arXiv subjects

Bin Yang

Publications and source records attributed to Bin Yang.

At least 415 records · Page 23Linked to original sources

arXiv2018

On the Feasibility of Generic Deep Disaggregation for Single-Load Extraction

Recently, and with the growing development of big energy datasets, data-driven learning techniques began to represent a potential solution to the energy disaggregation problem outperforming engineered and hand-crafted models. However, most proposed deep disaggregation models are load-dependent in the sense that either expert knowledge or a hyper-parameter optimization stage is required prior to training and deployment (normally for each load category) even upon acquisition and cleansing of aggregate and sub-metered data. In this paper, we present a feasibility study on the development of a generic disaggregation model based on data-driven learning. Specifically, we present a generic deep disaggregation model capable of achieving state-of-art performance in load monitoring for a variety of load categories. The developed model is evaluated on the publicly available UK-DALE dataset with a moderately low sampling frequency and various domestic loads.

cs.LG↗

arXiv2018

Selective Sampling and Mixture Models in Generative Adversarial Networks

In this paper, we propose a multi-generator extension to the adversarial training framework, in which the objective of each generator is to represent a unique component of a target mixture distribution. In the training phase, the generators cooperate to represent, as a mixture, the target distribution while maintaining distinct manifolds. As opposed to traditional generative models, inference from a particular generator after training resembles selective sampling from a unique component in the target distribution. We demonstrate the feasibility of the proposed architecture both analytically and with basic Multi-Layer Perceptron (MLP) models trained on the MNIST dataset.

cs.LG↗

arXiv2018

Dense Small Cell Networks: From Noise-Limited to Dense Interference-Limited

Considering both non-line-of-sight (NLoS) and line-of-sight (LoS) transmissions, the transitional behaviors from noise-limited regime to dense interference-limited regime have been investigated for the fifth generation (5G) small cell networks (SCNs). Besides, we identify four performance regimes based on base station (BS) density, i.e., (i) the noise-limited regime, (ii) the signal-dominated regime, (iii) the interference-dominated regime, and (iv) the interference-limited regime. To characterize the performance regime, we propose a unified framework analyzing the future 5G wireless networks over generalized shadowing/fading channels, in which the user association schemes based on the strongest instantaneous received power (SIRP) and the strongest average received power (SARP) can be studied, while NLoS/LoS transmissions and multi-slop path loss model are considered. Simulation results indicate that different factors, i.e., noise, desired signal, and interference, successively and separately dominate the network performance with the increase of BS density. Hence, our results shed new light on the design and management of SCNs in urban and rural areas with different BS deployment densities.

cs.NI↗

arXiv2017

Spectroscopy and thermal modelling of the first interstellar object 1I/2017 U1 'Oumuamua

During the formation and evolution of the Solar System, significant numbers of cometary and asteroidal bodies were ejected into interstellar space$^{1,2}$. It can be reasonably expected that the same happened for planetary systems other than our own. Detection of such Inter- stellar Objects (ISOs) would allow us to probe the planetesimal formation processes around other stars, possibly together with the effects of long-term exposure to the interstellar medium. 1I/2017 U1 'Oumuamua is the first known ISO, discovered by the Pan-STARRS1 telescope in October 2017$^3$.The discovery epoch photometry implies a highly elongated body with radii of $\sim 200 \times 20$ m when a comet-like geometric albedo of 0.04 is assumed. Here we report spectroscopic characterisation of 'Oumuamua, finding it to be variable with time but similar to organically rich surfaces found in the outer Solar System. The observable ISO population is expected to be dominated by comet-like bodies in agreement with our spectra, yet the reported inactivity implies a lack of surface ice. We show this is consistent with predictions of an insulating mantle produced by long-term cosmic ray exposure. An internal icy composition cannot therefore be ruled out by the lack of activity, even though 'Oumuamua passed within 0.25 au of the Sun.

astro-ph.EP↗

arXiv2017

On the Energy-Efficient Deployment for Ultra-Dense Heterogeneous Networks with NLoS and LoS Transmissions

We investigate network performance of ultra-dense heterogeneous networks (HetNets) and study the maximum energy-efficient base station (BS) deployment incorporating probabilistic non-line-of-sight (NLoS) and line-of-sight (LoS) transmissions. First, we develop an analytical framework with the maximum instantaneous received power (MIRP) and the maximum average received power (MARP) association schemes to model the coverage probability and related performance metrics, e.g., the potential throughput (PT) and the energy efficiency (EE). Second, we formulate two optimization problems to achieve the maximum energy-efficient deployment solution with specific service criteria. Simulation results show that there are tradeoffs among the coverage probability, the total power consumption, and the EE. To be specific, the maximum coverage probability with ideal power consumption is superior to that with practical power consumption when the total power constraint is small and inferior to that with practical power consumption when the total power constraint becomes large. Moreover, the maximum EE is a decreasing function with respect to the coverage probability constraint.

cs.NI↗

arXiv2017

Isotopic ratios in outbursting comet C/2015 ER61

Isotopic ratios in comets are critical to understanding the origin of cometary material and the physical and chemical conditions in the early solar nebula. Comet C/2015 ER61 (PANSTARRS) underwent an outburst with a total brightness increase of 2 magnitudes on the night of 2017 April 4. The sharp increase in brightness offered a rare opportunity to measure the isotopic ratios of the light elements in the coma of this comet. We obtained two high-resolution spectra of C/2015 ER61 with UVES/VLT on the nights of 2017 April 13 and 17. At the time of our observations, the comet was fading gradually following the outburst. We measured the nitrogen and carbon isotopic ratios from the CN violet (0,0) band and found that $^{12}$C/$^{13}$C=100 $\pm$ 15, $^{14}$N/$^{15}$N=130 $\pm$ 15. In addition, we determined the $^{14}$N/$^{15}$N ratio from four pairs of NH$_2$ isotopolog lines and measured $^{14}$N/$^{15}$N=140 $\pm$ 28. The measured isotopic ratios of C/2015 ER61 do not deviate significantly from those of other comets.

astro-ph.EP↗

arXiv2017

Reliable Energy-Efficient Routing Algorithm for Vehicle-Assisted Wireless Ad-Hoc Networks

We investigate the design of the optimal routing path in a moving vehicles involved the internet of things (IoT). In our model, jammers exist that may interfere with the information exchange between wireless nodes, leading to worsened quality of service (QoS) in communications. In addition, the transmit power of each battery-equipped node is constrained to save energy. We propose a three-step optimal routing path algorithm for reliable and energy-efficient communications. Moreover, results show that with the assistance of moving vehicles, the total energy consumed can be reduced to a large extend. We also study the impact on the optimal routing path design and energy consumption which is caused by path loss, maximum transmit power constrain, QoS requirement, etc.

cs.NI↗

arXiv2017

The Main Belt Comets and Ice in the Solar System

We review the evidence for buried ice in the asteroid belt; specifically the questions around the so-called Main Belt Comets (MBCs). We summarise the evidence for water throughout the Solar System, and describe the various methods for detecting it, including remote sensing from ultraviolet to radio wavelengths. We review progress in the first decade of study of MBCs, including observations, modelling of ice survival, and discussion on their origins. We then look at which methods will likely be most effective for further progress, including the key challenge of direct detection of (escaping) water in these bodies.

astro-ph.EP↗

arXiv2017

Thermophysical characteristics of the large main-belt asteroid (349) Dembowska

(349) Dembowska, a large, bright main-belt asteroid, has a fast rotation and oblique spin axis. It may have experienced partial melting and differentiation. We constrain Dembowska's thermophysical properties, e.g., thermal inertia, roughness fraction, geometric albedo and effective diameter within 3$σ$ uncertainty of $Γ=20^{+12}_{-7}\rm~Jm^{-2}s^{-0.5}K^{-1}$, $f_{\rm r}=0.25^{+0.60}_{-0.25}$, $p_{\rm v}=0.309^{+0.026}_{-0.038}$, and $D_{\rm eff}=155.8^{+7.5}_{-6.2}\rm~km$, by utilizing the Advanced Thermophysical Model (ATPM) to analyse four sets of thermal infrared data obtained by IRAS, AKARI, WISE and Subaru/COMICS at different epochs. In addition, by modeling the thermal lightcurve observed by WISE, we obtain the rotational phases of each dataset. These rotationally resolved data do not reveal significant variations of thermal inertia and roughness across the surface, indicating the surface of Dembowska should be covered by a dusty regolith layer with few rocks or boulders. Besides, the low thermal inertia of Dembowska show no significant difference with other asteroids larger than 100 km, indicating the dynamical lives of these large asteroids are long enough to make the surface to have sufficiently low thermal inertia. Furthermore, based on the derived surface thermophysical properties, as well as the known orbital and rotational parameters, we can simulate Dembowska's surface and subsurface temperature throughout its orbital period. The surface temperature varies from $\sim40$ K to $\sim220$ K, showing significant seasonal variation, whereas the subsurface temperature achieves equilibrium temperature about $120\sim160$ K below $30\sim50$ cm depth.

astro-ph.EP↗

arXiv2017

T-CNN: Tubelets with Convolutional Neural Networks for Object Detection from Videos

The state-of-the-art performance for object detection has been significantly improved over the past two years. Besides the introduction of powerful deep neural networks such as GoogleNet and VGG, novel object detection frameworks such as R-CNN and its successors, Fast R-CNN and Faster R-CNN, play an essential role in improving the state-of-the-art. Despite their effectiveness on still images, those frameworks are not specifically designed for object detection from videos. Temporal and contextual information of videos are not fully investigated and utilized. In this work, we propose a deep learning framework that incorporates temporal and contextual information from tubelets obtained in videos, which dramatically improves the baseline performance of existing still-image detection frameworks when they are applied to videos. It is called T-CNN, i.e. tubelets with convolutional neueral networks. The proposed framework won the recently introduced object-detection-from-video (VID) task with provided data in the ImageNet Large-Scale Visual Recognition Challenge 2015 (ILSVRC2015).

cs.CV↗

arXiv2017

X-shooter search for outgassing from Main Belt Comet P/2012 T1 (Pan-STARRS)

Main Belt Comets are a recently identified population of minor bodies with stable asteroid-like orbits but cometary appearances. Sublimation of water ice is the most likely mechanism for their recurrent activity (i.e. dust tails and dust comae), although there has been no direct detection of gas. These peculiar objects could hold the key to the origin of water on Earth. In this paper we present a search for the gas responsible for lifting dust from P/2012 T1 (Pan-STARRS), and review previous attempts at such measurements. To date such searches have mainly been indirect, looking for the common cometary gas CN rather than gasses related to water itself. We use the VLT and X-shooter to search for emission from OH in the UV, a direct dissociation product of water. We do not detect any emission lines, and place an upper limit on water production rate from P/2012 T1 of $8-9\times10^{25}$ molecules s$^{-1}$. This is similar to limits derived from observations using the Herschel space telescope. We conclude that the best current facilities are incapable of detecting water emission at the exceptionally low levels required to produce the observed activity in Main Belt Comets.

astro-ph.EP↗

arXiv2017

Performance Analysis of Dense Small Cell Networks with Generalized Fading

In this paper, we propose a unified framework to analyze the performance of dense small cell networks (SCNs) in terms of the coverage probability and the area spectral efficiency (ASE). In our analysis, we consider a practical path loss model that accounts for both non-line-of-sight (NLOS) and line-of-sight (LOS) transmissions. Furthermore, we adopt a generalized fading model, in which Rayleigh fading, Rician fading and Nakagami-m fading can be treated in a unified framework. The analytical results of the coverage probability and the ASE are derived, using a generalized stochastic geometry analysis. Different from existing work that does not differentiate NLOS and LOS transmissions, our results show that NLOS and LOS transmissions have a significant impact on the coverage probability and the ASE performance, particularly when the SCNs grow dense. Furthermore, our results establish for the first time that the performance of the SCNs can be divided into four regimes, according to the intensity (aka density) of BSs, where in each regime the performance is dominated by different factors.

cs.NI↗

arXiv2016

TorontoCity: Seeing the World with a Million Eyes

In this paper we introduce the TorontoCity benchmark, which covers the full greater Toronto area (GTA) with 712.5 $km^2$ of land, 8439 $km$ of road and around 400,000 buildings. Our benchmark provides different perspectives of the world captured from airplanes, drones and cars driving around the city. Manually labeling such a large scale dataset is infeasible. Instead, we propose to utilize different sources of high-precision maps to create our ground truth. Towards this goal, we develop algorithms that allow us to align all data sources with the maps while requiring minimal human supervision. We have designed a wide variety of tasks including building height estimation (reconstruction), road centerline and curb extraction, building instance segmentation, building contour extraction (reorganization), semantic labeling and scene type classification (recognition). Our pilot study shows that most of these tasks are still difficult for modern convolutional neural networks.

cs.CV↗

arXiv2016

Shape model of asteroid (130) Elektra from optical photometry and disk-resolved images from VLT/SPHERE and Nirc2/Keck

Asteroid (130) Elektra belongs to one of the six known triple asteroids in the main belt, so its mass has been reliably determined. We aim to use all available disk-resolved images of (130) Elektra obtained by the SPHERE instrument at VLT and by the Nirc2 of the Keck telescope together with the disk-integrated photometry to determine its shape model and its size. The volume can be then used in combination with the known mass to derive the bulk density of the primary. We apply the All-Data Asteroid Modeling (ADAM) algorithm to the optical disk-integrated data, 2 disk-resolved images obtained by the SPHERE instrument and 13 disk-resolved images from the Nirc2 of the Keck telescope, and derive the shape model and size of Elektra. We present the shape model, volume-equivalent diameter (199$\pm$7 km) and bulk density (1.60$\pm$0.13 g cm$^{-3}$) of the C-type asteroid Elektra.

astro-ph.EP↗

arXiv2016

Near-infrared thermal emission from near-Earth asteroids: Aspect-dependent variability

Here we explore a technique for constraining physical properties of near-Earth asteroids (NEAs) based on variability in thermal emission as a function of viewing aspect. We present case studies of the low albedo, near-Earth asteroids (285263) 1998 QE2 and (175706) 1996 FG3. The Near-Earth Asteroid Thermal Model (NEATM) is used to fit signatures of thermal emission in near-infrared (0.8 - 2.5 micron) spectral data. This analysis represents a systematic study of thermal variability in the near-IR as a function of phase angle. The observations of QE2 imply that carefully timed observations from multiple viewing geometries can be used to constrain physical properties like retrograde versus prograde pole orientation and thermal inertia. The FG3 results are more ambiguous with detected thermal variability possibly due to systematic issues with NEATM, an unexpected prograde rotation state, or a surface that is spectrally and thermally heterogenous. This study highlights the potential diagnostic importance of high phase angle thermal measurements on both sides of opposition. We find that the NEATM thermal beaming parameters derived from our near-IR data tend to be of order 10's of percent higher than parameters from ensemble analyses of longer wavelength data sets. However, a systematic comparison of NEATM applied to data in different wavelength regimes is needed to understand whether this offset is simply a reflection of small number statistics or an intrinsic limitation of NEATM when applied to near-IR data. With the small sample presented here, it remains unclear whether NEATM modeling at near-IR wavelengths can robustly determine physical properties like pole orientation and thermal inertia.

astro-ph.EP↗

arXiv2016

Crafting GBD-Net for Object Detection

The visual cues from multiple support regions of different sizes and resolutions are complementary in classifying a candidate box in object detection. Effective integration of local and contextual visual cues from these regions has become a fundamental problem in object detection. In this paper, we propose a gated bi-directional CNN (GBD-Net) to pass messages among features from different support regions during both feature learning and feature extraction. Such message passing can be implemented through convolution between neighboring support regions in two directions and can be conducted in various layers. Therefore, local and contextual visual patterns can validate the existence of each other by learning their nonlinear relationships and their close interactions are modeled in a more complex way. It is also shown that message passing is not always helpful but dependent on individual samples. Gated functions are therefore needed to control message transmission, whose on-or-offs are controlled by extra visual evidence from the input sample. The effectiveness of GBD-Net is shown through experiments on three object detection datasets, ImageNet, Pascal VOC2007 and Microsoft COCO. This paper also shows the details of our approach in wining the ImageNet object detection challenge of 2016, with source code provided on \url{https://github.com/craftGBD/craftGBD}.

cs.CV↗

arXiv2016

Coverage Analysis of Heterogeneous Cellular Networks in Urban Areas

In this article, a network model incorporating both line-of-sight (LOS) and non-line-of-sight (NLOS) transmissions is proposed to investigate impacts of blockages in urban areas on heterogeneous network coverage performance. Results show that co-existence of NLOS and LOS transmissions has a significant impact on network performance. We find in urban areas, that deploying more BSs in different tiers is better than merely deploying all BSs in the same tier in terms of coverage probability.

cs.NI↗

arXiv2016

CRAFT Objects from Images

Object detection is a fundamental problem in image understanding. One popular solution is the R-CNN framework and its fast versions. They decompose the object detection problem into two cascaded easier tasks: 1) generating object proposals from images, 2) classifying proposals into various object categories. Despite that we are handling with two relatively easier tasks, they are not solved perfectly and there's still room for improvement. In this paper, we push the "divide and conquer" solution even further by dividing each task into two sub-tasks. We call the proposed method "CRAFT" (Cascade Region-proposal-network And FasT-rcnn), which tackles each task with a carefully designed network cascade. We show that the cascade structure helps in both tasks: in proposal generation, it provides more compact and better localized object proposals; in object classification, it reduces false positives (mainly between ambiguous categories) by capturing both inter- and intra-category variances. CRAFT achieves consistent and considerable improvement over the state-of-the-art on object detection benchmarks like PASCAL VOC 07/12 and ILSVRC.

cs.CV↗