BeneWinD: An Adaptive Benefit Win–Win Platform with Distributed Virtual Emotion Foundation

In recent decades, online platforms that use Web 3.0 have tremendously expanded their goods, services, and values to numerous applications thanks to its inherent advantages of convenience, service speed, connectivity, etc. Although online commerce and other relevant platforms have clear merits, offline-based commerce and payments are indispensable and should be activated continuously, because offline systems have intrinsic value for people. With the theme of benefiting all humankind, we propose a new adaptive benefit platform, called BeneWinD, which is endowed with strengths of online and offline platforms. Furthermore, a new currency for integrated benefits, the win–win digital currency, is used in the proposed platform. Essentially, the proposed platform with a distributed virtual emotion foundation aims to provide a wide scope of benefits to both parties, the seller and consumer, in online and offline settings. We primarily introduce features, applicable scenarios, and services of the proposed platform. Different from previous systems and perspectives, BeneWinD can be combined with Web 3.0 because it deliberates based on the decentralized or distributed virtual emotion foundation, and the virtual emotion feature and the detected virtual emotion information with anonymity are open to everyone who wants to participate in the platform. It follows that the BeneWinD platform can be connected to the linked virtual emotion data block or win–win digital currency. Furthermore, crucial research challenges and issues are addressed in order to make great contributions to improve the development of the platform

Eco-Friendly Low Resource Security Surveillance Framework Toward Green AI Digital Twin

Most intelligent systems focused on how to improve performance including accuracy, processing speed with a massive number of data sets and those performance-biased intelligent systems, Red AI systems, have been applied to digital twin in smart cities. On the other hand, it is highly reasonable to consider Green AI features covering environmental, economic, social costs for advanced digital twin services. In this letter, we propose eco-friendly low resource security surveillance toward Green AI-enabled digital twin service, which provides eco-friendly security by the active participation of low resource devices. And, we formally define a problem whose objective is to maximize the participation of low source or reusable devices such that reusable surveillance borders are created within security district. Also, a dense sub-district with low resource devices priority completion scheme is proposed to resolve the problem. Then, the devised method is performed by expanded simulations and the achieved result is evaluated with demonstrated discussions

Maximum Activation 3D Cube Transition System for Virtual Emotion Surveillance

The concept of barrier coverage has been utilized for with various applications of surveillance, object tracking in smart cities. In barrier coverage, it is desirable to have large number of active barriers to maximize lifetime of UAV-assisted application. Because existing studies primarily focused on the formation of barriers in two-dimensional area with limited applicability, it is indispensable to extend the barrier constructions in three-dimensional area. In this letter, a cube transition barrier system using smart UAVs is designed for three-dimensional space. Then, we formally define a problem whose goal is to maximize the number of cube transition barriers by applying a two-dimensional theory to a three-dimensional spaces. To solve this problem, we propose two algorithms to return the number of barriers and evaluate their performances based on numerical simulation results

Intelligent Aerial-Ground Surveillance and Epidemic Prevention with Discriminative Public and Private Services

Since complete surveillance is essential to provide safe daily life to citizen in smart cities, the issue of how to achieve secure surveillance has been driven by various research communities. Also, due to recent epidemic spread such as COVID-19, it is obvious that we should focus on how to manage a cooperative framework for possible future pandemic fights and allied medical services continuously. To support those purposes, it is anticipated that we can utilize AI-assisted communications and technologies using a variety of devices and equipment, including UAVs, mobile robots, and smart devices on the aerial and ground sides. In this article, an aerial-ground cooperative infrastructure is designed to study surveillance and epidemic prevention with managing energy recharge and AI-supported communications through collected or pre-knowledge information for public and private areas. Also, in the proposed architecture, we specify system settings, promising scenarios, and strategies in order to satisfy several objectives and tasks. Then possible research challenges and issues are addressed for successful realization and management of intelligent surveillance and efficient epidemic prevention

GeoSS: Geographic Segmentation Security Barriers for Virtual Emotion Detection With Discriminative Priorities in Intelligent Cooperative Vehicular System

A development of the integrated vehicular system through ground and aerial cooperation using intelligent mobile robots and smart UAVs is required to support various applications including intelligent transportation, secure service, surveillance reinforcement. Also, it is highly anticipated that the applicability of virtual emotion is expanded continuously in smart systems. In this paper, we introduce a geographic segmentation security barrier system for the purpose of secure surveillance through virtual emotion detection in intelligent cooperative vehicular area with mobile robots and UAVs. The proposed system is necessary to provide discriminative priorities in the requested cooperative vehicular area consisting of mobile robots and UAVs with rapid construction. Moreover, with ILP formulation, we formally defined a problem whose goal is to maximize a total number of geographic segmentation security barriers such that the completed establishment of those barriers is done by a specific group of mobile robots and UAVs within the requested various districts where they are divided according to differential security priorities. To solve the problem, we devise novel schemes to return the maximum number of geographic segmentation security barriers so that it pursues the maximization of system lifetime consequently. Then, the proposed approaches are implemented through expansive simulations and their performances based on numerical results are evaluated clearly

Flexible, Highly Efficient All-Polymer Solar Cells

All-polymer solar cells have shown great potential as flexible and portable power generators. These devices should offer good mechanical endurance with high power-conversion efficiency for viability in commercial applications. In this work, we develop highly efficient and mechanically robust all-polymer solar cells that are based on the PBDTTTPD polymer donor and the P(NDI2HD-T) polymeracceptor. These systems exhibit high power-conversion efficiency of 6.64%. Also, the proposed all-polymer solar cells have even better performance than the control polymer-fullerene devices with phenyl-C 61 -butyric acid methyl ester (PCBM) as the electron acceptor (6.12%). More importantly, our all-polymer solar cells exhibit dramatically enhanced strength and flexibility compared withpolymer/PCBM devices, with 60- and 470-fold improvements in elongation at break and toughness, respectively. The superior mechanical properties of all-polymer solar cells afford greater tolerance to severe deformations than conventional polymer-fullerene solar cells, making them much better candidates for applications in flexible and portable devices.ope

Exchange anisotropy and the dynamic phase transition in thin ferromagnetic Heisenberg films

Monte Carlo simulations have been performed to investigate the dependence of the dynamic phase behavior on the bilinear exchange anisotropy of a classical Heisenberg spin system. The system under consideration is a planar thin ferromagnetic film with competing surface fields subject to a pulsed oscillatory external field. The results show that the films exhibit a single discontinuous dynamic phase transition (DPT) as a function of the anisotropy of the bilinear exchange interaction in the Hamiltonian. Furthermore there is no evidence of stochastic resonance (SR) associated with the DPT. These results are in marked contrast to the continuous DPT observed in the same system as a function of temperature and applied field strength for a fixed bilinear exchange anisotropy.Comment: 11 pages including 3 figure pages; submitted to PR

Dynamic phase transitions in thin ferromagnetic films

Monte Carlo simulations have been used to investigate the dynamic phase behavior of a classical Heisenberg spin system with a bilinear exchange anisotropy in a planar thin film geometry. Studies of the field amplitude, frequency and temperature dependence show dynamic phase transitions in films subject to a pulsed oscillatory external field. Thin films with competing surface fields show separate and distinct dynamic phase transitions for the bulk and surface layers of the film. Between the two transitions, a mixed state with coexisting dynamically ordered and dynamically disordered phases is observed in the film. In contrast, the free film with no surface fields shows a single dynamic phase transition as in a bulk system.Comment: 25 pages including figures in pdf format, to be published in PR

Convex Hull Obstacle-Aware Pedestrian Tracking and Target Detection in Theme Park Applications

Barriers are utilized for various tasks in security, environmental monitoring, penetration detection and reconnaissance. It is highly necessary to consider how to support pedestrian tracking and target detection in theme park areas having multiple obstacles. In this paper, we create security barriers through cooperation between mobile robots and UAVs for use in theme park areas where multiple obstacles of undetermined forms are placed. We formally define the problem and the goals. The goals are the following: to maximize the number of convex hull obstacle-aware tracking barriers using mobile robots and UAVs, to satisfy given detection accuracy, and to ensure that all environments are protected by convex hull obstacle-aware tracking barriers without disturbance from irregular obstacles. To address the problem, we propose two different algorithms, to improve security barriers and avoid various forms of obstacles, in a bid to work towards a 6G-enabled virtual emotion environment. Then, the proposed schemes are executed through simulations with various settings, and the numerical results evaluated with detailed discussions and demonstrations

A Successive Epidemic Prevention Infrastructure Using Mobile Robots and Smart Devices in Intelligent Public Area

International audienc