COST EFFECTIVENESS ANALYSES OF RADIATION THERAPY TREATMENTS

The impact of radiation therapy in cancer treatments has shown great improvement in clinical outcomes. Recent radiation therapy advances with innovative technologies have changed the standard of care in cancer treatments rapidly. Evolution in radiation therapy has demanded highly specialized trained resources and comes at substantial increase in cost. Even though evidence based treatments have demonstrated the important role of advanced radiation therapy technologies in various cancer treatments, the sustainability of quality healthcare in an increasingly resource constrained environment has been ongoing challenge. Therefore, economic evaluation for new treatment technologies has been requested to make the most effective use of resources. In this dissertation, we evaluated cost effectiveness analysis (CEA) for various disease sites with innovative technologies. First, we conducted CEA of 3-dimensional (3D) image guided brachytherapy (IGBT) compared to conventional 2-dimensional (2D) high dose rate (HDR) brachytherapy for the treatment of locally advanced cervical cancer. We found that 3D IGBT is a cost effective strategy compared to 2D HDR brachytherapy with a willingness to pay (WTP) threshold of $50,000/quality adjusted life years (QALY) gained, strongly supporting the routine use of 3D image guided brachytherapy. Second, we performed a CEA of single fraction of stereotactic body radiation therapy (SBRT) compared with single fraction of external beam radiation therapy (EBRT) for palliation of vertebral bone metastases. We found that SBRT is not a cost effective treatment strategy compared to conventional EBRT with a WTP threshold of$100,000/QALY gained in patients with relatively short life expectancy. Finally, we performed a CEA of stereotactic body radiation therapy (SBRT) compared to radiofrequency ablation (RFA) for inoperable colorectal liver metastases. We found that SBRT is not cost effective compared to RFA with a WTP of $100,000/QALY gained unless large tumor size is treated. In summary, given increasing attention placed on healthcare costs, a cost-effectiveness analysis can provide the appropriate platform to compare these treatment options. Therefore, the findings from the papers in this dissertation will identify the proper treatment choice to improve clinical outcomes at a reasonable cost, incorporating economic considerations into clinical decision making

Indoor Propagation of Electromagnetic Waves with Orbital Angular Momentum at 5.8 GHz

Propagation of electromagnetic waves with orbital angular momentum (OAM) is investigated in indoor environments. The OAM modes generated by circular patch array antennas are used. With proper alignment and suppressed multipath, the OAM modes can transport multiple wireless data stream at the same time. Through measurements and ray-tracing simulations, it is found that the advantages of OAM modes are limited if those two conditions are not satisfied. It is also found that multipath effect can be enervated by using narrow beam antennas

SuperNet in Neural Architecture Search: A Taxonomic Survey

Deep Neural Networks (DNN) have made significant progress in a wide range of visual recognition tasks such as image classification, object detection, and semantic segmentation. The evolution of convolutional architectures has led to better performance by incurring expensive computational costs. In addition, network design has become a difficult task, which is labor-intensive and requires a high level of domain knowledge. To mitigate such issues, there have been studies for a variety of neural architecture search methods that automatically search for optimal architectures, achieving models with impressive performance that outperform human-designed counterparts. This survey aims to provide an overview of existing works in this field of research and specifically focus on the supernet optimization that builds a neural network that assembles all the architectures as its sub models by using weight sharing. We aim to accomplish that by categorizing supernet optimization by proposing them as solutions to the common challenges found in the literature: data-side optimization, poor rank correlation alleviation, and transferable NAS for a number of deployment scenarios

Detailed Human-Centric Text Description-Driven Large Scene Synthesis

Text-driven large scene image synthesis has made significant progress with diffusion models, but controlling it is challenging. While using additional spatial controls with corresponding texts has improved the controllability of large scene synthesis, it is still challenging to faithfully reflect detailed text descriptions without user-provided controls. Here, we propose DetText2Scene, a novel text-driven large-scale image synthesis with high faithfulness, controllability, and naturalness in a global context for the detailed human-centric text description. Our DetText2Scene consists of 1) hierarchical keypoint-box layout generation from the detailed description by leveraging large language model (LLM), 2) view-wise conditioned joint diffusion process to synthesize a large scene from the given detailed text with LLM-generated grounded keypoint-box layout and 3) pixel perturbation-based pyramidal interpolation to progressively refine the large scene for global coherence. Our DetText2Scene significantly outperforms prior arts in text-to-large scene synthesis qualitatively and quantitatively, demonstrating strong faithfulness with detailed descriptions, superior controllability, and excellent naturalness in a global context

Investigating key attributes in experience and satisfaction of hotel customer using online review data

© 2019 by the authors. Licensee MDPI, Basel, Switzerland. With the development of social media, customers are sharing their experiences, and it is rapidly spreading as a form of online review. That is why the online review has become a significant information source affecting customers\u27 purchase intention and behavior. Therefore, it is important to understand the customer\u27s experience shown in the online review in order to maintain sustainable customer satisfaction and loyalty. The purpose of this study is to investigate what are the key attributes and the structural relationship of those key attributes. To accomplish this purpose, a total of 6596 hotel reviews were collected from Google (google.com). A frequency analysis using text mining was performed to figure out the most frequently mentioned attributes. In addition, semantic network analysis, factor analysis, and regression analysis were applied to understand the experience and satisfaction of the hotel customer. As a result, the top 99 keywords were divided into four groups such as Intangible Service , Physical Environment , Purpose , and Location . The factor analysis reduced the dimension of the original 64 keywords to 22 keywords, and grouped them into five factors, which are Access , F&B (Food and Beverage) , Purpose , Tangibles , and Empathy . Based on these results, theoretical and practical implications for sustainable hotel marketing strategies are suggested

A Study on Knowledge Distillation from Weak Teacher for Scaling Up Pre-trained Language Models

Distillation from Weak Teacher (DWT) is a method of transferring knowledge from a smaller, weaker teacher model to a larger student model to improve its performance. Previous studies have shown that DWT can be effective in the vision domain and natural language processing (NLP) pre-training stage. Specifically, DWT shows promise in practical scenarios, such as enhancing new generation or larger models using pre-trained yet older or smaller models and lacking a resource budget. However, the optimal conditions for using DWT have yet to be fully investigated in NLP pre-training. Therefore, this study examines three key factors to optimize DWT, distinct from those used in the vision domain or traditional knowledge distillation. These factors are: (i) the impact of teacher model quality on DWT effectiveness, (ii) guidelines for adjusting the weighting value for DWT loss, and (iii) the impact of parameter remapping as a student model initialization technique for DWT.Comment: Findings of ACL 202

Codon usage patterns of LT-Ag genes in polyomaviruses from different host species

Background Polyomaviruses (PyVs) have a wide range of hosts, from humans to fish, and their effects on hosts vary. The differences in the infection characteristics of PyV with respect to the host are assumed to be influenced by the biochemical function of the LT-Ag protein, which is related to the cytopathic effect and tumorigenesis mechanism via interaction with the host protein. Methods We carried out a comparative analysis of codon usage patterns of large T-antigens (LT-Ags) of PyVs isolated from various host species and their functional domains and sequence motifs. Parity rule 2 (PR2) and neutrality analysis were applied to evaluate the effects of mutation and selection pressure on codon usage bias. To investigate evolutionary relationships among PyVs, we carried out a phylogenetic analysis, and a correspondence analysis of relative synonymous codon usage (RSCU) values was performed. Results Nucleotide composition analysis using LT-Ag gene sequences showed that the GC and GC3 values of avian PyVs were higher than those of mammalian PyVs. The effective number of codon (ENC) analysis showed host-specific ENC distribution characteristics in both the LT-Ag gene and the coding sequences of its domain regions. In the avian and fish PyVs, the codon diversity was significant, whereas the mammalian PyVs tended to exhibit conservative and host-specific evolution of codon usage bias. The results of our PR2 and neutrality analysis revealed mutation bias or highly variable GC contents by showing a narrow GC12 distribution and wide GC3 distribution in all sequences. Furthermore, the calculated RSCU values revealed differences in the codon usage preference of the LT-AG gene according to the host group. A similar tendency was observed in the two functional domains used in the analysis. Conclusions Our study showed that specific domains or sequence motifs of various PyV LT-Ags have evolved so that each virus protein interacts with host cell targets. They have also adapted to thrive in specific host species and cell types. Functional domains of LT-Ag, which are known to interact with host proteins involved in cell proliferation and gene expression regulation, may provide important information, as they are significantly related to the host specificity of PyVs.This work was supported by a grant from the National Research Foundation of Korea funded by the Korea government (MSIP) (No. 2016R1C1B2015511) and the Ministry of Education (No. 2017R1D1A1B03033413)