arXiv subjects

Tao Ye

Publications and source records attributed to Tao Ye.

31 records · Page 2Linked to original sources

arXiv2020

Music Classification in MIDI Format based on LSTM Mdel

Music classification between music made by AI or human composers can be done by deep learning networks. We first transformed music samples in midi format to natural language sequences, then classified these samples by mLSTM (multiplicative Long Short Term Memory) + logistic regression. The accuracy of the result evaluated by 10-fold cross validation can reach 90%. Our work indicates that music generated by AI and human composers do have different characteristics, which can be learned by deep learning networks.

cs.SD↗

arXiv2020

Microscopic study of the $^{7}$Li-nucleus potential

The optical potential without any free parameters for $^7$Li-nucleus interaction system is studied in a microscopic approach. It is obtained by folding the microscopic optical potentials of the constituent nucleons of $^{7}$Li over their density distributions. We employ an isospin-dependent nucleon microscopic optical potential, which is based on the Skyrme nucleon-nucleon effective interaction and derived by using the Green's function method, to be the nucleon optical potential. Harmonic oscillator shell model is used to describe the internal wave function of $^7$Li and get the nucleon density distribution. The $^7$Li microscopic optical potential is used to predict the reaction cross sections and elastic scattering angular distributions for target range from $^{27}$Al to $^{208}$Pb and energy range below 450 MeV. Generally the results can reproduce the measured data reasonably well. In addition, the microscopic optical potential is comparable to a global phenomenological optical potential in fitting the presently existing measured data generally.

nucl-th↗

arXiv2018

Communicating Two States in Perovskite Revealed by Time-Resolved Photoluminescence Spectroscopy

Organic-inorganic perovskite as a promising candidate for solar energy harvesting has attracted immense interest for its low-cost preparation and extremely high quantum efficiency. However, the fundamental understanding of the photophysics in perovskite remains elusive. In this work, we have revealed two distinct states in MAPbI3 thin films at low temperature through time-resolved photoluminescence spectroscopy (TRPL). In particular, we observe a photo-induced carrier injection from the high energy (HE) state to the low energy (LE) state which has a longer lifetime. The strong interaction between the two states, evidenced by the injection kinetics, can be sensitively controlled through the excitation power. Understanding the interacting two-states not only sheds light on the long PL lifetime in perovskite but also helps to understand the different behavior of perovskite in response to different excitation power. Further efforts in modifying the low energy state could significantly improve the quantum efficiency and lead to novel application in optoelectronics based on perovskite.

physics.app-ph↗

arXiv2018

Modeling Musical Taste Evolution with Recurrent Neural Networks

Finding the music of the moment can often be a challenging problem, even for well-versed music listeners. Musical tastes are constantly in flux, and the problem of developing computational models for musical taste dynamics presents a rich and nebulous problem space. A variety of factors all play some role in determining preferences (e.g., popularity, musicological, social, geographical, generational), and these factors vary across different listeners and contexts. In this paper, we leverage a massive dataset on internet radio station creation from a large music streaming company in order to develop computational models of listener taste evolution. We delve deep into the complexities of this domain, identifying some of the unique challenges that it presents, and develop a model utilizing recurrent neural networks. We apply our model to the problem of next station prediction and show that it not only outperforms several baselines, but excels at long tail music personalization, particularly by learning the long-term dependency structure of listener music preference evolution.

cs.IR↗

arXiv2018

Exceed Improved Efficient Perovskite Solar Cells Under Dual-Irradiation System

In general, perovskite solar cells (PSC) with a sensitized or thin film architecture absorb light from a single illumination. This paper reported a PSC architecture with a semitransparent Au/ITO counter electrode, which allows light to pass it partially. When the device was illuminated simultaneously from both the FTO and Au/ITO sides, the PSC has achieved an overall power conversion efficiency (PCE) as high as 20.1% under high light intensity (1.4 sun), which is much higher than that of the single-irradiation system.

physics.app-ph↗

arXiv2014

A Multi-parent Memetic Algorithm for the Linear Ordering Problem

In this paper, we present a multi-parent memetic algorithm (denoted by MPM) for solving the classic Linear Ordering Problem (LOP). The MPM algorithm integrates in particular a multi-parent recombination operator for generating offspring solutions and a distance-and-quality based criterion for pool updating. Our MPM algorithm is assessed on 8 sets of 484 widely used LOP instances and compared with several state-of-the-art algorithms in the literature, showing the efficacy of the MPM algorithm. Specifically, for the 255 instances whose optimal solutions are unknown, the MPM is able to detect better solutions than the previous best-known ones for 66 instances, while matching the previous best-known results for 163 instances. Furthermore, some additional experiments are carried out to analyze the key elements and important parameters of MPM.

cs.NE↗

arXiv2014

A Memetic Algorithm for the Linear Ordering Problem with Cumulative Costs

This paper introduces an effective memetic algorithm for the linear ordering problem with cumulative costs. The proposed algorithm combines an order-based recombination operator with an improved forward-backward local search procedure and employs a solution quality based replacement criterion for pool updating. Extensive experiments on 118 well-known benchmark instances show that the proposed algorithm achieves competitive results by identifying 46 new upper bounds. Furthermore, some critical ingredients of our algorithm are analyzed to understand the source of its performance.

cs.NE↗

arXiv2013

Iterated Tabu Search Algorithm for Packing Unequal Circles in a Circle

This paper presents an Iterated Tabu Search algorithm (denoted by ITS-PUCC) for solving the problem of Packing Unequal Circles in a Circle. The algorithm exploits the continuous and combinatorial nature of the unequal circles packing problem. It uses a continuous local optimization method to generate locally optimal packings. Meanwhile, it builds a neighborhood structure on the set of local minimum via two appropriate perturbation moves and integrates two combinatorial optimization methods, Tabu Search and Iterated Local Search, to systematically search for good local minima. Computational experiments on two sets of widely-used test instances prove its effectiveness and efficiency. For the first set of 46 instances coming from the famous circle packing contest and the second set of 24 instances widely used in the literature, the algorithm is able to discover respectively 14 and 16 better solutions than the previous best-known records.

math.OC↗

arXiv2013

Integrating tabu search and VLSN search to develop enhanced algorithms: A case study using bipartite boolean quadratic programs

The bipartite boolean quadratic programming problem (BBQP) is a generalization of the well studied boolean quadratic programming problem. The model has a variety of real life applications; however, empirical studies of the model are not available in the literature, except in a few isolated instances. In this paper, we develop efficient heuristic algorithms based on tabu search, very large scale neighborhood (VLSN) search, and a hybrid algorithm that integrates the two. The computational study establishes that effective integration of simple tabu search with VLSN search results in superior outcomes, and suggests the value of such an integration in other settings. Complexity analysis and implementation details are provided along with conclusions drawn from experimental analysis. In addition, we obtain solutions better than the best previously known for almost all medium and large size benchmark instances.

cs.AI↗

arXiv2013

Application of machine learning algorithms to the study of noise artifacts in gravitational-wave data

The sensitivity of searches for astrophysical transients in data from the LIGO is generally limited by the presence of transient, non-Gaussian noise artifacts, which occur at a high-enough rate such that accidental coincidence across multiple detectors is non-negligible. Furthermore, non-Gaussian noise artifacts typically dominate over the background contributed from stationary noise. These "glitches" can easily be confused for transient gravitational-wave signals, and their robust identification and removal will help any search for astrophysical gravitational-waves. We apply Machine Learning Algorithms (MLAs) to the problem, using data from auxiliary channels within the LIGO detectors that monitor degrees of freedom unaffected by astrophysical signals. The number of auxiliary-channel parameters describing these disturbances may also be extremely large; an area where MLAs are particularly well-suited. We demonstrate the feasibility and applicability of three very different MLAs: Artificial Neural Networks, Support Vector Machines, and Random Forests. These classifiers identify and remove a substantial fraction of the glitches present in two very different data sets: four weeks of LIGO's fourth science run and one week of LIGO's sixth science run. We observe that all three algorithms agree on which events are glitches to within 10% for the sixth science run data, and support this by showing that the different optimization criteria used by each classifier generate the same decision surface, based on a likelihood-ratio statistic. Furthermore, we find that all classifiers obtain similar limiting performance, suggesting that most of the useful information currently contained in the auxiliary channel parameters we extract is already being used.

astro-ph.IM↗

arXiv2012

Electric-triple-layer model based AC electroosmosis flow

The paper presents an novel electric triple layer(ETL) model as an improved model of electrical double layer(EDL) to predict electroosmosis flow rate on the electrode surface at low frequency. The predicted slip velocity based on classical EDL theory is much higher than experimental results, and ETL model can account for this deviation. Cross-over frequency at which the maximum electroosmosis flow velocity occurs based on ETL model is a little bit higher than that predicted in EDL theory, but still in keeping with classical prediction. Influences of triple layer thickness and electrode surface roughness on electroosmosis flow are analyzed via simulation and theoretical analysis agrees with experimental data very well, proving its validity.

physics.class-ph↗

arXiv2011

Corner Occupying Theorem for the Two-dimensional Integral Rectangle Packing Problem

This paper proves a corner occupying theorem for the two-dimensional integral rectangle packing problem, stating that if it is possible to orthogonally place n arbitrarily given integral rectangles into an integral rectangular container without overlapping, then we can achieve a feasible packing by successively placing an integral rectangle onto a bottom-left corner in the container. Based on this theorem, we might develop efficient heuristic algorithms for solving the integral rectangle packing problem. In fact, as a vague conjecture, this theorem has been implicitly mentioned with different appearances by many people for a long time.

cs.DM↗

arXiv2011

Bottom-Left Placement Theorem for Rectangle Packing

This paper proves a bottom-left placement theorem for the rectangle packing problem, stating that if it is possible to orthogonally place n arbitrarily given rectangles into a rectangular container without overlapping, then we can achieve a feasible packing by successively placing a rectangle onto a bottom-left corner in the container. This theorem shows that even for the real-parameter rectangle packing problem, we can solve it after finite times of bottom-left placement actions. Based on this theorem, we might develop efficient heuristic algorithms for solving the rectangle packing problem.

cs.DM↗