Reconfigurable Pattern Patch Antenna for Mid-Band 5G: A Review

New requirements in communication technologies make it imperative to rehash conventional features such as reconfigurable antennas to adapt with the future adaptability advancements. This paper presents a comprehensive review of reconfigurable antennas, specifically in terms of radiation patterns for adaptation in the upcoming Fifth Generation (5G) New Radio frequency bands. They represent the key of antenna technology for materializing a high rate transmission, increased spectral and energy efficiency, reduced interference, and improved the beam steering and beam shaping, thereby land a great promise for planar antennas to boost the mid-band 5G. This review begins with an overview of the underlying principals in reconfiguring radiation patterns, followed by the presentations of the implemented innovative antenna topologies to suit particular advanced features. The various adaptation techniques of radiation pattern reconfigurable planar antennas and the understanding of its antenna design approaches has been investigated for its radiation pattern enhancement. A variety of design configurations have also been critically studied for their compatibilities to be operated in the mid-band communication systems. The review provides new insights on pattern reconfigurable antenna where such antennas are categorized as beam steering antenna and beam shaping antennas where the operation modes and purposes are clearly investigated. The review also revealed that for mid-band 5G communication, the commonly used electronic switching such as PIN diodes have sufficient isolation loss to provide the required beam performance.     

Modelling of heat transfer for progressive freeze concentration process by spiral finned crystallizer

This study presents a novel design for a spiral finned crystallizer which is the primary element of progressive freeze concentration (PFC) system,which simplifies the setup of the conventional system.After the crystallizer has been designed,the research experiments have been conducted and evaluated through a thorough analysis of its performance by developing a mathematical model that can be used to predict the productivity of ice crystal at a range of coolant temperature.The model is developed based on the basic heat transfer equation,and by considering the solution's and the coolant's convective heat transfer coefficient (h) under the forced flow condition.The model's accuracy is verified by making comparison between the ice crystal mass' experimental value and the values predicted by the model.Conseouentiv,the study found that the model helos in enhancing the PFC system.     

A Frequency-Reconfigurable Microstrip Antenna with Constant Dipole-Like Radiation Patterns Using Single Bias,Triple Varactor Tuning with Reduced Complexity

Wireless Personal Communications - This work proposes a novel frequency-reconfigurable circular patch antenna incorporated with a rectangular slot and a narrow slot capable of producing constant...     

Tailoring the Silica Amount in Stabilizing the Tetragonal Phase of Zirconia for Enhanced Photodegradation of 2-Chlorophenol

Topics in Catalysis - A simple microwave method was employed to prepare silica-doped mesoporous zirconia nanoparticles, SiO2/ZrO2 (SiZr) catalysts under various Si amount and then characterized by...     

Optimizing ANN models with PSO for predicting short building seismic response

The present study aimed to optimize the artificial neural network (ANN) with one of the well-established optimization algorithms called particle swarm optimization (PSO) for the problem of ground...     

The effect of crosslinker on mechanical and morphological properties of tropical wood material composites

In this study, wood polymer composites (WPCs) based on five kinds of selected tropical wood species, namely Jelutong (Dyera costulata), Terbulan (Endospermum diadenum), Batai (Paraserianthes moluccana), Rubber (Hevea brasiliensis), and Pulai (Alstonia pneumatophora), were impregnated with methyl methacrylate (MMA) and hexamethylene diisocyanate (HMDIC) monomers mixture in the ratio of 1:1 for composite manufacturing. All these tropical wood reacted with hexamethylene diisocyanate and crosslinked with MMA which enhanced the hydrophobic (restrained water) nature of wood. The vacuum-pressure method was used to impregnate the samples with monomer mixture. The monomer mixture loading achievable was found to be dependent on the properties of wood species. Low loading was observed for the high density wood species. Mechanical strength of fabricated wood polymer composites (WPCs) in term of modulus of elasticity (MOE) and modulus of rupture (MOR) were found to be significantly improved. The wood–polymer interaction was confirmed by Fourier transform infrared (FTIR) spectroscopy. Morphological properties of raw wood and WPC samples were evaluated by scanning electron microscopy (SEM) and XRD analysis and an improvement in morphological properties was also observed for WPC.     

Optimization of ANFIS with GA and PSO estimating α ratio in driven piles

This study aimed to optimize Adaptive Neuro-Fuzzy Inferences System (ANFIS) with two optimization algorithms, namely, Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) for the calculation friction capacity ratio (α) in driven shafts. Various studies are shown that both ANFIS are valuable methods for prediction of engineering problems. However, optimizing ANFIS with GA and PSO has not been used in the area of pile engineering. The training data set was collected from available full-scale results of the driven piles. The input parameters used in this study were pile diameter (m), pile length (m), relative density (I_d), embedment ratio (L/D), both of the pile end resistance (q_c) and base resistance at relatively 10% base settlement (q_b0.1) from CPT result, whereas the output was α. A learning fuzzy-based algorithm was used to train the ANFIS model in the MATLAB software. The system was optimized by changing the number of clusters in the FIS and then the output was used for the GA and PSO optimization algorithm. The prediction was compared with the real-monitoring field data. As a result, good agreement was attained representing reliability of all proposed models. The estimated results for the collected database were assessed based on several statistical indices such as R², RMSE, and VAF. According to R², RMSE, and VAF, values of (0.9439, 0.0123 and 99.91), (0.9872, 0.0117 and 99.99), and (0.9605, 0.0119 and 99.97) were obtained for testing data sets of the optimized ANFIS, GA–ANFIS, and PSO–ANFIS predictive models, respectively. This indicates higher reliability of the optimized GA–ANFIS model in estimating α ratio in driven shafts.

     

Easy removing of phenol from wastewater using vegetable oil-based organic solvent in emulsion liquid membrane process

Phenol is considered as pollutant due to its toxicity and carcinogenic effect.Thus,variety of innovative methods for separation and recovery of phenolic compounds is developed in order to remove the unwanted phenol from wastewater and obtain valuable phenolic compound.One of potential method is extraction using green based liquid organic solvent.Therefore,the feasibility of using palm oil was investigated.In this research,palm oil based organic phase was used as diluents to treat a simulated wastewater containing 300×10~(-6) of phenol solution using emulsion liquid membrane process(ELM).The stability of water-in-oil(W/O) emulsion on diluent composition and the parameters affecting the phenol removal efficiency and stability of the emulsion;such as emulsification speed,emulsification time,agitation speed,surfactant concentration,pH of external phase,contact time,stripping agent concentration and treat ratio were carried out.The results of ELM study showed that at ratio7 to 3 of palm oil to kerosene,5 min and 1300 r·min~(-1) of emulsification process the stabile primary emulsion were formed.Also,no carrier is needed to facilitate the phenol extraction.In experimental conditions of500 r·min~(-1) of agitation speed,3%Span 80,pH 8 of external phase,5 min of contact time,0.1 mol·L~(-1) NaOH as stripping agent and 1:10 of treat ratio,the ELM process was very promising for removing the phenol from the wastewater.The extraction performance at about 83%of phenol was removed for simulated wastewater and an enrichment of phenol in recovery phase as phenolate compound was around 11 times.