Computation-Performance Optimization of Convolutional Neural Networks with Redundant Kernel Removal

Deep Convolutional Neural Networks (CNNs) are widely employed in modern computer vision algorithms, where the input image is convolved iteratively by many kernels to extract the knowledge behind it. However, with the depth of convolutional layers getting deeper and deeper in recent years, the enormous computational complexity makes it difficult to be deployed on embedded systems with limited hardware resources. In this paper, we propose two computation-performance optimization methods to reduce the redundant convolution kernels of a CNN with performance and architecture constraints, and apply it to a network for super resolution (SR). Using PSNR drop compared to the original network as the performance criterion, our method can get the optimal PSNR under a certain computation budget constraint. On the other hand, our method is also capable of minimizing the computation required under a given PSNR drop.Comment: This paper was accepted by 2018 The International Symposium on Circuits and Systems (ISCAS

THE EFFECT OF PRICE PRESENTATION, SALES RESTRICTIONS, AND SOCIAL NETWORKS ON CONSUMER EWOM ACTIVITIES: TWO-PHASE VALIDATION

Word-of-mouth (WOM) is recognized as an effective communication channel among consumers. The Internet provides consumers with richer sales information and more online associates than do brick-and-mortar stores but makes complex the assessment of the shaping of electronic WOM (eWOM) intention and return on eWOM. Thus, we will conduct two experiments to examine the shaping of eWOM intention and return on eWOM. The first experiment explore the eWOM broadcasting from the perspective of eWOM senders in a laboratory setting, and the second experiment will validate the eWOM model from the perspective of both message senders and receivers. The first experiment will allow us to control for variables that are difficult to control in the field and examine the mechanisms behind eWOM intention. The preliminary validation of the research model will increase its explanatory power in the field and allow us examine the value of eWOM associated with eWOM intention

MOTIVATION FOR USING THE SOCIAL COMMERCE WEBSITE IN THE SHARING ECONOMY: A TWO-FACTOR THEORY PERSPECTIVE

The influence and power of the sharing economy are beginning to change our lifestyles and consumption patterns. Among the sharing firms operating in the sharing economy, Airbnb is not only a well-known example of a successful O2O (online to offline) giant but also positions itself as a social commerce website. This study intends to remove the mask of Airbnb from the perspectives of website decomposing because it is important to understand how social commerce is incorporated into the websites of e-commerce retailers to support their online business models. Drawing on the two-factor theory, we focus on the following two research questions: (1) Which website features are hygiene factors and which are motivation factors? (2) How are the hygiene and motivation factors that affect a consumer’s motivation for using the Airbnb website distributed across the stages of the consumer decision-making process? To answer these questions, this study will be conducted by a survey methodology to collect the data

Reduce Uncertainty of Online Potential Mates: Employing Signalling Theory

The online dating environment is full of uncertainties, and thus online daters use various searchable and experiential cues to determine whether online potential partners are in line with their expectations. Uncertainties caused by information asymmetry between dating parties are likely to influence their predicted outcome value judgment. To reduce the uncertainty of online mating, we propose a research model based on signalling theory to examine how two evaluative approach (the trait-evaluation and live-interaction approach) influence the level of online mate uncertainty and the predicted outcome value judgment of online daters. In addition, we also examine the moderating effect of perceived physical attractiveness on the relationship between online mates’ levels of uncertainty and the perceived outcome value judgment. The contributions of two evaluative approach on online dating are also discussed in this study

Fractional Quantum Hall Effect of Hard-Core Bosons in Topological Flat Bands

Recent proposals of topological flat band (TFB) models have provided a new route to realize the fractional quantum Hall effect (FQHE) without Landau levels. We study hard-core bosons with short-range interactions in two representative TFB models, one of which is the well known Haldane model (but with different parameters). We demonstrate that FQHE states emerge with signatures of even number of quasi-degenerate ground states on a torus and a robust spectrum gap separating these states from higher energy spectrum. We also establish quantum phase diagrams for the filling factor 1/2 and illustrate quantum phase transitions to other competing symmetry-breaking phases.Comment: 4 pages, 6 figure