352 research outputs found
Simplified information geometry approach for massive MIMO-OFDM channel estimation - Part II: Convergence analysis
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Convergence condition of simplified information geometry approach for massive MIMO-OFDM channel estimation
No full textMacro Analysis on Apple Stock In order to determine investment value of Apple
Get PDFThe purpose of this article is to address the question of whether Apple is worth investing in by analyzing investment data on Apple’s stock and Apple’s own data. In this article, the author assumes 10,000 shares of Apple Inc stock from January 1, 2020, until August 2, 2022, and uses Yahoo Finance’s historical data to calculate past earnings levels, combined with the author’s macro analysis of Apple’s economic conditions and market conditions to conclude that Apple is well worth investing in over the next 3-5 years
Application of Seasonal ARIMA Model in Forecasting the Exchange Rate: Taking RMB to USD as an Example
No full textForecasting exchange rate is very profitable and crucial. Realizing the forecasting of the exchange rate means that personal investors can do arbitrage; For the policy makers, it means that they can optimize their fiscal policy and monetary policy. The article has used seasonal ARIMA model in terms of forecasting the RMB to USD exchange rate, and captures the seasonal factors of the RMB to USD exchange rate which is a time series better. First, the author deals with the data by using first-order seasonal difference；then,the author applies the auto ARIMA model in Rstudio to fit the model with the data, receiving the ARIMA(4,2,1)(0,1,0)(365). After that, the author forecasts the RMB to USD exchange rate in the next 90 days. Finally, the author does the residual test, and discusses the autocorrelation,fitting degree, and whether or not it is overfitted of the model. The conclusion of the writer is that the RMB to USD exchange rate will fall in the next 90 days
Targeting and Modeling Immune Resistance in Lung Cancer
No full textThe general metadata -- e.g., title, author, abstract, subject headings, etc. -- is publicly available, but access to the submitted files is restricted to UT Southwestern campus access and/or authorized UT Southwestern users.Lung cancer causes most cancer-associated death both in U.S. and worldwide. Immune checkpoint blockade has achieved durable therapeutic effects in some lung cancer patients. The mechanism of immune escape in lung cancer merits further investigation to improve the efficacy of immune checkpoint blockade and other treatments. This thesis is focused on targeting innate immune resistance in small cell lung cancer (SCLC) and modeling human non-small cell lung cancer (NSCLC) in genetically engineered mouse models (GEMMs). I observed that SCLC escapes from innate immune surveillance by down-regulating NK cell-activating ligands. Histone deacetylase (HDAC) inhibitor could restore expression of NK cell-activating ligands and trigger anti-tumor immunity in vivo. HDAC inhibitors can be potential therapeutics for SCLC. Besides, I generated a NSCLC GEMM with high tumor mutational burden (TMB) by incorporating PoleP286R. PoleP286R GEMM with wildtype p53 is sensitive to immune checkpoint blockade (ICB). Loss of p53 and tumor heterogeneity contributed to immune escape in this high TMB mouse model. This ICB-sensitive, high TMB model can be utilized to explore novel immunotherapy and study novel mechanism of immune resistance of NSCLC
Understanding Rural Governance Changes in China: A Case Study of Rural Programs in Jiangning
No full textShen, Mingrui.Thesis Ph.D. Chinese University of Hong Kong 2016.Includes bibliographical references (leaves ).Abstracts also in Chinese.Title from PDF title page (viewed on …)
Correction: Subnational-level government influence and FDI location choices: The moderating roles of resource dependence relations
No full textIn this article Luqun Xie should also have been denoted as a corresponding author, and the affiliation details for Luqun Xie were incorrectly given as “Department of Innovation and Strategy, Shanghai Jiaotong University, 1954 Huashan Road, Shanghai 200030, People’s Republic of China” but should have been “Department of Information, Technology, and Innovation, Shanghai Jiaotong University, 1954 Huashan Road, Shanghai 200030, People’s Republic of China”. The original article has been corrected.</p
A lightweight multiscale convolutional neural network for garbage sorting
No full textWaste sorting plays a vital role in establishing a sustainable society by effectively reducing resource waste and promoting its recycling. However, traditional garbage sorting heavily relies on manual labor, which is inefficient, costly, and constrained by limited human resources. To address these challenges, this paper employs the convolutional neural network technique in deep learning for intelligent waste sorting. Firstly, a multi-scale processing strategy is introduced to enhance the system's resilience and accuracy by considering feature information at various scales. Secondly, a lightweight approach using tiny convolutions instead of large convolutions is adopted to reduce model parameters. Combining the advantages of both, we constructed a lightweight multiscale convolution (LMConv) and experiments the Lightweight Multiscale Convolutional Neural Network (LMNet) based on LMConv, and its optimal convolutional architecture is determined through ablation experiments. The experiment results demonstrate that LMNet outperforms other well-known convolutional neural network models in the area of garbage sorting
Research on the impact of entrepreneurial learning on business model design under the moderation of information cocoons
Get PDFEntrepreneurial learning plays a significant role in promoting business model design. In the information age everyone will fall into the information cocoon effect. Will the information cocoons have an impact on entrepreneurs’ business model design decisions? Based on the cognitive perspective of business model research starting from the two entrepreneurial learning levels of individual learning and organizational learning this study constructs a logical relationship model that drives the business model design of start-ups through entrepreneurial learning. At the same time it is also taken into consideration that the phenomenon of information cocoons in the mass media environment exists in this process and has an impact on the business model design outcome. Through a questionnaire survey and empirical analysis of 322 entrepreneurs the research finds that in the process of entrepreneurship organizational learning matches the design of novelty-centered business models; information cocoons objectively exist in the process of business model design driven by entrepreneurial learning and it, to a certain extent limits the innovative behavior of entrepreneurs
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