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Unit Commitment With Gas Network AwarenessFeb 08 2019Recent changes in the fuel mix for electricity generation and, in particular, the increase in Gas-Fueled Power Plants (GFPP), have created significant interdependencies between the electrical power and natural gas transmission systems. However, despite ... More

Benders Decomposition for a Class of Mathematical Programs with Constraints on Dual VariablesFeb 12 2019Interdependent systems with mutual feedback are best represented as a multi-level mathematical programming, in which the leader decisions determine the follower operations, which subsequently affect the leader operations. For instance, a recent paper ... More

Communication-Constrained Expansion Planning for Resilient Distribution SystemsJan 10 2018Distributed generation and remotely controlled switches have emerged as important technologies to improve the resiliency of distribution grids against extreme weather-related disturbances. Therefore it becomes impor- tant to study how best to place them ... More

Concatenated Raptor Codes in NAND Flash MemoryDec 20 2013Two concatenated coding schemes based on fixed-rate Raptor codes are proposed for error control in NAND flash memory. One is geared for off-line recovery of uncorrectable pages and the other is designed for page error correction during the normal read ... More

The exceptional set in a generalized Goldbach`s problemOct 14 2015Mar 08 2016In this paper, we compute the size of the exceptional set in a generalized Goldbach problem and show that for a given polynomial $f(x) \in \mathbb{Z}[x]$ with a positive leading coefficient, positive integers $A$, $B$, $g$ and $0 \leq i, j < g$, there ... More

Hardy's inequality in a limiting case on general bounded domainsJul 13 2017Mar 08 2018In this paper, we study Hardy's inequality in a limiting case: $$ \int_{\Omega} |\nabla u |^N dx \ge C_N(\Omega) \int_{\Omega} \frac{|u(x)|^N}{|x|^N \left(\log \frac{R}{|x|} \right)^N} dx $$ for functions $u \in W^{1,N}_0(\Omega)$, where $\Omega$ is a ... More

Symmetry and monotonicity of least energy solutionsJun 02 2008We give a simple proof of the fact that for a large class of quasilinear elliptic equations and systems the solutions that minimize the corresponding energy in the set of all solutions are radially symmetric. We require just continuous nonlinearities ... More

Parallel Multi-Dimensional LSTM, With Application to Fast Biomedical Volumetric Image SegmentationJun 24 2015Convolutional Neural Networks (CNNs) can be shifted across 2D images or 3D videos to segment them. They have a fixed input size and typically perceive only small local contexts of the pixels to be classified as foreground or background. In contrast, Multi-Dimensional ... More

On a conjecture of Gross and ZagierJan 26 2015Nov 02 2015Gross and Zagier conjectured that if the analytic rank of a rational elliptic curve is 1, then the order of the rational torsion subgroup of the elliptic curve divides the product of Tamagawa number, Manin constant, and the square root of the order of ... More

Selective Deep Convolutional Neural Network for Low Cost Distorted Image ClassificationJul 04 2018Deep convolutional neural networks have proven to be well suited for image classification applications. However, if there is distortion in the image, the classification accuracy can be significantly degraded, even with state-of-the-art neural networks. ... More

ContextVP: Fully Context-Aware Video PredictionOct 23 2017Sep 09 2018Video prediction models based on convolutional networks, recurrent networks, and their combinations often result in blurry predictions. We identify an important contributing factor for imprecise predictions that has not been studied adequately in the ... More

Semimetallicity and Negative Differential Resistance from Hybrid Halide Perovskite NanowiresDec 03 2018In the rapidly progressing field of organometal halide perovskites, the dimensional reduction could open up new opportunities for device applications. Herein, taking the recently synthesized trimethylsulfonium lead triiodide (CH$_3$)$_3$SPbI$_3$ perovskite ... More

Selective Deep Convolutional Neural Network for Low Cost Distorted Image ClassificationJul 04 2018Feb 14 2019Deep convolutional neural networks have proven to be well suited for image classification applications. However, if there is distortion in the image, the classification accuracy can be significantly degraded, even with state-of-the-art neural networks. ... More

Data-Driven Forecasting of High-Dimensional Chaotic Systems with Long Short-Term Memory NetworksFeb 21 2018Jul 10 2018We introduce a data-driven forecasting method for high-dimensional chaotic systems using long short-term memory (LSTM) recurrent neural networks. The proposed LSTM neural networks perform inference of high-dimensional dynamical systems in their reduced ... More

Boosting segmentation with weak supervision from image-to-image translationApr 02 2019In many cases, especially with medical images, it is prohibitively challenging to produce a sufficiently large training sample of pixel-level annotations to train deep neural networks for semantic image segmentation. On the other hand, some information ... More

Boosting segmentation with weak supervision from image-to-image translationApr 02 2019Apr 04 2019In many cases, especially with medical images, it is prohibitively challenging to produce a sufficiently large training sample of pixel-level annotations to train deep neural networks for semantic image segmentation. On the other hand, some information ... More

The Infrared Medium-deep Survey. VI. Discovery of Faint Quasars at $z\sim5$ with a Medium-band-based ApproachNov 21 2018Nov 22 2018The faint quasars with $M_{1450}>-24$ mag are known to hold the key to the determination of the ultraviolet emissivity for the cosmic re-ionization. But only a few have been identified so far because of the limitations on the survey data. Here, we present ... More

Intensive Monitoring Survey of Nearby Galaxies (IMSNG)Jan 31 2019Intensive Monitoring Survey of Nearby Galaxies (IMSNG) is a high cadence observation program monitoring nearby galaxies with high probabilities of hosting supernovae (SNe). IMSNG aims to constrain the SN explosion mechanism by inferring sizes of SN progenitor ... More