1,723,888 research outputs found
An exploratory study of multiple identities in East Asian American women who are attracted to women
No full textThis exploratory study examined the experiences of East Asian American women who are romantically or sexually attracted to women (EAAWAW). EAAWAW was selected as the most inclusive term for women self-identifying as lesbian, gay, queer, and bisexual. EAAWAW have previously been studied as a population that experiences unique challenges due to their multiple minority status. They have to navigate situations in which one or more of their minority statuses related to their gender, sexual orientation, and ethnicity are stigmatized, which might lead to psychological stress. Three main research questions were addressed in this study: 1) What are the challenges that EAAWAW face with regard to their sexual identity, gender, and ethnicity? 2) How do they deal with these challenges? Specifically, how might they utilize multiple self-aspects to manage stigma and stress associated with being attracted to women, East Asian, and female? 3) How do EAAWAW conceptualize themselves with regard to their identity and how does their self-concept vary across contexts? A qualitative analysis of nine semi-structured, in-depth interviews was completed using a grounded theory approach. Participants ranged in age from 25 to 65 and were all residing in the United States. The interview data were analyzed to uncover qualitative themes. These included the range of identities and roles with which EAAWAW identify, multiple minority stress, invisibility, conflict between sexual orientation and family and East Asian values, freedom from societal norms, positive discrimination, benevolent prejudice, social support, identity management, and cognitive reframes. Overall, despite the stigma- related challenges that EAAWAW experience, the individuals interviewed in this study demonstrated much resilience and a variety of coping strategies that allowed them to move between communities and manage their multiple identities. These findings are discussed as well as their important implications for EAAWAW, their families, mental health professionals, and the communities to which EAAWAW belong. The study suggests that these groups would benefit from an increased understanding of the nature of multiple minority stress as well as the variety of cognitive, interpersonal, and identity management strategies available to EAAWAW as they navigate different communities and contexts in their personal and professional lives.Psy. D.Includes bibliographical referencesby Diana Lei Lei On
Non-Orthogonal Multiple Access for Next-Generation Satellite Systems: Flexibility Exploitation and Resource Optimization
Get PDFIn conventional satellite communication systems, onboard resource management follows pre-design approaches with limited flexibility. On the one hand, this can simplify the satellite payload design. On the other hand, such limited flexibility hardly fits the scenario of irregular traffic and dynamic demands in practice. As a consequence, the efficiency of resource utilization could be deteriorated, evidenced by mismatches between offered capacity and requested traffic in practical operations. To overcome this common issue, exploiting multi-dimension flexibilities and developing advanced resource management approaches are of importance for next-generation high-throughput satellites (HTS). Non-orthogonal multiple access (NOMA), as one of the promising new radio techniques for future mobile communication systems, has proved its advantages in terrestrial communication systems. Towards future satellite systems, NOMA has received considerable attention because it can enhance power-domain flexibility in resource management and achieve higher spectral efficiency than orthogonal multiple access (OMA). From ground to space, terrestrial-based NOMA schemes may not be directly applied due to distinctive features of satellite systems, e.g., channel characteristics and limited onboard capabilities, etc. To investigate the potential synergies of NOMA in satellite systems, we are motivated to enrich this line of studies in this dissertation. We aim at resolving the following questions: 1) How to optimize resource management in NOMA-enabled satellite systems and how much performance gain can NOMA bring compared to conventional schemes? 2) For complicated resource management, how to accelerate the decision-making procedure and achieve a good tradeoff between complexity reduction and performance improvement? 3) What are the mutual impacts among multiple domains of resource optimization, and how to boost the underlying synergies of NOMA and exploit flexibilities in other domains?
The main contributions of the dissertation are organized in the following four chapters: First, we design an optimization framework to enable efficient resource allocation in general NOMA-enabled multi-beam satellite systems. We investigate joint optimization of power allocation, decoding orders, and terminal-timeslot assignment to improve the max-min fairness of the offered-capacity-to-requested-traffic ratio (OCTR). To solve the mixed-integer non-convex programming (MINCP) problem, we develop an optimal fast-convergence algorithmic framework and a heuristic scheme, which outperform conventional OMA in matching capacity to demand.
Second, to accelerate the decision-making procedure in resource optimization, we attempt to solve optimization problems for satellite-NOMA from a machine-learning perspective and reveal the pros and cons of learning and optimization techniques. For complicated resource optimization problems in satellite-NOMA, we introduce deep neural networks (DNN) to accelerate decision making and design learning-assisted optimization schemes to jointly optimize power allocation and terminal-timeslot assignment. The proposed learning-optimization schemes achieve a good trade-off between complexity and performance.
Third, from a time-domain perspective, beam hopping (BH) is promising to mitigate the capacity-demand mismatches and inter-beam interference by selectively and sequentially illuminating suited beams over timeslots. Motivated by this, we investigate the synergy and mutual influence of NOMA and BH for satellite systems to jointly exploit power- and time-domain flexibilities. We jointly optimize power allocation, beam scheduling, and terminal-timeslot assignment to minimize the capacity-demand gap. The global optimal solution may not be achieved due to the NP-hardness of the problem. We develop a bounding scheme to tightly gauge the global optimum and propose a suboptimal algorithm to enable efficient resource assignment. Numerical results demonstrate the synthetic synergy of combining NOMA and BH, and their individual performance gains compared to the benchmarks.
Fourth, from the spatial domain, adaptive beam patterns can adjust the beam coverage to serve irregular traffic demand and alleviate co-channel interference, motivating us to investigate joint resource optimization for satellite systems with flexibilities in power and spatial domains. We formulate a joint optimization problem of power allocation, beam pattern selection, and terminal association, which is in the format of MINCP. To tackle the integer variables and non-convexity, we design an algorithmic framework and a low-complexity scheme based on the framework. Numerical results show the advantages of jointly optimizing NOMA and beam pattern selection compared to conventional schemes.
In the end, the dissertation is concluded with the main findings and insights on future works
Chipola: A Chinese Podcast Lexical Database for Capturing Spoken Language Nuances and Predicting Behavioral Data
No full textThis is the repository for the data and codes of our manuscript:
"Zhao, Ning & Lei, Lei. (2025). Chipola: A Chinese podcast lexical database for capturing spoken language nuances and predicting behavioral data. Behavior Research Methods. https://doi.org/10.3758/s13428-025-02697-0".
All data are stored in the chipola_data folder.
Please download the .zip file and unzip it.
Thanks
Electric bus charging schedules relying on real data-driven targets based on hierarchical deep reinforcement learning
No full textDeep reinforcement learning aided platoon control relying on V2X information
No full textThe impact of Vehicle-to-Everything (V2X) communications on platoon control performance is investigated. Platoon control is essentially a sequential stochastic decision problem (SSDP), which can be solved by Deep Reinforcement Learning (DRL) to deal with both the control constraints and uncertainty in the platoon leading vehicle’s behavior. In this context, the value of V2X communications for DRL-based platoon controllers is studied with an emphasis on the tradeoff between the gain of including exogenous information in the system state for reducing uncertainty and the performance erosion due to the curse-of-dimensionality. Our objective is to find the specific set of information that should be shared among the vehicles for the construction of the most appropriate state space. SSDP models are conceived for platoon control under different information topologies (IFT) by taking into account ‘just sufficient’ information. Furthermore, theorems are established for comparing the performance of their optimal policies. In order to determine whether a piece of information should or should not be transmitted for improving the DRL-based control policy, we quantify its value by deriving the conditional KL divergence of the transition models. More meritorious information is given higher priority in transmission, since including it in the state space has a higher probability in offsetting the negative effect of having higher state dimensions. Finally, simulation results are provided to illustrate the theoretical analysis
sj-txt-1-sgo-10.1177_21582440221089963 – Supplemental material for The Research Trends of Text Classification Studies (2000–2020): A Bibliometric Analysis
No full textSupplemental material, sj-txt-1-sgo-10.1177_21582440221089963 for The Research Trends of Text Classification Studies (2000–2020): A Bibliometric Analysis by Haoran Zhu and Lei Lei in SAGE Open</p
Going Beyond Counting First Authors in Author Co-citation Analysis
Get PDFThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Factors Influencing Continuous Intention To Use CB Pay (Zin Lei Lei Oo, 2023)
Get PDFThe aims of the study are to examine the influencing factors on perception on
CB PAY and to analyze the effect of perception on continuous intention to use CB
PAY. Self -Service Technology (SST) service quality factors are used as influencing
factors in this study. Descriptive statistics and qualitative research method are
employed. Both primary and secondary sources are utilized in the study. This study is
based on primary data from 150 respondents who are 20% CB Bank (Botahtaung
Branch) customers registered to use CB PAY. Simple random sampling method is used
as the sampling method. The secondary data were gathered from relevant text books,
research papers, journals, theses, and articles from internet websites. Among the SST
service quality factors, functionality, security and design have highest mean score. The
study showed that convenience and customization significantly influence the
perception of CB PAY users. The study also revealed that convenience has the largest
influence on user perception towards CB PAY. Moreover, the study found that there is
a significant effect of user perception on continuous intention of CB PAY users. The
bank should provide follow-up service easily and solve the problems immediately
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