Optically Transparent Tri-Wideband Mosaic Frequency Selective Surface with Low Cross-Polarisation

Acquiring an optically transparent feature on the wideband frequency selective surface (FSS), particularly for smart city applications (building window and transportation services) and vehicle windows, is a challenging task. Hence, this study assessed the performance of optically transparent mosaic frequency selective surfaces (MFSS) with a conductive metallic element unit cell that integrated Koch fractal and double hexagonal loop fabricated on a polycarbonate substrate. The opaque and transparent features of the MFSS were studied. While the study on opaque MFSS revealed the advantage of having wideband responses, the study on transparent MFSS was performed to determine the optical transparency application with wideband feature. To comprehend the MFSS design, the evolutionary influence of the unit cell on the performance of MFSS was investigated and discussed thoroughly in this paper. Both the opaque and transparent MFSS yielded wideband bandstop and bandpass responses with low cross-polarisation (−37 dB), whereas the angular stability was limited to only 25°. The transparent MFSS displayed high-level transparency exceeding 70%. Both the simulated and measured performance comparison exhibited good correlation for both opaque and transparent MFSS. The proposed transparent MFSS with wideband frequency response and low cross-polarisation features signified a promising filtering potential in multiple applications.

Defluoridation performance comparison of aluminum hydroxides with different crystalline phases

Aluminum hydroxide is an eye catching and extensively researched adsorbent for fluoride removal and its defluoridation performance is closely related to the preparation method and crystalline phase. In this research, the defluoridation performances of aluminum hydroxides with different crystalline phases are compared and evaluated in terms of fluoride removal capacity, sensitivity to pH values and residual Al contents after defluoridation. It is found that the defluoridation performance of different aluminum hydroxides follows the order of boehmite > bayerite > gibbsite. The fluoride adsorption on aluminum hydroxides follows pseudo-second-order kinetic model and Langmuir isotherm model, and the maximum defluoridation capacities of boehmite, bayerite and gibbsite are 42.08, 2.97 and 2.74 mg m−2, respectively. The pH values and FTIR analyses reveal that the ligand exchange between fluoride and surface hydroxyl groups is the fluoride removal mechanism. Different aluminum hydroxides have different surface hydroxyl group densities, which results in the different defluoridation capacities. This work provides a new idea to prepare aluminum hydroxide with outstanding defluoridation performance.

Enabling continuous connectivity services for ambrosus blockchain application by incorporating 5G-multilevel machine learning orchestrations

Most revolutionary applications extending far beyond smartphones and high configured mobile device use to the future generation wireless networks’ are high potential capabilities in recent days. One of the advanced wireless networks and mobile technology is 5G, where it provides high speed, better reliability, and amended capacity. 5 G offers complete coverage, which is accommodates any IoT device, connectivity, and intelligent edge algorithms. So that 5 G has a high demand in a wide range of commercial applications. Ambrosus is a commercial company that integrates block-chain security, IoT network, and supply chain management for medical and food enterprises. This paper proposed a novel framework that integrates 5 G technology, Machine Learning (ML) algorithms, and block-chain security. The main idea of this work is to incorporate the 5 G technology into Machine learning architectures for the Ambrosus application. 5 G technology provides continuous connection among the network user/nodes, where choosing the right user, base station, and the controller is obtained by using for ML architecture. The proposed framework comprises 5 G technology incorporate, a novel network orchestration, Radio Access Network, and a centralized distributor, and a radio unit layer. The radio unit layer is used for integrating all the components of the framework. The ML algorithm is evaluated the dynamic condition of the base station, like as IoT nodes, Ambrosus users, channels, and the route to enhance the efficiency of the communication. The performance of the proposed framework is evaluated in terms of prediction by simulating the model in MATLAB software. From the performance comparison, it is noticed that the proposed unified architecture obtained 98.6% of accuracy which is higher than the accuracy of the existing decision tree algorithm 97.1% .