and the extremely poor diffraction capacity of light, the path loss of the VLC channel is susceptible to wavelength dependence and blockage effect. In this paper, we propose a novel path loss model which can characterize the impact of wavelength dependence combined with mobile human blockage for both the single-LED (light emitting diode) and the multi-LED scenario. When there is no blockage in the channel, the multi-wavelength path loss under free space propagation is modeled with a small standard deviation of 0.262 in the single-LED scenario and a small root mean square error of 0.009 in the multi-LED scenario which indicates the high accuracy of the model. When considering the mobile human blockage, the blockage probability (BP) is modeled with full consideration of realistic human mobility and human body shadowing. The results indicate that the BP in single-LED scenario can reach 0.08, while the BP in multi-LED scenario is 0.022. This demonstrates that the distributed deployment of transmitters can effectively reduce the occurrence of the blockage state in VLC.

Efficient and Low-Complex Signal Detection with Iterative Feedback in Wireless MIMO-OFDM Systems.

To solve error propagation and exorbitant computational complexity of signal detection in wireless multiple-input multiple-output-orthogonal frequency division multiplexing (MIMO-OFDM) systems, a low-complex and efficient signal detection with iterative feedback is proposed via a constellation point feedback optimization of minimum mean square error-ordered successive interference cancellation (MMSE-OSIC) to approach the optimal detection. The candidate vectors are formed by selecting the candidate constellation points. Additionally, the vector most approaching received signals is chosen by the maximum likelihood (ML) criterion in formed candidate vectors to reduce the error propagation by previous erroneous decision, thus improving the detection performance. Under a large number of matrix inversion operations in the above iterative MMSE process, effective and fast signal detection is hard to be achieved. Then, a symmetric successive relaxation iterative algorithm is proposed to avoid the complex matrix inversion calculation process. The relaxation factor and initial iteration value are reasonably configured with low computational complexity to achieve good detection close to that of the MMSE with fewer iterations. Simultaneously, the error diffusion and complexity accumulation caused by the successive detection of the subsequent OSIC scheme are also improved. In addition, a method via a parallel coarse and fine detection deals with several layers to both reduce iterations and improve performance. Therefore, the proposed scheme significantly promotes the MIMO-OFDM performance and thus plays an irreplaceable role in the future sixth generation (6G) mobile communications and wireless sensor networks, and so on.

Weapon of choice: a neoliberal institutional perspective on Italy’s decision to procure a sixth generation fighter aircraft

ABSTRACT In 2018, Italy decided to join the British-led Team Tempest to develop a sixth generation fighter aircraft. This decision came at the expense of a rival project, the Future Combat Air System (FCAS), led by France and Germany. The Italian decision to join Tempest raises a theoretical question overlooked by the existing literature: when states have different cooperative procurement options, what makes them choose one rather than another? The aim of the article is to provide an analytically informed account of the process that led Italy to join Tempest. In doing so, we adopt a neo-institutionalist perspective, as it allows us to identify the actors and motivations that made this outcome possible. We argue that due to the peculiar Italian bureaucratic-institutional setting, no domestic actor was solely responsible for the final decision. The final decision to join Tempest was the result of a coalition between the Armed Forces and defence firms.

The Fragility of Authorship for Film Directors in Contemporary China

Despite its progressive liberalisation and development, the Chinese film industry is still subject to strict control from the China Film Administration (CFA). Laws and regulations evolved since the 1990s, but they leave large space to interpretation, opening the door to a long process of negotiation that can alter the vision of the directors. In the early 1990s, the Sixth Generation of directors changed the canons of Chinese art-house cinema, adopting a gritty neo-realist style, investigating the darker sides of Chinese society, and working outside the official studio system. Despite recognition in the international festival circuit, which deprived them of national distribution, they decided to return to the fold. The negotiation process with the CFA makes their authorship fragile, and the necessity to continue to be present in the festival circuit risk to put them in a double occupancy position. This article will analyse what are the factors that fragilise the authorship of contemporary Chinese art-house directors and what are the countermeasures adopted by some of them to preserve their authorship.

Next-Generation Urban Intelligence: Integrating 6G Communication and Blockchain Technology for Smart City Advancements

The process of modern urbanization necessitates significant advancements in social, environmental, and economic aspects to enhance the overall quality of life in cities. This evolution has given rise to the concept of "Smart Cities." The incorporation of cutting-edge technologies such as blockchain, the Internet of Things (IoT), and other innovative communication systems has accelerated the progress towards the establishment of the sixth-generation communication intelligence, commonly known as 6G.Connected to the blockchain in smart cities is a crucial key, and researchers conducted an in-depth analysis of prior research to elucidate the pivotal contributions, ensuring a clear understanding of the state-of-the-art in sixth generation blockchain for smart cities. This study aims to pave the way for future research by examining key technologies, scenarios, challenges, and associated issues. Exploring the obstacles in deployment that require resolution before the implementation of block intelligence in 6G networks, this study aims to establish a foundational understanding for forthcoming advancements in blockchain technology within this generation. The paper outlines prospective research areas critical for the evolution of blockchain in the 6G era. Additionally, it addresses the challenges associated with integrating blockchain amidst the advancements in computing and mobile communication technologies, offering insights into the complexities that need to be navigated for a successful efficiency.

Reconfigurable Wide‐Angle Beam‐Steering Terahertz Metasurfaces Based on Vanadium Dioxide

AbstractThe sixth generation (6G) wireless network is envisioned to provide faster and more reliable communication by utilizing electromagnetic waves in the terahertz spectrum. However, terahertz waves suffer from high propagation loss and, hence, wavefront manipulation solutions to focus and redirect terahertz waves are of paramount importance. Reconfigurable intelligent surface (RIS) is one such promising dynamic wavefront engineering solution proposed for 6G networks, but the technological realization of 6G (&gt;100 GHz) RIS is still largely lacking. Here, spatially‐selective vanadium dioxide (VO2) patches incorporating coding metasurfaces for dynamic beam steering of terahertz waves are presented. The reversible and abrupt insulator‐to‐metal phase transition property of VO2 is exploited to achieve a reconfigurable transmission angle for the normal incident terahertz wave. By designing metasurfaces with specific linear phase gradients and designer phase sequencing, electrically switchable beam steering is achieved from co‐polarized 0° (normal transmission) in the OFF state to cross‐polarized 0° (control), 11°, 23°, 36°, and 52° in the ON state at 0.6 THz. Scaling up the proposed concept to achieve individual control of each active element (VO2) within the metasurface will enable a complete 6G RIS solution for full 3D terahertz beam manipulation to support the future THz wireless communication networks.

Deep learning‐assisted reconfigurable intelligent surface for enhancing 6G mobile networks

AbstractThis article presents the role of Reconfigurable Intelligent Surface (RIS) using the Multi‐Input Multi‐Output (MIMO) technique as the enabling technology to boost the achievable data rate for mobile networks of the sixth generation (6G). The RIS has been adopted to mitigate the interference at the Cell Edge User (CEU) placed where two adjacent cells are separated. That is by reflecting the incident interference signal in the CEU direction out of phase with the basic interference signals coming from the interfering BS towards the CEU. This article adopts an efficient solution for designing the RIS redirecting (reflection) matrix with trivial training overhead using Deep Learning (DL) technology. Whereas a few of the reflecting elements in RIS are chosen to be active (attached to the baseband), whilst the majority are chosen to be passive, in which the active element's channels are known and used as medium indicators and indicate further the positions of the transmitter and receiver. This article illustrated the efficacy of the adopted framework with DL, by changing the training parameters regarding the data rates that can be achieved, the Spectral Energy Efficiency (SEE), and the Satisfaction Rate (SR). As a result, the proposed model improves the achievable data rate by a near average of 97% above the reference model. Furthermore, it enhances the achievable data rate above the baseline model that assumes no RIS used by an average of 115%. Therefore, The DL method demonstrated that the proposed model is promising for enhancing 6G Mobile Networks.

Evolution toward intelligent communications: Impact of deep learning applications on the future of 6G technology

AbstractThe sixth generation (6G) represents the next evolution in wireless communication technology and is currently under research and development. It is expected to deliver faster speeds, reduced latency, and greater capacity compared to the current 5G wireless technology. 6G is envisioned as a technology capable of establishing a fully data‐driven network, proficient in analyzing and optimizing end‐to‐end behavior and handling massive volumes of real‐time data at rates of up to terabits per second (Tb/s). Moreover, 6G is designed to accommodate an average of 1000+ substantial connections per person over the course of a decade. The concept of a data‐driven network introduces a new service paradigm, which offers fresh opportunities for applications within 6G wireless communication and network design in the future. This paper aims to provide a survey of existing applications of 6G that are based on deep learning techniques. It also explores the potential, essential technologies, scenarios, challenges, and related topics associated with 6G. These aspects are crucial for meeting the requirements for the development of future intelligent networks. Furthermore, this work delves into various research gaps between deep learning and 6G that remain unexplored. Different potential deep learning applications for 6G networks, including privacy, security, environmentally friendly communication, sustainability, and various wireless applications, are discussed. Additionally, we shed light on the challenges and future trends in this field.This article is categorized under: Technologies &gt; Computational Intelligence Fundamental Concepts of Data and Knowledge &gt; Explainable AI Technologies &gt; Machine Learning

A comprehensive survey on 6G and beyond: Enabling technologies, opportunities of machine learning and challenges

Multiple nations are now in the process of launching 5G mobile networks. All of the telecoms industry has been revolutionized by the concept of 5G networks. Since late 2018, researchers and telecom players have been actively exploring the potential of 6G as a successor to 5G. It is anticipated that the 6G generation would have even more severe performance criteria than the 5G generation had. New sophisticated technologies and paradigms must be included into 6G network designs and procedures to satisfy the requirements and standards of the sixth generation. As a result, several publications and studies covering the relevant technologies, techniques, algorithms, and architectures have appeared in the recent few years. The current paper fills a gap in the literature by offering informative recommendations for further study of 6G networks. Connectivity targets within 6G are outlined, and the study explains the wireless progression toward 6G networks. The technologies are outlined, as are the obstacles that must be surmounted. This chapter also provides a thorough and up-to-date overview of the state of the art. Additionally, multiple classifications of 6G capabilities and techniques are provided, with an emphasis on the advantages and disadvantages of each process. In order to accelerate the advancement of 6G technologies and fulfill their needs, we also identify open problems and potential future possibilities.

An Overview of the Implications of Artificial Intelligence (AI) in Sixth Generation (6G) Communication Network

The 6G communication network is anticipated to be a cutting-edge next-generation communication network that will enhance the value of the intelligent Internet of Things (IoT). The emergence of many domains within artificial intelligence (AI) has paved the way for significant opportunities in the development of 6G technology. These opportunities include the enhancement of human intelligence, the integration of various devices and systems through the Internet of Everything (IoE), improvements in the quality of experiences, and enhancements in the overall quality of life. The integration of AI and 6G networking technology is anticipated to bring about a transformative shift, transitioning from a focus on interconnected devices to a paradigm centered around interconnected intelligent systems. This article provides an overview of the extent to which AI is poised to revolutionize 6G networking technologies. This study is primarily concerned with the implementation of appropriate applications that address human needs and challenges. Furthermore, this research highlights the significance of technology that has the potential to provide value for emerging technologies.

PERAN KH. MA’MUN DALAM PERKEMBANGAN PONDOK PESANTREN RIYADLUL ‘ULUM WADDA’WAH TAHUN 1986-2014 M

PERAN KH. MA’MUN DALAM PERKEMBANGAN PONDOK PESANTREN RIYADLUL ‘ULUM WADDA’WAH TAHUN 1986-2014 M