Large stars with few colors

A recent question in generalized Ramsey theory is that for fixed positive integers $s\leq t$, at least how many vertices can be covered by the vertices of no more than $s$ monochromatic members of the family $\cal F$ in every edge coloring of $K_n$ with $t$ colors. This is related to an old problem of Chung and Liu: for graph $G$ and integers $1\leq s<t$ what is the smallest positive integer $n=R_{s,t}(G)$ such that every coloring of the edges of $K_n$ with $t$ colors contains a copy of $G$ with at most $s$ colors. We answer this question when $G$ is a star and $s$ is either $t-1$ or $t-2$ generalizing the well-known result of Burr and Roberts

A Facile, Fast, and Low-Cost Method for Fabrication of Micro/Nano-Textured Superhydrophobic Surfaces

Background Alkyl ketene dimer (AKD) is frequently used in paper industry as an inexpensive sizing agent. The formation of a fractal structure after curing the solidified AKD for an extra-long time (4 - 6 days) results in superhydrophobicity. In this study, a facile and low-cost method was utilized to turn AKD’s surface superhydrophobic in a very short period of time. Method We fabricated a superhydrophobic layer by dipping glass and paper substrates in molten AKD and then treating them with ethanol after solidification. The samples were characterized by X-ray diffraction, Scanning electron microscopy, Fourier transform-infrared spectroscopy, X-ray photoelectron spectroscopy, Confocal laser scanning microscopy, and dynamic contact angle goniometry. Results The results show that briefly treating the coatings, obtained from isothermally heated AKD melt at 40°C for 3 min, with ethanol leads to superhydrophobicity with an advancing and receding contact angle of 158.7±1.4° and 156.8±0.9°, respectively. By increasing the melt temperature to 70°C and heating time to 6 h followed by ethanol treatment, the advancing and receding contact angles increased to 163.7±1.3° and 162.6±1.2°, respectively. Conclusions This enhancement in superhydrophobicity is due to the formation of entangled irregular micro/nano textures that create air cushions on the surface resulting in droplet state transition from Wenzel to Cassie. In this method, ethanol can be used several times, and the energy consumption becomes very low. Based on the other techniques in this field, our method has eliminated the complex equipment and procedure applied in the fabrication of a superhydrophobic AKD.https://scholarscompass.vcu.edu/gradposters/1072/thumbnail.jp

Comprehensive Privacy Analysis of Deep Learning: Passive and Active White-box Inference Attacks against Centralized and Federated Learning

Deep neural networks are susceptible to various inference attacks as they remember information about their training data. We design white-box inference attacks to perform a comprehensive privacy analysis of deep learning models. We measure the privacy leakage through parameters of fully trained models as well as the parameter updates of models during training. We design inference algorithms for both centralized and federated learning, with respect to passive and active inference attackers, and assuming different adversary prior knowledge. We evaluate our novel white-box membership inference attacks against deep learning algorithms to trace their training data records. We show that a straightforward extension of the known black-box attacks to the white-box setting (through analyzing the outputs of activation functions) is ineffective. We therefore design new algorithms tailored to the white-box setting by exploiting the privacy vulnerabilities of the stochastic gradient descent algorithm, which is the algorithm used to train deep neural networks. We investigate the reasons why deep learning models may leak information about their training data. We then show that even well-generalized models are significantly susceptible to white-box membership inference attacks, by analyzing state-of-the-art pre-trained and publicly available models for the CIFAR dataset. We also show how adversarial participants, in the federated learning setting, can successfully run active membership inference attacks against other participants, even when the global model achieves high prediction accuracies.Comment: 2019 IEEE Symposium on Security and Privacy (SP

Modeling metro users' travel behavior in Tehran: Frequency of Use

Transit-oriented development (TOD), as a sustainable supporting strategy, emphasizes the improvement of public transportation coverage and quality, land use density and diversity around public transportation stations and priority of walking and cycling at station areas. Traffic, environmental and economic problems arising from high growth of private cars, inappropriate distribution of land use, and car-orientation of the metropolitan area, necessitate adoption of TOD. In recent years, extensive research into urban development and transportation has focused on this strategy. This research in which metro stations are considered as a base for development, aims to model metro users' travel behavior and decision-making procedures. In this regard, the research question is: what are the parameters or factors affecting the frequency of travel by metro in a half-mile radius from stations. The radius was determined based on TOD definitions and five-minute walking time to metro stations. A questionnaire was designed in three sections that include travel features by metro, attitudes toward metro, and economic and social characteristics of respondents. Ten stations were selected based on their geographic dispersion in Tehran and a sample of 450 respondents was determined. The questionnaires were surveyed face to face in (half-mile) vicinity of metro stations. Based on a refined sample on 400 questionnaires ordered discrete choice models were considered. Results of descriptive statistics show that 38.5 percent of the sample used metro more than 4 times per week. Trip purpose for 45.7 percent of metro users is work. Access mode to the metro stations for nearly half of the users (47.6 percent) is bus. The results of ordered logit models show a number of significant variables including: habit of using the metro, waiting time in stations, trip purpose (working, shopping and recreation), personal car access mode to the metro station, walking access mode to the metro station and being a housewife