An extremely wide-band tightly coupled dipole antenna array(TCDA) is presented. A novel balun is developed with a spoof surface plasmon polariton (SSPP) structure and a RC resonant circuits to ...achieve impedance matching and a conversion from unbalanced dipole feeding to balanced feeding. According to the simulation, the proposed TCDA demonstrates a remarkable 60:1 bandwidth (0.08GHz-4.83GHz) with VSWR<2.5. The overall array thickness is 0.03{{{\lambda }}}_{\text{low}} (where {{{\lambda }}}_{\text{low}} is the wavelength at the lowest frequency of operation, 80 MHz). The final array design consists of 12 dipole unit cells arranged in a one-dimensional configuration.
A compact integrated tri-band antenna for Sub-6GHz and millimeter wave (mmW) 5G mobile devices is developed. The antenna comprises a multiple-input-multiple-output (MIMO) antenna pair consisting of ...two symmetric inverted-F antenna (IFA) units and five split ring resonator antenna (SRRA) units. The inserted SRRA units serve the dual-purpose of forming a mmW array and mitigating mutual coupling among the IFA units at 3.5 GHz. The antenna covers a small area of 39.48 × 5.7 mm 2 and can operate in three bands: 3.29-3.79, 4.79-4.92 and 24.15-29.58 GHz. The tri-band antenna might be a promising choice for 5G mobile devices.
Droplets are ubiquitous microscopic systems - ranging in size from several nanometers to ~100 micrometers – that undergo abundant environmental interactions. Researchers have shown that droplets can ...impact both earth climate and air quality through physical and chemical processes. Droplets released from the human respiratory system, either suspended in air or deposited on surfaces, can carry pathogens (e.g., influenza viruses, the SARS-CoV-2 virus), and are thus important for disease transmission. The need to understand the role of droplets in environmental processes requires appropriate tools for droplet characterization. We used Raman and surface-enhanced Raman spectroscopy (SERS) based imaging as such tools due to their capacity for simultaneous collection of abundant molecular information inside droplets and their potential to collect detailed images of droplet component distributions. We imaged pH and chemical moiety distributions inside droplets over a wide range of: 1) droplet compositions; 2) surrounding environmental conditions (relative humidity, temperature); and 3) droplet morphologies. This dissertation describes measurement of droplet pH in droplets containing mixtures of phosphate buffer (PB), one of the most commonly used biological solvents, and ammonium sulfate (AS), arguably the most abundant chemical species in atmospheric droplets, at room temperature. We observed a pH gradient inside PB droplets while a homogeneous pH distribution was found inside AS droplets, thus showing a significant pH effect due to droplet composition. We attributed the contrasting pH distribution in the two droplet systems to different ionic interactions at the air-water interface. In addition, we obtained AS droplet images at 223K to investigate ice nucleation upon freezing. We observed variable nucleation behavior in AS droplets as a function of concentration, a finding with implications for atmospheric cloud nucleation. We also investigated virus deposition during sessile droplet evaporation using gold nanoparticles. SERS imaging enabled development of correlations between virus viability and droplet deposition pattern and related them in terms of the coffee-ring effect. Suppression of the coffee-ring effect can reduce virus infectivity on surfaces during droplet evaporation. These works collectively exhibit the potential of Raman and SERS imaging for droplet characterization.
Doctor of Philosophy
Droplets are ubiquitous in the environment. Small droplets can form clouds and fogs, and are often micro- to nano-scale in size. Droplets can either grow or shrink in the environment when they absorb or lose water. Similarly, reactions may happen when droplets contain various species. Droplets in human breath exhalate may contain pathogens, such as the SARS-CoV-2 virus that is the cause of the COVID-19 pandemic. If the virus stays viable in droplets, no matter where the droplets are located, the virus will remain infectious and may be transmitted to others through contact. The studies in this dissertation were conducted to determine the distributions of soluble and insoluble components inside droplets and to elucidate how the observed distributions correlate with important droplet properties and environmental processes. We used two methods to observe droplets: Raman spectroscopy and surface-enhanced Raman spectroscopy (SERS). Molecules are constantly vibrating, these vibrations result in characteristic Raman signals that can be monitored. Both Raman and SERS provide such measurements, except that SERS has greater sensitivity due to the signal enhancement provided by gold or silver nanoparticles. In this dissertation, we obtained images of droplets with variable compositions at both room temperature and -50 °C. We also examined virus survival inside droplets during droplet drying. Using the collected images, we related the component distribution inside a droplet to its acidity, and evaluated virus survival in terms of droplet drying patterns. The images demonstrate that Raman and SERS imaging are promising tools for the study of droplets.
OPPO as a young Chinese mobile phone brand, it has to tackle many difficulties to survive in the competitive Red Sea of mobile industry, such as: lack of innovation of technology and core chips, ...short of complete product supply chain. All these factors may restrict and limit the further development of OPPO. The purpose of this paper is to examine and analyse how could OPPO find a way out of the competitive mobile industry. By researching the previous data, questionnaire for the public, and analysing the previous strategies of OPPO. Eventually we will provide some suggestions and idea for OPPO to tackle those problems and would benefit OPPO in the long-term.
This dissertation defines for the first time the concept of "one-sided" control of multivariate variability of a multiple quality characteristic X. Two control schemes are proposed for monitoring ...Cov(X). One scheme is of Shewhart type. Assuming the least acceptable covariance matrix is I without loss of generality, the statistic to be plotted is the squared sum of the distances between the observations and the target value of X. Although the statistic is derived under the assumption of normality, it is still quite meaningful in any other reasonable circumstances. In fact, the performance of the scheme appears satisfactory when X is Pearson II and VII. The other scheme is a sequential scheme. The statistic is the cumulative sum of the statistics described in the Shewhart scheme to date. Compared to the Shewhart scheme, the sequential scheme detects small and moderately large shifts much faster, but very large shifts slightly slower. This statement is still valid when X has Pearson type II and VII distributions.
Continuing previous work on effects of errors in inspection on group sampling schemes, a modification of Dorfman-Sterrett schemes is studied. The modification consists of reversion to group sampling ...when a specified number of decisions of nonconformance have occurred in the course of inspection of individual items.
The fast detection of classical contaminants and their distribution on high-voltage transmission line insulators is essential for ensuring the safe operation of the power grid. The analysis of ...existing insulator contamination has traditionally relied on taking samples during a power cut, taking the samples back to the lab and then testing them with elemental analysis equipment, especially for sugars, bird droppings, and heavy metal particulates, which cannot be analysed by the equivalent salt deposit density (ESDD) or non-soluble deposit density (NSDD) methods. In this study, a novel method called laser-induced breakdown spectroscopy (LIBS) offering the advantages of no sample preparation, being nearly nondestructive and having a fast speed was applied for the analysis of metal contamination. Several LIBS parameters (laser energy and delay time) were optimized to obtain better resolution of the spectral data. The limit of detection (LOD) of the observed elements was obtained using a calibration curve. Compared to calibration curves, multivariate analysis methods including principal component analysis (PCA), k-means and partial least squares regression (PLSR) showed their superiority in analyzing metal contamination in insulators. Then, the elemental distribution of natural pollution was predicted using LIBS to fully capture information about the bulk elements (Na, Ni, Cu, Mn, Ca, etc.) of entire areas with PLSR. The results showed that LIBS could be a promising method for accurate direct online quantification of metal contamination in insulators.
The aim of generative adversarial imitation learning (GAIL) is to allow an agent to learn an optimal policy from demonstrations via an adversarial training process. However, previous works have not ...considered a realistic setting for complex continuous control tasks such as robot manipulation, in which the available demonstrations are imperfect and possibly originate from different policies. Such a setting poses significant challenges for the application of the GAIL-related methods. This paper proposes a novel imitation learning (IL) algorithm, MD2-GAIL, to enable an agent to learn effectively from imperfect demonstrations by multiple demonstrators. Instead of training the policy from scratch, unsupervised pretraining is used to speed up the adversarial learning process. Confidence scores representing the quality of the demonstrations are utilized to reconstruct the objective function for off-policy adversarial training, making the policy match the optimal occupancy measure. Based on the Soft Actor Critic (SAC) algorithm, MD2-GAIL incorporates the idea of maximum entropy into the process of optimizing the objective function. Meanwhile, a reshaped reward function is adopted to update the agent policy to avoid falling into local optima.Experiments were conducted based on robotic simulation tasks, and the results show that our method can efficiently learn from the available demonstrations and achieves better performance than other state-of-the-art methods.
The direct conversion of syngas to ethanol using CuZnAl catalysts is very challenging. In this paper, CuZnAl@S-1, CuZn@S-1, ZnAl@S-1, and CuAl@S-1 catalysts were prepared using a solid-phase method ...to prepare silicate-1 molecular sieves with Cu, Zn, and Al components encapsulated in them, and their catalytic performance for CO hydrogenation was evaluated in a fixed-bed reaction. The structural and surface properties of the catalysts were characterized using X-ray diffraction, transmission electron microscopy, N2 physisorption, and X-ray photoelectron spectroscopy and correlated with the catalytic performance. The results showed that the use of structurally simple S-1 immobilized CuZnAI nanoparticles (CZA@S-1) was effective in enhancing the conversion of ethanol, where C2+OH/ROH up to 50.63% and ROH selectivity up to 27.27% were achieved, and no deactivation was observed within six days. The characterization results indicate that the interaction between CuZn in the CZA@S-1 catalysts is stronger than that between CuAl and ZnAl, that the CuZn active component is able to supply electrons to the molecular sieve, and that the core–shell structure promotes the adsorption and dissociation of CO and enhances C–C coupling. In situ diffuse reflectance infrared Fourier transform spectroscopy measurements of the reaction intermediates for each catalyst inferred a pathway for C–C coupling to ethanol, which provides an alternative pathway to the CuZnAl conventional catalyst.
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