The Impact and Evolution of Individual’s Learning: An Empirical Study in Open Innovation Community

Learning is critical for individuals to increase their performance. However, this benefit of learning is not always realized. Previous studies have distinguished different classifications of learning approaches and reached inconsistent results. Therefore, this study further refines the classification of learning approaches in an open innovation community and explore the individual’s learning curve from a dynamic perspective. Specifically, we focus on whether and under what conditions learning can increase individual’s performance, and how individual\u27s learning curve changes over the tenure. To examine our hypotheses, we collect a dataset includes 48,820 game mods developed by 6,141 creators spanning 7-years from an open game innovation community. The results not only show the significant curve relationship between the four learning approaches and performance, but also demonstrate individual’s learning curve evolves over the tenure. This paper provides valuable suggestions and implications for individuals to choose appropriate learning approaches and obtain better performance under different tenures

Understanding Key Drivers of Mooc Satisfaction and Continuance Intention To Use

Massive Open Online Courses (MOOCs) have attracted global audiences who desire to learn. However, the completion rate of these courses is less than 10 percent. Few studies have systematically researched the influence of expectation-confirmation theory (ECT) and user experience (e.g., flow experience, perceived interest) on user satisfaction of and the continuance intention to use MOOCs. The present study examines the drivers of MOOC satisfaction based on ECT and the influence of satisfaction on user behavior. A research model reflecting the relationships among confirmation, usefulness, interest, flow, satisfaction, and continuance intention to use, and intention to recommend was developed and tested using data collected from 300 subjects. Our findings show that flow and interest are important variables that enhance MOOC satisfaction based on ECT

Pedestrian Detection based on Clustered Poselet Models and Hierarchical And-Or Grammar

In this paper, a novel part-based pedestrian detection algorithm is proposed for complex traffic surveillance environments. To capture posture and articulation variations of pedestrians, we define a hierarchical grammar model with the and-or graphical structure to represent the decomposition of pedestrians. Thus, pedestrian detection is converted to a parsing problem. Next, we propose clustered poselet models, which use the affinity propagation clustering algorithm to automatically select representative pedestrian part patterns in keypoint space. Trained clustered poselets are utilized as the terminal part models in the grammar model. Finally, after all clustered poselet activations in the input image are detected, one bottom-up inference is performed to effectively search maximum a posteriori (MAP) solutions in the grammar model. Thus, consistent poselet activations are combined into pedestrian hypotheses, and their bounding boxes are predicted. Both appearance scores and geometry constraints among pedestrian parts are considered in inference. A series of experiments is conducted on images, both from the public TUD-Pedestrian data set and collected in real traffic crossing scenarios. The experimental results demonstrate that our algorithm outperforms other successful approaches with high reliability and robustness in complex environments

PRE-PURCHASE AND POST-PURCHASE SALES PROMOTIONS ON E-COMMERCE PLATFORMS: THE EFFECTS OF PROMOTIONAL BENEFITS ON CUSTOMER-BASED BRAND EQUITY

This research examines the impacts of electronic commerce platforms\u27 sales promotions\u27 benefits on customer-based brand equity (platform brand awareness and platform brand association) and how these relationships are moderated by the promotion stage. Based on the two functions of sales promotions (stimulation vs. maintenance), we propose a five-benefit framework consisting of exploration, convenience, savings, social bonds and structural bonds. Our results reveal the two functions of sales promotions and the positive effects of the benefits on customer-based brand equity (CBBE). The differences between pre- and post-purchase sales promotions are also significant. We discuss the managerial and theoretical implications of these results at the end

Ada-NETS: Face Clustering via Adaptive Neighbour Discovery in the Structure Space

Face clustering has attracted rising research interest recently to take advantage of massive amounts of face images on the web. State-of-the-art performance has been achieved by Graph Convolutional Networks (GCN) due to their powerful representation capacity. However, existing GCN-based methods build face graphs mainly according to kNN relations in the feature space, which may lead to a lot of noise edges connecting two faces of different classes. The face features will be polluted when messages pass along these noise edges, thus degrading the performance of GCNs. In this paper, a novel algorithm named Ada-NETS is proposed to cluster faces by constructing clean graphs for GCNs. In Ada-NETS, each face is transformed to a new structure space, obtaining robust features by considering face features of the neighbour images. Then, an adaptive neighbour discovery strategy is proposed to determine a proper number of edges connecting to each face image. It significantly reduces the noise edges while maintaining the good ones to build a graph with clean yet rich edges for GCNs to cluster faces. Experiments on multiple public clustering datasets show that Ada-NETS significantly outperforms current state-of-the-art methods, proving its superiority and generalization. Code is available at https://github.com/damo-cv/Ada-NETS

A novel and stable "two-hit" acute lung injury model induced by oleic acid in piglets

<p>Abstract</p> <p>Background</p> <p>Children are susceptible to pulmonary injury, and acute lung injury (ALI) often results in a high mortality and financial cost in pediatric patients. Evidence has showed that oleic acid (OA) plays an important role in ALI. Therefore, it has special significance to study ALI in pediatric patients by using OA-induced animal models. Unfortunately, the animal model hs a high mortality due to hemodynamic instability. The aim of this study was to establish a novel hemodynamically stable OA-induced ALI model in piglets with two hits.</p> <p>Methods</p> <p>18 Chinese mini-piglets were randomized into three groups: group C (received saline-ethanol solution), group T (received OA-ethanol solution in routine administration manner) and group H (received OA-ethanol solution in two-hit manner). Hemodynamic and pulmonary function data were measured. Histopathological assessments were performed.</p> <p>Results</p> <p>Two piglets in group T died of radical decline of systemic blood pressure. Group T showed more drastic hemodynamic changes than group H especially during the period of 5 to 30 minutes after OA administration. Both Group T and group H all produced severe lung injury, while group C had no significant pathologic changes. OA-induced hypotension might be caused by pulmonary hypertension rather than comprised left ventricular function.</p> <p>Conclusion</p> <p>OA leads to severe pulmonary hypertension which results in hemodynamic fluctuation in OA-induced ALI model. It is the first report on hemodynamic stable ALI animal model in piglets using two-hit method. The two-hit ALI animal model fulfils the ALI criteria and has the following characteristics: hemodynamic stability, stable damage to gas exchange and comparability with pediatric patients in body weight and corresponding age. The two-hit ALI animal model can be used to study the basic mechanism and the therapeutic strategies for pediatric ALI.</p

When Ad Is Selfie: The Effect of Selfie on the Effectiveness of Ad Endorsers in Social Media

Selfie has proliferated in social media and capture the attentions from businesses. Although selfie has been leveraged into social commerce, little literature has understood and explained the effect of selfie. To solve this gap, this paper considers the effect of selfie on the effectiveness of ad endorsers and the moderating role of product type. We interpret selfie as a form of self-disclosure and study three types of ad endorsers: celebrities, experts and typical consumers. Given the nature of selfie and ad endorsers, we hypothesize that selfie enhance the effectiveness of celebrities and typical consumers, not experts. Besides, we also hypothesize that selfie improve the effectiveness of celebrities and typical consumer for hedonic product more than for utilitarian product, and experts is good for utilitarian product. Towards hypotheses in our paper, we plan to employ lab and field experimental method to test them. Potential theoretical and practical implications have been discussed

LedMAC: More Efficient Variants of LightMAC

LightMAC is a lightweight MAC designed by Luykx et al. and recently standardized by ISO/IEC. In this paper, we refine LightMAC and suggest two simple variants called LedMAC1 and LedMAC2. Compared to LightMAC, our first scheme LedMAC1 avoids unnecessary padding without sacrificing the security. Our second scheme LedMAC2 further reduces the number of keys from two to one, and achieves the same level security as that of LightMAC

Forgery Attacks on Several Beyond-Birthday-Bound Secure MACs

At CRYPTO\u2718, Datta et al. proposed nPolyMAC and proved the security up to 2^{2n/3} authentication queries and 2^{n} verification queries. At EUROCRYPT\u2719, Dutta et al. proposed CWC+ and showed the security up to 2^{2n/3} queries. At FSE\u2719, Datta et al. proposed PolyMAC and its key-reduced variant 2k-PolyMAC, and showed the security up to 2^{2n/3} queries. This security bound was then improved by Kim et al. (EUROCRYPT\u2720) and Datta et al (FSE\u2723) respectively to 2^{3n/4} and in the multi-user setting. At FSE\u2720, Chakraborti et al. proposed PDM*MAC and 1k-PDM*MAC and showed the security up to 2^{2n/3} queries. Recently, Chen et al. proposed nEHtM_p^+ and showed the security up to 2^{2n/3} queries. In this paper, we show forgery attacks on nPolyMAC, CWC+, PolyMAC, 2k-PolyMAC, PDM*MAC, 1k-PDM*MAC and nEHtM_p^+. Our attacks exploit some vulnerability in the underlying polynomial hash function Poly, and (i) require only one authentication query and one verification query; (ii) are nonce-respecting; (iii) succeed with probability 1. Thus, our attacks disprove the provable high security claims of these schemes. We then revisit their security analyses and identify what went wrong. Finally, we propose two solutions that can restore the beyond-birthday-bound security

Revisiting the Security of DbHtS MACs: Beyond-Birthday-Bound in the Multi-User Setting

Double-block Hash-then-Sum (DbHtS) MACs are a class of MACs that aim for achieving beyond-birthday-bound security, including SUM-ECBC, PMAC\_Plus, 3kf9 and LightMAC_Plus. Recently Datta et al. (FSE\u2719), and then Kim et al. (Eurocrypt\u2720) prove that DbHtS constructions are secure beyond the birthday bound in the single-user setting. However, by a generic reduction, their results degrade to (or even worse than) the birthday bound in the multi-user setting. In this work, we revisit the security of DbHtS MACs in the multi-user setting. We propose a generic framework to prove beyond-birthday-bound security for DbHtS constructions. We demonstrate the usability of this framework with applications to key-reduced variants of DbHtS MACs, including 2k-SUM-ECBC, 2k-PMAC_Plus and 2k-LightMAC_Plus. Our results show that the security of these constructions will not degrade as the number of users grows. On the other hand, our results also indicate that these constructions are secure beyond the birthday bound in both single-user and multi-user setting without additional domain separation, which is used in the prior work to simplify the analysis. Moreover, we find a critical flaw in 2kf9, which is proved to be secure beyond the birthday bound by Datta et al. (FSE\u2719). We can successfully forge a tag with probability 1 without making any queries. We go further to show attacks with birthday-bound complexity on several variants of 2kf9