19916 research outputs found
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Amina Carter and family
No full textGroup portrait featuring Amina Carter, Melody Riley, Ratibu Jacocks, Malaika Jacocks, and Jamala Jacocks (color photograph).https://scholarworks.lib.csusb.edu/bridges-photographs/1070/thumbnail.jp
San Bernardino Vally College 1964 Track and Field Men\u27s Competitors
No full textGroup portrait of San Bernardino Valley College\u27s 1964 State Junior College Track and Field Championship Runner-Up team: Robert Howard (top left), George Greenwood (top right), Walter Brown, Jim Sullivan, and Eugene Carson in their uniforms with a trophy (black-and-white photograph).https://scholarworks.lib.csusb.edu/bridges-photographs/1084/thumbnail.jp
Anye Riley and Amina Carter
No full textGroup portrait featuring Anye Riley and Amina Carter (color photograph).https://scholarworks.lib.csusb.edu/bridges-photographs/1122/thumbnail.jp
Amina Carter
No full textPortrait of Amina Carter (color photograph).https://scholarworks.lib.csusb.edu/bridges-photographs/1124/thumbnail.jp
THE CULTURAL MISMATCH BETWEEN LATINAS\u27 INTERDEPENDENT SELF-CONCEPT AND THE INDEPENDENT CULTURE OF STEM
Get PDFI assessed the role of self-concept fit, as outlined in the SAFE model (Schmader & Sedikides, 2018), in Latina college students’ feelings toward pursuing a STEM course. Research on the underrepresentation of certain social groups in STEM has mainly focused on the role of goal fit. More specifically, researchers have found that portraying STEM environments as affording communal goals promotes goal fit, which is related to positive outcomes like interest, belonging, and favorable ratings for STEM courses, careers, and lab positions (Belanger et al., 2017; Belanger et al., 2020; Diekman et al., 2011). Because Latinas are socialized within an interdependent culture due to their ethnic and gender identities and the intersection of these identities (Madison & Trafimow, 2001; Galanti, 2003; Castillo et al., 2010), it is possible there is a perceived culture mismatch between Latinas’ interdependent self-concept and the independent culture of STEM (Diekman et al., 2010; Joshi et al., 2022). In the current project, I expected that participants who read about a STEM course with an interdependent culture, compared to participants who read about a STEM course with an independent culture, would report more self-concept fit, especially if the participants held a more interdependent self-concept. Additionally, I expected higher levels of self-concept fit to predict higher levels of interest and intent to persist in the course. Thus, I expected self-concept fit to mediate the relationship between course framing or culture and interest and intent to persist. Unexpectedly, course framing did not have a direct effect on self-concept fit, interest, or intent to persist. However, there was significant moderated mediation effect on both interest and intent to persist. Participants who held a more interdependent self-concept and read about a STEM course with an independent culture reported lower self-concept fit. Self-concept fit significantly predicted interest and intent to persist in the course
UNDERSTANDING THE DYNAMICS OF CHATBOT DESIGN, TRANSPARENCY, AND ETHICAL IMPLICATIONS IN CUSTOMER–BRAND RELATIONSHIP IN HOSPITALITY AND TOURISM INDUSTRY
Get PDFThis culminating experience project investigated the impact of chatbot interactions on customer perceptions, ethical considerations, and transparency within the hospitality and tourism industry. The research questions are: Q1: how do the specific visual and verbal aspects contribute to shaping customer perceptions within the context of chatbot marketing efforts? Q2: what steps can companies take to address and mitigate ethical concerns surrounding interactions with chatbots? Q3: To what extent does the level of transparency and explainability in chatbot interactions influence customer trust and satisfaction? The findings are: Q1: the study revealed that visual and verbal aspects of chatbot design significantly shape customer perceptions, with visually appealing chatbots and a friendly tone of voice being positively correlated with higher satisfaction levels. This indicates that strategic design elements enhance customer satisfaction and trust. Q2: the study identified transparency, robust data protection measures, and ethical design practices as crucial steps to address ethical concerns. Transparency about chatbot identity and capabilities, secure data handling, and ethical guidelines embedded in ai algorithms help mitigate ethical risks and build customer trust. Q3: the study found that transparency and clear explanations in chatbot interactions significantly enhance customer trust and satisfaction. Customers who are aware they are interacting with an ai and
who receive clear explanations for chatbot actions report higher levels of trust and satisfaction.
Conclusion for each research question is as follows: Q1: it was concluded that businesses must carefully consider visual and verbal design elements in chatbot marketing efforts to positively influence customer perceptions, satisfaction, and trust. Q2: it was concluded that addressing ethical concerns through transparency, data protection, and ethical ai design is crucial for maintaining customer trust. Proactive measures in these areas help build a responsible and trustworthy chatbot interaction framework. Q3: it was concluded that transparency and explainability are key to enhancing customer trust and satisfaction. Clear communication about the chatbot\u27s identity and actions fosters reliability and positive user experiences.
The future scope for research questions is as follows: Q1: future research could explore the long-term impact of visual and verbal design elements on customer loyalty and the effectiveness of various design variations. Q2: further research could investigate evolving ethical challenges in ai-driven customer service and the impact of emerging regulations on ethical chatbot deployment. Q3: future research could assess the impact of transparency practices on customer trust over time and explore cross-cultural variations in response to transparent chatbot interactions
ENHANCING CYBERSECURITY FOR UNMANNED SYSTEMS: A COMPREHENSIVE LITERATURE REVIEW
Get PDFThis culminating experience project addresses the pressing cybersecurity challenges encountered by unmanned autonomous vehicles. The research provides a comprehensive literature review on how hybrid encryption techniques can improve the security of its communication systems. The chosen research questions guiding this study are: (Q1) How can we enhance cybersecurity measures to safeguard the communication and transmission of sensitive data from unmanned systems, thereby preventing unauthorized access by malicious actors? (Q2) How can we ensure the confidentiality and integrity of messages exchanged with unmanned systems to a command-and-control center operating on the tactical edge? (Q3) How can hybrid encryption tackle the consumption problem of substantial processing power required for encrypting and transmitting data in unmanned systems?
The findings are: Q1. hybrid security strategy ensures strong communication integrity and safeguards against malicious interception in operations involving unmanned systems; Q2. lightweight cryptographic algorithms and hybrid encryption methods specifically designed for unmanned systems efficiently protect both the confidentiality and integrity of messages while optimizing computational resources; Q3. when using hybrid encryption, unmanned systems can effectively manage power consumption while maintaining robust data security protocols. The conclusions are: Q1. combining symmetric encryption for efficient data handling with asymmetric encryption for secure key exchange significantly enhances data confidentiality, integrity, and overall security. Q2. end-to-end encryption, secure key management, and authenticated encryption mechanisms within a hybrid encryption framework reduce risks associated with interception, tampering, and unauthorized access via unmanned systems. Q3. integrating efficient algorithm selection, optimized key management, resource-aware encryption, and dynamic key generation methods, can address power consumption concerns. Future research directions should include deeper exploration of hybrid encryption practices within unmanned systems to advance understanding in the realm of communication systems for autonomous vehicles
Emotional Eating in Adolescents with Obesity: Case Series
Get PDFChildhood obesity remains a significant public health concern, with substantial implications for physical and mental well-being. This thesis aims to explore the intricate relationship between emotional eating and obesity among adolescents, with a focus on identifying emotional triggers and assessing their psychological impact. Utilizing a cross-sectional study design at a university in southern California, data were collected from two adolescents aged 13-18 years. Through surveys and body composition measurements, participants\u27 emotional barriers to weight loss and readiness for change were assessed. The findings underscore the presence of varying degrees of emotional hurdles among adolescents with obesity, including depression, frustration, and emotional hunger. Despite these challenges, participants exhibited a high willingness to engage in weight management interventions. The study highlights the importance of addressing emotional triggers and offering effective coping mechanisms in public health interventions targeting adolescent obesity. Recommendations for future research include longitudinal studies to elucidate the cause-and-effect relationship between emotional eating and obesity, as well as evidence-based interventions incorporating cognitive-behavioral methodologies and nutritional education. By bridging research insights with practical recommendations, this thesis contributes to both theoretical advancements and real-world interventions in the critical area of adolescent obesity and emotional eating
REAL-TIME GUN DETECTION IN VIDEO STREAMS USING YOLO V8
Get PDFIn this research, we advance the domain of public safety by developing a machine learning model that utilizes the YOLO v8 architecture for real-time detection of firearms in video streams. A diverse and extensive dataset, capturing a range of firearms in varying lighting and backgrounds, was meticulously assembled and preprocessed to enhance the model\u27s adaptability to real-world scenarios. Leveraging the YOLO v8 framework, known for its real-time object detection accuracy, the model was fine-tuned to accurately identify firearms across different shapes and orientations.
The training phase capitalized on GPU computing and transfer learning to expedite the learning process while preserving a high degree of precision, recall, and F1-score in the model’s performance metrics. Through iterative optimization post-evaluation, the model\u27s detection capabilities were further refined.
Deployed in an Online Mode, the model operates on a cloud-based platform, utilizing the scalability and computational prowess of Google Cloud Platform (GCP). A dedicated application, designed with Flutter, delivers a consistent user interface that streamlines interaction, complemented by Google Cloud Functions that manage data communication seamlessly.
This project demonstrates the considerable promise of the YOLO v8 architecture for real-time surveillance and public safety applications. The outcomes are promising, and future endeavors will aim to broaden the validation with more extensive video datasets