Diablo Valley College

Research background: Equity structure, as an important factor influencing corporate governance and enterprise performance, is particularly crucial in the rapidly changing global technology industry environment. Research Topic: This paper takes Microsoft Corporation as a typical case to deeply explore the specific characteristics of equity structure, governance effectiveness, and its impact on the long-term development of enterprises. Research method: A combination of literature review and case analysis was adopted to specifically analyze Microsoft's latest annual financial report, governance structure documents and related market data, and to extract the characteristics of Microsoft's equity structure and governance practices. Research results: Microsoft's equity is mainly composed of institutional investors, with a high concentration of equity and a stable shareholder structure. The board of directors is dominated by independent directors, effectively enhancing the objectivity and transparency of governance decisions and promoting the strategic transformation and performance improvement of the enterprise. Research conclusion: A clear and stable equity structure has significant positive significance for the effective operation of the corporate governance mechanism and the long-term performance growth of enterprises. The Microsoft model has important reference value for similar technology companies.

The A* algorithm is widely used in the field of path planning for autonomous mobile robots. However, A* is a simple algorithm that cannot avoid moving obstacles. One of our research directions is to realize dynamic obstacle avoidance, which is based on A* algorithm. At the same time, we found that the A* algorithm is computationally inefficient. In contrast, the emerging nature-inspired algorithm outperforms the classical algorithm because of the reduced computational overhead. The nature-inspired algorithm is one of the most common heuristic algorithms. We reproduce a near-optimal algorithm that considers a single UGV approximate optimal path planning algorithm for obstacle avoidance in static environments. The algorithm uses two heuristic values, hence the name H2A (double heuristic algorithm). Our goal is to try to be able to avoid two moving obstacles at a time, the performance of the proposed algorithm is compared with the performance of the A* algorithm.

With the rapid development of Intelligent Transportation Systems (ITS), vehicle type classification, as a key link in Automatic Toll Collection systems (ATC), is of great significance in improving traffic efficiency and reducing economic losses. This study proposes an intelligent vehicle classification system based on deep learning and multi-sensor data fusion to address the accuracy issues existing in vehicle classification methods based on optical sensors (OS) and human observers. The system significantly improves the accuracy and robustness of vehicle classification by combining deep Convolutional Neural Networks (CNN), LiDAR sensors, and machine learning algorithms. We first constructed a large-scale annotated dataset containing multiple vehicle types and complex traffic scenes to improve our model's capability to identify different vehicle characteristics. Next, CNN models based on different architectures were designed to extract global and local features of the vehicle, respectively. In addition, the LiDAR sensor was used to achieve the spatial structure architectures of the vehicle and combined with the output of the CNN model to improve classification performance under occlusion and complex scenes.

Cultural diversity plays a major role in this increasingly interconnected world, especially as we live in a multicultural society where people live together with different cultural backgrounds. The irreversible trends of globalization and migration also fueled the boom of a wide variety of cultural manifestations. This paper emphasizes the implications of cultural diversity in social development. It tackles two questions: First, what is cultural diversity and how does it evolve over the years? And second, what is the impact of cultural diversity on social development? This paper offers a comprehensive overview to explore the relationship between cultural diversity and social development, and aims to put forward suggestions to tackle inequality issues and promote sustainable changes from the cultural dimensions.

Objetivo: identificar o conhecimento dos enfermeiros que atuam na Estratégia Saúde da Família quanto à segurança do paciente. Método: estudo qualitativo exploratório, descritivo, realizado com 20 enfermeiros da Estratégia Saúde da Família de um município paranaense. A coleta de dados foi realizada entre julho e dezembro de 2021 com entrevistas semiestruturadas. Os dados foram categorizados e analisados com auxílio do software Iramuteq. Resultados: os enfermeiros relataram dificuldades no processo de trabalho e aspectos que influenciavam nas ações relacionadas à segurança do paciente: falta de profissionais, sobrecarga de trabalho, falhas na comunicação, trabalho em equipe e processo de formação, impacto da pandemia contra COVID-19, eventos adversos e cultura de notificação. Considerações finais: o estudo demonstrou a fragilidade dos enfermeiros em relação à segurança do paciente na Atenção Primária à Saúde e a necessidade de o tema ser amplamente discutido entre todos os componentes das equipes da Estratégia Saúde da Família.

This paper is a discussion of economic inequality in China. We look for the nature of many inequalities by correlating the Gini coefficient with unemployment, education, health care, and transport. By comparing graphs and data, we propose a series of solutions to improve inequality and discuss the effects and problems caused by these inequalities. The conclusion is that unemployment has no significant correlation with Gini Coefficient and that education, health care, and transport are all highly negatively correlated with Gini Coefficient. Therefore, upgrading education, healthcare, and transportation in backward regions is one of the solutions to reduce economic inequality in China.

ABSTRACT We report the results of long-term reverberation mapping campaigns of the nearby active galactic nuclei (AGNs) NGC 4151, spanning from 1994 to 2022, based on archived observations of the FAST Spectrograph Publicly Archived Programs and our new observations with the 2.3 m telescope at the Wyoming Infrared Observatory. We reduce and calibrate all the spectra in a consistent way, and derive light curves of the broad H β line and 5100 Å continuum. Continuum light curves are also constructed using public archival photometric data to increase sampling cadences. We subtract the host galaxy contamination using Hubble Space Telescope imaging to correct fluxes of the calibrated light curves. Utilizing the long-term archival photometric data, we complete the absolute flux-calibration of the AGN continuum. We find that the H β time delays are correlated with the 5100 Å luminosities as $\tau _{\rm H\beta }\propto L_{5100}^{0.46\pm 0.16}$. This is remarkably consistent with Bentz et al. (2013)’s global size–luminosity relationship of AGNs. Moreover, the data sets for five of the seasons allow us to obtain the velocity-resolved delays of the H β line, showing diverse structures (outflows, inflows, and discs). Combining our results with previous independent measurements, we find the measured dynamics of the H β broad-line region (BLR) are possibly related to the long-term trend of the luminosity. There is also a possible additional ∼1.86 yr time lag between the variation in BLR radius and luminosity. These results suggest that dynamical changes in the BLR may be driven by the effects of radiation pressure.

Materials for the workshop on social justice presented at the 2021 BIOME Institute.