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Collaborative filtering is widely used in recommender systems. When training data are extremely sparse, neighbor selection methods work ineffectively. To address this issue, this paper proposes a distributed representation model that represents users as low-dimensional vectors for neighbor selection by considering the chronological order of users' ratings. Experiments show that the proposed method...
In this paper, a method is proposed for classification of patients with disorder of consciousness (DOC) based on the diffusion tensor imaging (DTI) sequences analysis. The patients are divided into vegetative state (VS) and minimally consciousness state (MCS). Firstly, tract-based spatial statistics (TBSS) was applied to find the regions of interest (ROIs), and the values of fractional anisotropy...
A new multiple classifier system (MCS) is proposed based on CTSP (classification based on Testing Sample Pairs), which is a kind of applicable and efficient classification method. However, the original output form of the CTSP is only crisp class labels. To make use of the information provided by the classifier, in this paper, the output of CTSP is modeled using the membership function. Then, the fuzzy-cautious...
Graphene-boron nitride (BN) heterostructures provide a versatile platform to flexibly tune the sign of the group velocity of the hybrid plasmon-phonon-polaritons, enabling all-angle negative refraction between graphene plasmons, BN's phonon polaritons and their hybrid polaritons.
We theoretically propose a pathway to low-loss plasmonics. We show that dielectric-on-metal nanoresonators scatter more strongly than is possible in all-metal or all-dielectric approaches, offer near-unity-efficiency spontaneous-emission enhancements, and are robust to quantum corrections.
We present experimental results demonstrating multiple order Smith-Purcell radiation in high aspect ratio Silicon Nanowires structures using low-energy electrons (2.5–10keV). These produce emission spanning the visible, paving the way to a fully tunable ultraviolet source.
We report generation of terahertz repetition rate pulse directly from Erbium-Ytterbium co-doped fiber based on the combination effect of amplification and nonlinear phase locking. The repetition rate is up to 2.75 terahertz and the pulse width is 100 femtosecond.
Focused electron beams can induce electromagnetic radiation from periodic surfaces. We have used low-energy electrons (1.5–6kV) to induce visible light emission from nanoscale gratings (50nm and 60nm). Our results coincide well with numerical simulations.
The goal of complex event detection is to automatically detect whether an event of interest happens in temporally untrimmed long videos which usually consist of multiple video shots. Observing some video shots in positive (resp. negative) videos are irrelevant (resp. relevant) to the given event class, we formulate this task as a multi-instance learning (MIL) problem by taking each video as a bag...
The microgrid concept was proposed as a way to facilitate the integration of distributed renewable energy resources. However, due to the use of distributed energy resources (DERs) microgrids face new protection challenges that need resolved. One of those challenges is that traditional protection methods, such as overcurrent protection, cannot be used mainly because of low fault currents, bi-directionality...
As the complexity of the ocean environment, shape of towed array changes with time and space, so the accurate measurement shape of towed array is the key to improve the performance of signal processing. To solve this problem this paper proposes an estimation method based on genetic algorithm, firstly, established the objective function according to a known distance and azimuth of the target by beam...
Zero-shot learning (ZSL) aims to transfer knowledge from observed classes to the unseen classes, based on the assumption that both the seen and unseen classes share a common semantic space, among which attributes enjoy a great popularity. However, few works study whether the human-designed semantic attributes are discriminative enough to recognize different classes. Moreover, attributes are often...
Convolutional Neural Network (CNN) has led to significant progress in face recognition. Currently most CNNbased face recognition methods follow a two-step pipeline, i.e. a detected face is first aligned to a canonical one predefined by a mean face shape, and then it is fed into a CNN to extract features for recognition. The alignment step transforms all faces to the same shape, which can cause loss...
Heap overflow is one of the most widely exploited vulnerabilities, with a large number of heap overflow instances reported every year. It is important to decide whether a crash caused by heap overflow can be turned into an exploit. Efficient and effective assessment of exploitability of crashes facilitates to identify severe vulnerabilities and thus prioritize resources. In this paper, we propose...
In-app advertising provides a monetization solution for free apps, but also consumes lots of energy due to the long tail problem in cellular networks. To reduce the tail energy, we can predict the number of ads needed in the future and then prefetch those ads together instead of periodically. However, prefetching unnecessary ads may waste both energy and cellular bandwidth, and this problem becomes...
Smartwatches are quickly gaining popularity, but their limited battery life remains an important factor that adversely affects user satisfaction. To provide full functionality, smartwatches are usually connected to phones via Bluetooth. However, the Bluetooth power characteristics and the energy impact of Bluetooth data traffic have been rarely studied. To address this issue, we first establish the...
This paper presents the DeepCD framework which learns a pair of complementary descriptors jointly for image patch representation by employing deep learning techniques. It can be achieved by taking any descriptor learning architecture for learning a leading descriptor and augmenting the architecture with an additional network stream for learning a complementary descriptor. To enforce the complementary...
The main contribution of this paper is a simple semisupervised pipeline that only uses the original training set without collecting extra data. It is challenging in 1) how to obtain more training data only from the training set and 2) how to use the newly generated data. In this work, the generative adversarial network (GAN) is used to generate unlabeled samples. We propose the label smoothing regularization...
A dual-frequency linear-to-circular polarization converter with half transmission and half reflection is designed using a single-layered metamaterial composed of coupled split ring resonators(SRRs) in this paper. The unit cell of this metamaterial structure include two pairs of coupled SRRs of different sizes, and is periodically arranged in plane. The simulated results show that the metamaterial...
How to precisely evaluate the characteristics of glioma tumor in vivo is a challenging question for surgical resection clinically. Due to the infiltration feature of the tumor, precise resection remains challenging because of the uncertainties of surrounding vasculature. The sensitivity of flow measurement is improved by ultrafast plane-wave imaging which is capable of delineating the flow information...
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