1,022 research outputs found
The impact of anti-bullying laws on children's social-behavioral skills
No full textBullying and violence, both on and off campuses, significantly impact children’s well-being. To address school bullying, every U.S. state gradually developed and implemented school anti-bullying laws (ABLs) and regulations between 2000 and 2015. This paper evaluates the effectiveness of ABLs using a difference-in-differences model and nationally representative samples of U.S. elementary school children. While state ABLs show limited overall effects on children’s social-behavioral skills, significant improvements are observed in self-control and interpersonal skills among low-income children, along with reduced externalizing behaviors among Hispanic children. States with strong or moderate ABLs show greater improvements in children’s interpersonal skills compared to states with weaker policies. These findings indicate social disparities in school bullying outcomes and highlight the importance of stronger policy enforcement.Published versio
Feasibility of Software-Based Duty Cycling of GPS for Trajectory-Based Services
No full textEnergy-efficient localization is increasingly important for many types of smartphone apps. The research community has argued that fixed duty cycling of GPS is not a good choice for trajectory-based services concerning route accuracy. In this paper, we describe the design and implementation of a highly accurate map matching and path construction algorithm. Furthermore, with thorough field experiments, we show that fixed duty cycling of a smartphone GPS receiver is a feasible approach for trajectory-based services, and it can achieve considerable energy conservation without sacrificing much route accuracy. When increasing the GPS sampling period beyond 120 seconds, it saves at least 78% energy in comparison to continuous GPS sampling, while the loss of route accuracy tends to be stable around 23%.Li, Xiaohan, Yuan, Fengpeng, & Lindqvist, Janne. (2016). Feasibility of Software-Based Duty Cycling of GPS for Trajectory-Based Services. In Proceedings of Consumer Communications & Networking Conference (CCNC2016-EdgeCom), Las Vegas, NV. http://ieeexplore.ieee.org/xpl/conhome.jsp?reload=true&punumber=1001153Peer reviewe
Food Security and Health Outcomes following Gray Divorce
No full textThe study evaluates the immediate and long-term consequences of gray divorce (i.e., marital dissolution after age 50) for the food security, depression, and disability of older Americans. Staggered Difference-in-Difference models were fitted to a nationally representative longitudinal sample of adults aged ≥ 50 years from the Health and Retirement Study, 1998–2018. Food insecurity and disability increase in the year of gray divorce and remain significantly elevated for up to six years or more following the event, consistent with the chronic strain model of gray divorce. Gray divorce has particularly adverse consequences for the food security of older women, while no gender differences were observed for disability. Increasing trends in gray divorce have important negative implications for food security and health of older Americans, particularly women, who appear to be less prepared to financially withstand a marital collapse in older age. Targeted policies to provide nutrition assistance and support in reemployment might be necessary to reduce the burden of food insecurity in the wake of gray divorce among women
Geochemistry and geochronology of high-grade rocks from the Grove Mountains, East Antarctica: Evidence for an Early Neoproterozoic basement metamorphosed during a single Late Neoproterozoic/Cambrian tectonic cycle
No full textsj-docx-1-tct-10.1177_15330338231161141 - Supplemental material for NRF1 Regulates the Epithelial Mesenchymal Transition of Breast Cancer by Modulating ROS Homeostasis
No full textSupplemental material, sj-docx-1-tct-10.1177_15330338231161141 for NRF1 Regulates the Epithelial Mesenchymal Transition of Breast Cancer by Modulating ROS Homeostasis by Linjuan Sun, Nan Ouyang, Shaheryar Shafi, Rongchuan Zhao, Jinlin Pan, Lei Hong, Xueyan Song, Xiaohan Sa and Yuanshuai Zhou in Technology in Cancer Research & Treatment</p
Learning deep part-aware embedding for person retrieval
No full textPerson retrieval is an important vision task, aiming at matching the images of the same person under various camera views. The key challenge of person retrieval lies in the large intra-class variations among the person images. Therefore, how to learn discriminative feature representations becomes the core problem. In this paper, we propose a deep part-aware representation learning method for person retrieval. First, an improved triplet loss is introduced such that the global feature representations from the same identity are closely clustered. Meanwhile, a localization branch is proposed to automatically localize those discriminative person-wise parts or regions, only using identity labels in a weakly supervised manner. Via the learning simultaneously guided by the global branch and the localization branch, the proposed method can further improve the performance for person retrieval. Through an extensive set of ablation studies, we verify that the localization branch and the improved triplet loss each contributes to the performance boosts of the proposed method. Our model obtains superior (or comparable) performance compared to state-of-the-art methods for person retrieval on the four public person retrieval datasets. On the CUHK03-labeled dataset, for instance, the performance increases from 73.0% mAP and 77.9% rank-1 accuracy to 80.8% (+7.8%) mAP and 83.9% (+6.0%) rank-1 accuracy.Yang Zhao,Chunhua Shen, Xiaohan Yu, Hao Chen, Yongsheng Gao, Shengwu Xion
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Analyzing and Processing Big Real Graphs
Full text linkAs fundamental abstractions of network structures, graphs are everywhere, ranging from biological protein interaction networks and Internet routing networks, to emerging online social networks. Studying graphs is critical to understanding the fundamental processes behind the networks, and of practical importance in experimental research. Although many studies on graphs have been carried out in decades, most of the work focused on small or synthetic graphs. In recent years, because of the unprecedented increase of existing networks and the emergence of new complex networks, more and more big real graphs are becoming available. Compared to the graphs studied in prior work, the graphs from these networks are significantly different in scale, level of dynamics and structure.In this dissertation, we tackle three important graph research problems caused by the significant differences of the big real graphs: efficient node distance computation, graph dynamic analysis and modeling, and graph privacy.First, we target on a fundamental graph analysis problem, i.e. node distance computation. As a primitive of graph analysis and network applications, the computation of shortest path or random walk distances is computationally expensive, and difficult to scale with the sheer size of big real graphs. To address the scalability issue, we design a novel node distance computation method, named graph coordinate systems, to efficiently estimate node distances with high accuracy.Our second work is to understand and model the dynamic processes in big real graphs. Specifically, we propose methods to analyze graph dynamics at multiple network scales and explore temporal properties of network growth. Through measurements on Renren first two-year dynamic data, we find independent and predictable processes at different network levels, and detect self-similar properties in its edge creation process. Based on the observations, we propose a new dynamic graph model to capture both temporal and spatial properties. Calibrated with the Renren dataset, our model successfully produces synthetic graphs showing similar dynamic properties.Finally, to address privacy issue in sharing graphs, we design a graph privacy system to guarantee the required level of privacy. The goal of our work is to design a system that can both maintain a meaningful graph structure and provide strong privacy guarantee. To navigate the tradeoff between the strength of privacy and graph structure utility, we propose a differentially-private graph model. Our rigorous proof shows that the graphs produced by the system can achieve the required level of privacy. By running the system on real graphs collected from Facebook, Internet, and Web, the results demonstrate that the generated synthetic graphs match the original graphs in terms of graph structural metrics and application-level performance.In summary, to analyze and process the graphs from today's large complex networks, we work on three important problems, including efficiently computing node distances in massive graphs, analyzing and modeling high volume of dynamics in big real graphs, and protecting graph privacy in sharing graphs. We propose novel solutions to address these problems. Through our extensive experiments, we show that our designs perform consistently well on big real graphs
Эколого-экономическая оценка энергетической эффективности рекомендуемых комплексов работ по безопасному зимнему содержанию автомобильных дорог
Full text linkShvedovsky, Petr Vladimirovich; Zhicheng, Dai; Weidong, W; Xiaohan, Zhao; Kozlovsky, Denis Stanislavovich. Environmental and economic assessment of energy efficiency of the recommended work packages for safe winter maintenance of road
The golden touch: how screen touches influence product attitude and purchase intention
Full text linkThe widespread usage of touch screen devices such as smartphones and tablets has changed how people interact with mediated information. The physical action of touch is more direct in that people interact with the information on the screen, rather than indirectly via input devices like a mouse or trackpad. The goal of this study is to examine whether different ways of physically interacting with media influence consumers’ attitude and purchase intention in online shopping, and how congruity between the touch feeling of specific products and touchscreens may moderate this effect of interaction. Participants viewed pictures of products which had either congruent or incongruent haptic feeling with an iPad screen by directly touching the screen or indirectly using a mouse, and then indicated their attitude, purchase intention and valuation toward these products. The results showed that consumers assigned more value when product information was acquired by touching. However, the main effect of physical interaction on attitude and purchase intention, and interaction effect between interaction and haptic congruity were not found.Submission published under a 24 month embargo labeled 'U of I Access', the embargo will last until 2018-05-01The student, Xiaohan Hu, accepted the attached license on 2016-04-27 at 12:36.The student, Xiaohan Hu, submitted this Thesis for approval on 2016-04-27 at 12:48.This Thesis was approved for publication on 2016-04-28 at 13:32.DSpace SAF Submission Ingestion Package generated from Vireo submission #9546 on 2016-07-07 at 13:51:02Made available in DSpace on 2016-07-07T20:35:22Z (GMT). No. of bitstreams: 2
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Previous issue date: 2016-04-28Embargo set by: Seth Robbins for item 93194
Lift date: 2018-07-07T20:35:34Z
Reason: Author requested U of Illinois access only (OA after 2yrs) in Vireo ETD systemU of I Only Restriction Lifted for Item 93194 on 2018-07-08T09:15:30Z
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