Finding the Balance

Translating different invisible emotions, feelings and symbiotic relationships. Explore the Traditional Chinese Humanistic Philosophy of \u27Tian Ren He Yi\u27. The interwoven relationship between human, nature and machine is complicated yet beautiful. I explores how visceral emotion, feeling, language and communication all play an important part of how our bodies react, to visualize this invisible feeling. I attempts to visualize the mystery of the human body and society through various ceramic and glass techniques, such as hand-building, blowing and ceramic 3D printing. Using different methods of combining and stressing the material, capturing that resistance and embracing the outcome through a series of making and remaking of a specific object. I also explores the symbiotic relationship between human, nature and technology through combining 3D printing technique and hand building technique together. Creating a tranquil meditation space that evokes deep contemplation

Top Management Team Characteristics and Corporate Social Responsibility in China: Moderating Effect of Compensation

This study explores the relationship between top management team (TMT) characteristics and corporate social responsibility (CSR) under the moderating effect of executive compensation for 563 companies listed in China for the period 2014 to 2018. While it is proved by many researchers that TMT characteristics influence CSR, the inconsistent effect of specific characteristics observed in previous research implies the possible impact of other contingent variables. Through incorporating agency theory and upper-echelons theory, this study further investigates the moderating role of executive compensation, a significant component of corporate governance. The results show that TMTs’ average age, education level, overseas experience and academic experience are positively related to the CSR performance, while the average tenure influences the CSR performance negatively. Moreover, it is found that the compensation moderates the influence of some characteristics on CSR significantly. However, the direction and intensity of the moderating effects vary from different incentive compensation and individual characteristics. More specifically, monetary compensation strengthens the positive influence of executives’ age, education level, academic experience significantly, whereas the equity incentive weakens the positive relationship between overseas experience and academic experience. The results indicate that matched TMT characteristics and compensation design would help TMT characteristics exert a greater influence on CSR performance. Therefore, TMT composition and executive compensation should be considered at the same time to prompt CSR in China more effectively

What Should Streamers Communicate in Livestream E-Commerce? The Effects of Social Interactions on Live Streaming Performance

Compared with traditional e-commerce, livestreaming e-commerce is characterized by direct and intimate communication between streamers and consumers that stimulates instant social interactions. This study focuses on streamers’ three types of information exchange (i.e., product information, social conversation, and social solicitation) and examines their roles in driving both short-term and long-term livestreaming performance (i.e., sales and customer base growth). We find that the informational role of product information (nonpromotional and promotional) is beneficial not only to sales performance, but also to the growth of the customer base. We also find that social conversation has a relationship-building effect that positively impacts both sales and customer base growth, whereas social solicitation has both a relationship-building and a relationship-straining effect that positively affects customer base growth but can hurt sales. Furthermore, our results show that streamers’ social interactions with consumers can stimulate consumer engagement in different ways, leading to different effects on livestreaming performance

A Faster kk-means++ Algorithm

K-means++ is an important algorithm to choose initial cluster centers for the k-means clustering algorithm. In this work, we present a new algorithm that can solve the $k$-means++ problem with near optimal running time. Given $n$ data points in $\mathbb{R}^d$, the current state-of-the-art algorithm runs in $\widetilde{O}(k )$ iterations, and each iteration takes $\widetilde{O}(nd k)$ time. The overall running time is thus $\widetilde{O}(n d k^2)$. We propose a new algorithm \textsc{FastKmeans++} that only takes in $\widetilde{O}(nd + nk^2)$ time, in total

Query Complexity of Active Learning for Function Family With Nearly Orthogonal Basis

Many machine learning algorithms require large numbers of labeled data to deliver state-of-the-art results. In applications such as medical diagnosis and fraud detection, though there is an abundance of unlabeled data, it is costly to label the data by experts, experiments, or simulations. Active learning algorithms aim to reduce the number of required labeled data points while preserving performance. For many convex optimization problems such as linear regression and $p$-norm regression, there are theoretical bounds on the number of required labels to achieve a certain accuracy. We call this the query complexity of active learning. However, today's active learning algorithms require the underlying learned function to have an orthogonal basis. For example, when applying active learning to linear regression, the requirement is the target function is a linear composition of a set of orthogonal linear functions, and active learning can find the coefficients of these linear functions. We present a theoretical result to show that active learning does not need an orthogonal basis but rather only requires a nearly orthogonal basis. We provide the corresponding theoretical proofs for the function family of nearly orthogonal basis, and its applications associated with the algorithmically efficient active learning framework

A Semipersistent Plant Virus Differentially Manipulates Feeding Behaviors of Different Sexes and Biotypes of Its Whitefly Vector.

It is known that plant viruses can change the performance of their vectors. However, there have been no reports on whether or how a semipersistent plant virus manipulates the feeding behaviors of its whitefly vectors. Cucurbit chlorotic yellows virus (CCYV) (genus Crinivirus, family Closteroviridae) is an emergent plant virus in many Asian countries and is transmitted specifically by B and Q biotypes of tobacco whitefly, Bemisia tabaci (Gennadius), in a semipersistent manner. In the present study, we used electrical penetration graph (EPG) technique to investigate the effect of CCYV on the feeding behaviors of B. tabaci. The results showed that CCYV altered feeding behaviors of both biotypes and sexes of B. tabaci with different degrees. CCYV had stronger effects on feeding behaviors of Q biotype than those of B biotype, by increasing duration of phloem salivation and sap ingestion, and could differentially manipulate feeding behaviors of males and females in both biotype whiteflies, with more phloem ingestion in Q biotype males and more non-phloem probing in B biotype males than their respective females. With regard to feeding behaviors related to virus transmission, these results indicated that, when carrying CCYV, B. tabaci Q biotype plays more roles than B biotype, and males make greater contribution than females

Adore: Differentially Oblivious Relational Database Operators

There has been a recent effort in applying differential privacy on memory access patterns to enhance data privacy. This is called differential obliviousness. Differential obliviousness is a promising direction because it provides a principled trade-off between performance and desired level of privacy. To date, it is still an open question whether differential obliviousness can speed up database processing with respect to full obliviousness. In this paper, we present the design and implementation of three new major database operators: selection with projection, grouping with aggregation, and foreign key join. We prove that they satisfy the notion of differential obliviousness. Our differentially oblivious operators have reduced cache complexity, runtime complexity, and output size compared to their state-of-the-art fully oblivious counterparts. We also demonstrate that our implementation of these differentially oblivious operators can outperform their state-of-the-art fully oblivious counterparts by up to $7.4\times$.Comment: VLDB 202

Refined Equivalent Pinhole Model for Large-scale 3D Reconstruction from Spaceborne CCD Imagery

In this study, we present a large-scale earth surface reconstruction pipeline for linear-array charge-coupled device (CCD) satellite imagery. While mainstream satellite image-based reconstruction approaches perform exceptionally well, the rational functional model (RFM) is subject to several limitations. For example, the RFM has no rigorous physical interpretation and differs significantly from the pinhole imaging model; hence, it cannot be directly applied to learning-based 3D reconstruction networks and to more novel reconstruction pipelines in computer vision. Hence, in this study, we introduce a method in which the RFM is equivalent to the pinhole camera model (PCM), meaning that the internal and external parameters of the pinhole camera are used instead of the rational polynomial coefficient parameters. We then derive an error formula for this equivalent pinhole model for the first time, demonstrating the influence of the image size on the accuracy of the reconstruction. In addition, we propose a polynomial image refinement model that minimizes equivalent errors via the least squares method. The experiments were conducted using four image datasets: WHU-TLC, DFC2019, ISPRS-ZY3, and GF7. The results demonstrated that the reconstruction accuracy was proportional to the image size. Our polynomial image refinement model significantly enhanced the accuracy and completeness of the reconstruction, and achieved more significant improvements for larger-scale images.Comment: 24 page