Optical engineering of iii-nitride nanowire light-emitting diodes and applications

Applications of III-nitride nanowires are intensively explored in different emerging technologies including light-emitting diodes (LEDs), laser diodes, photodiodes, biosensors, and solar cells. The synthesis of the III-nitride nanowires by molecular beam epitaxy (MBE) is investigated with significant achievements. III-nitride nanowires can be grown on dissimilar substrates i.e., silicon with nearly dislocation free due to the effective strain relaxation. III-nitride nanowires, therefore, are perfectly suited for high performance light emitters for cost-effective fabrication of the advanced photonic-electronic integrated platforms. This dissertation addresses the design, fabrication, and characterization of III-nitride nanowire full-color micro-LED (µLED) on silicon substrates for µLED display technologies, high-efficient ultraviolet (UV) LEDs, and spectral engineering for narrow band LEDs. In this dissertation, InGaN/AlGaN nanowire µLEDs were demonstrated with highly stable emission which can be varied from the blue to red spectrum. Additionally, by integrating full-color emissions in a single nanowire, phosphor-free white-color µLEDs are achieved with an unprecedentedly high color rendering index of ~ 94. Such high-performance µLEDs are perfectly suitable for the next generation high-resolution micro-display applications. Moreover, the first demonstration of two-step surface passivation using Potassium Hydroxide (KOH) and Ammonium Sulfide (NH4)2Sx is reported. The photoluminescence, electroluminescence, and optical power of the 335 nm AlGaN nanowire UV LEDs show improvements by 49%, 83%, and 65%, respectively. Such enhanced performance is attributed to the mitigation of the surface nonradiative recombination on the nanowire surfaces. A combination of KOH and (NH4)2Sx treatment shows a promising approach for high efficiency and high power AlGaN nanowire UV LEDs. The LEDs with narrow spectra are highly desirable light sources for precisely controlled applications such as phototherapy. In this regard, we have further demonstrated narrow spectral nanowire LEDs using on-chip integrated bandpass filters. To achieve narrow band spectra, the bandpass filters are designed and fabricated using all-dielectric and metal-dielectric multilayers for visible and UV regions, respectively. They are fabricated onto LED devices as a single photonic platform to achieve the narrow band LEDs for innovative applications like phototherapy for wound healing

OPTIMIZATION OF CONDITIONS FOR CAROTENOIDS EXTRACTION FROM SHRIMP WASTE USING ORGANIC SOLVENT

In this study, factors affecting the extraction yield of carotenoids from dry shrimp waste by organic solvents such as ratio of hexane / acetone, ratio of solvent / shrimp waste, extraction temperature, extraction time, extraction method such as dynamic or static have been studied. The results showed that the solvent ratio hexane: acetone = 3: 1 gave the highest carotenoid yield. In this ratio of solvent’s mixture, the yield reached highest at temperature 60 °C for 2 hours, which was 44,64 µg / g raw shrimp waste (d.b.) (ratio of solvent to raw material 3/1). Ultrasound or vortexing gave higher extraction yield than in static conditions, which was 1.5- to 1.8- fold increase, respectively. At the ratio of solvent: dried shrimp = 4: 1, the amount of carotenoid recovered at 60°C for 2 hours reached 57.4 µg / g. However, if the shrimp waste was hydrolyzed with Alcalase at 50°C for 4 hours before extraction by solvent, the amount of carotenoid recovered achieved 149 µg / g of raw materia

Seismic data conditioning, attribute analysis, and machine-learning facies classification: applications to Texas panhandle, Australia, New Zealand, and Gulf of Mexico

Whether analyzed by a human interpreter or by a machine learning algorithm, 3D seismic interpretation is only as good as the data that goes into it. The goal of seismic processing is to minimize noise and enhance signal to provide the most accurate image of the subsurface. Once imaged, the resulting migrated data volume can be further enhanced to suppress random and cross-cutting coherent noise and to better balance the spectrum to improve vertical resolution. Next, seismic attributes enhance subtle geologic features that may be otherwise overlooked. At this point, skilled human interpreters are very adept at not only seeing patterns in the data, but also in constructing correlations in their brain between multiple attributes and geologic features of interest. Machine learning algorithms are not yet at this point. Several machine learning algorithms require, and many perform better on data that exhibit Gaussian statistics, such that we need to carefully scale the attribute volumes to be analyzed. The application of filters that block and smooth the attribute volume, mimicking what a human interpreter “sees” provide further improvements. In this dissertation, I address most of these data conditioning challenges, as well as adapting and recoding the machine learning algorithms themselves. Conventional imaging of the shallow targets often results in severe migration aliasing. To improve the interpretation of a shallow fractured-basement reservoir in the Texas Panhandle, I developed a data conditioning technique called constrained conjugate-gradient least-squares migration to the prestack unmigrated data of the study area. I found that constrained conjugate-gradient least-squares migration can increase the signal-to-noise ratio, suppress migration artifacts, and improve seismic inversion results. Although 3D seismic surveys are routinely acquired, in frontier areas, much of our data consist of a grid of 2D seismic lines. Few publications discuss the application and limitations of modern seismic attributes to 2D lines, and fewer still the application of machine learning. I used a grid of 2D lines acquired over a turbidite channel system and carbonate sequences in the Exmouth Plateau, North Carnarvon Basin, Australia, to address this question. First, I modified 3D data conditioning workflows including nonlinear spectral balancing and structure-oriented filtering, and found that spectral balancing followed by structure-oriented filtering provides superior results. All of the more common attributes perform well, but with analysis of 2D lines providing apparent dip and apparent curvature in the inline direction rather than true dip magnitude and azimuth, and most-positive and most-negative curvature and their strikes. I analyzed coherence, curvature, reflector convergence, and envelope attributes using self-organizing maps and was able to successfully map turbidite canyon, carbonate mounds, and mass-transport complexes (MTCs) in the study area. Although some attributes exhibit Gaussian statistics, most do not. Although many machine learning algorithms are based on Gaussian statistics, most applications apply a simple Z-score normalization. I therefore compared the results of seismic facies classification of a Canterbury Basin turbidite system when using the traditional Z-score normalization versus one I developed that addresses skewness, kurtosis, and other scaling features in the attribute histogram. I found that logarithmic normalizations of skewed distributions are better input to unsupervised PCA, ICA, SOM, and GTM classification algorithms, but are worse for the supervised learning PNN classification algorithm. In contrast, supervised classification benefits greatly from a class-dependent normalization scheme, where the training data are normalized differently for each class

Avoid Deadlock Resource Allocation (ADRA) Model V VM-out-of-N PM: Avoid Deadlock Resource Allocation (ADRA) Model V VM-out-of-N PM

This paper presents an avoid deadlock resource allocation (ADRA) for model V VM-out-of-N PM since cloud computing is a new computing paradigm composed of grid computing, distributed computing and utility concepts. Cloud computing presents a different resource allocation paradigm than either grids or distributed systems. Cloud service providers dynamically scale virtualized computing resources as a service over the internet. Due to variable number of users and limited resources, cloud is prone to deadlock at very large scale. Resource allocation and the associated deadlock avoidance is problem originated in the design and the implementation of the distributed computing, grid computing. In this paper, a new concept of free space cloud is proposed to avoid deadlock by collecting available free resource from all allocated users. New algorithms are developed for allocating multiple resources to competing services running in virtual machines on a heterogeneous distributed platform.  An experiment is tested in CloudSim. The performance of resource pool manager is evaluated by using CloudSim and resource utilization and indicating good results

Short shots and industrial case studies: Understanding fluid flow and solidification in high pressure die casting

AbstractThe geometric complexity and high fluid speeds involved in high pressure die casting (HPDC) combine to give strongly three dimensional fluid flow with significant free surface fragmentation and splashing. A simulation method that has proved particularly suited to modelling HPDC is Smoothed Particle Hydrodynamics (SPH). Materials are approximated by particles that are free to move around rather than by fixed grids, enabling more accurate prediction of fluid flows involving complex free surface motion. Three practical industrial case studies of SPH simulated HPDC flows are presented; aluminium casting of a differential cover (automotive), an electronic housing and zinc casting of a door lock plate. These show significant detail in the fragmented fluid free surfaces and allow us to understand the predisposition to create defects such as porosity in the castings. The validation of flow predictions coupled with heat transfer and solidification is an important area for such modelling. One powerful approach is to use short shots, where insufficient metal is used in the casting or the casting shot is halted part way through, to leave the die cavity only partially filled. The frozen partial castings capture significant detail about the order of fill and the flow structures occurring during different stages of filling. Validation can occur by matching experimental and simulated short shots. Here we explore the effect of die temperature, metal super-heat and volume fill on the short shots for the casting of a simple coaster. The bulk features of the final solid castings are found to be in good agreement with the predictions, but the fine details appear to depend on surface behaviour of the solidifying metals. This potentially has significant implications for modelling HPDC

Determinants Influencing Consumers’ Attitude Towards Online Shopping: An Extension of the Technology Acceptance Model

This research is conducted for investigating determinants influencing consumers’ attitude towards online shopping. The survey was based on 423 Vietnamese Internet users. Data collected was analyzed in accordance with the process from Cronbach's Alpha to EFA and multiple regression technique. The results show that consumers’ attitude towards online shopping was impacted by perceived usefulness, compatibility and trust. Based on the findings, some recommendations are given for retailers to improve customers’ attitude toward online shopping in the context of Vietnam in particular and in emerging countries in general. Keywords: Attitude, Online shopping, Perceived usefulness, Trust

Teachers’ perception of the necessity of applying online applications for organizing teaching activities at high school in Vietnam

E-learning has gained popularity as a method of delivering education recently and offers many advantages to enhance the learning experience for students. Technology allows teachers to design more interactive and engaging lessons that cater to different learning styles. It can also provide opportunities for teachers to incorporate virtual simulations and real-time data which can help students better understand complex concepts. The total number of survey samples was 187 teachers. Awareness of the need and purpose of applying information literacy in the organization of teaching activities was created to analyze. The results of the findings were interpreted in three ways: (i) Self-assessment of teachers’ competence in applying technology in organizing teaching activities.  (ii) Awareness of the necessity of using online applications in organizing teaching activities in schools.  (iii) Awareness of the goal of using online applications in the organization of teaching activities. Based on the results of the current study, the article establishes the process of applying online applications in the organization of teaching activities and proposes recommendations for subjects directly related to the application of online applications. High school administrators, teachers and educational management agencies at all levels are using online innovation to organize teaching activities in high schools

Welfare consequences of inconsistent monetary policy implementation in Vietnam

We develop a New Keynesian model featuring Calvo price setting and Calvo wage setting to quantify the welfare consequences of shifting trend inflation in Vietnam. To capture the characteristics of the Vietnamese economy, we use the Simulated Method of Moment and calibrate parameters jointly to match the important selected moments of Vietnamese data. The results show a severe consequence of a constant positive trend inflation and an exogenous shock to trend inflation, especially when a central bank sets a high level of inflation target. Among staggered price and wage contracts, the latter play a vital role in transmitting the adverse impacts of constant and shifting trend inflation into the economy. Based on our analyses, raising inflation targets would seem to be a bad policy prescription in Vietnam

Effects of R&D, networking and leadership roles on environmental innovation adoption in Vietnam’s SMEs

Although small and medium-sized enterprises (SMEs) constitute a majority of firms, they still have little knowledge about environmental issues and generally encounter difficulties when integrating environmental aspects into their activities. Similar arguments are also highlighted by Ha et al. in the case of Vietnam. This paper, therefore, builds a guideline for promoting SMEs’ organisational environmental innovation adoption based on Environmental Standard Certification (ESC) by investigating the effects of R&D, networking, and leadership roles in Vietnam. By using SME survey data in Vietnam from 2011 to 2015, the empirical results show that R&D spending and organisational capabilities proxied by already owning ESC are positively associated with green innovation implementation. We also find that either collaboration with different partners, including competitors, banks, and public agents or communication networks, affects firms’ decisions on green innovations. The demographic characteristics of managers such as gender, educational level, and knowledge about the environmental laws play determining roles in these decisions. Finally, we advanced the literature by indicating the moderating effects of men in leadership roles and leaders with better related knowledge on the impacts of firms’ internal resources (R&D) and firms’ international orientation (export)