arXiv subjects

Ying Zhong

Publications and source records attributed to Ying Zhong.

16 recordsLinked to original sources

arXiv2026

Asymptotics and inequalities for the broken $k$-diamond partition function

Many papers have studied inequalities for Andrews and Paule's broken $k$-diamond partition function $Δ_{k}(n)$ when $k=1$ or $2$. In this paper, we derive an exact formula for $Δ_{k}(n)$ when $k\geq 1$. Building on this result, we also derive an asymptotic formula for $Δ_{k}(n)$ with an explicit error bound. Using this formula, we prove that for $k\geq 1$ and sufficiently large $n$, $Δ_{k}(n)$ satisfies the Turán and Laguerre inequalities of any order and exhibits asymptotic complete monotonicity. Define $n_k:=\max\left\{\left\lceil8k^{3}+\frac{k+1}{12}\right\rceil,526\right\}$. Furthermore, we show that $Δ_{k}(n)$ is log-concave for $k\ge3$ and $n\ge n_k$. Consequently, it follows that $Δ_{k}(a)Δ_{k}(b)\geΔ_{k}(a+b)$ for $k\ge3$ and $a,b \ge n_k$.

math.CO↗

arXiv2026

Mechanism-Faithful Queueing Simulation Model Translation with Large Language Model Support

Queueing simulation studies often require substantial manual effort to translate conceptual system descriptions into executable programs and to verify that the implemented mechanisms match the intended queueing logic. Although large language models (LLMs) may produce executable scripts, executability alone is insufficient when arrival, routing, interruption, or reporting logic is wrong. This study presents a simulation-oriented support framework for \texttt{SimPy}-based queueing model translation. We propose a category-template framework for mechanism coverage with a staged adaptation workflow that targets structured event logic and common simulation-specific failure modes. On held-out task instances, the adapted models improve executability, output-format compliance, and instruction-mechanism consistency across basic, behavioral, and networked queueing settings, so the generated scripts are more reliable as queueing simulation scripts. Error analysis shows better preservation of routing semantics and interruption-resume logic, while also exposing remaining weaknesses in multi-node transfer and residual-service updates. Overall, the results suggest that the proposed framework can act as a simulation-faithful generator for more standardized and reproducible queueing model construction.

cs.CL↗

arXiv2025

Asymptotics and inequalities for the distinct partition function

In this paper, we give explicit error bounds for the asymptotic expansion of the shifted distinct partition function $q(n +s)$ for any nonnegative integer $s$. Then based on this refined asymptotic formula, we give the exact thresholds of $n$ for the inequalities derived from the invariants of the quartic binary form, the double Turán inequalities, the Laguerre inequalities and their corresponding companion versions.

math.CO↗

arXiv2023

Inequalities for the $k$-Regular Overpartitions

Bessenrodt and Ono, Chen, Wang and Jia, DeSalvo and Pak were the first to discover the log-subadditivity, log-concavity, and the third-order Turán inequality of partition function, respectively. Many other important partition statistics are proved to enjoy similar properties. This paper focuses on the partition function $\overline{p}_k(n)$, which counts the number of overpartitions of $n$ with no parts divisible by $k$. We provide a combinatorial proof to establish that for any $k\geq2$, the partition function $\overline{p}_k(n)$ exhibits strict log-subadditivity. Specifically, we show that $\overline{p}_k(a)\overline{p}_k(b)>\overline{p}_k(a+b)$ for integers $a\geq b\geq1$ and $a+b\geq k$. Furthermore, we investigate the log-concavity and the satisfaction of the third-order Turán inequality for $\overline{p}_k(n)$, where $2\leq k\leq9$.

math.NT↗

arXiv2023

Asymptotics for $k$-crank of $k$-colored partitions

In this paper, we obtain asymptotic formulas for $k$-crank of $k$-colored partitions. Let $M_k(a, c; n)$ denote the number of $k$-colored partitions of $n$ with a $k$-crank congruent to $a$ mod $c$. For the cases $k=2,3,4$, Fu and Tang derived several inequality relations for $M_k(a, c; n)$ using generating functions. We employ the Hardy-Ramanujan Circle Method to extend the results of Fu and Tang. Furthermore, additional inequality relations for $M_k(a, c; n)$ have been established, such as logarithmic concavity and logarithmic subadditivity.

math.CO↗

arXiv2022

Deep Temporal Contrastive Clustering

Recently the deep learning has shown its advantage in representation learning and clustering for time series data. Despite the considerable progress, the existing deep time series clustering approaches mostly seek to train the deep neural network by some instance reconstruction based or cluster distribution based objective, which, however, lack the ability to exploit the sample-wise (or augmentation-wise) contrastive information or even the higher-level (e.g., cluster-level) contrastiveness for learning discriminative and clustering-friendly representations. In light of this, this paper presents a deep temporal contrastive clustering (DTCC) approach, which for the first time, to our knowledge, incorporates the contrastive learning paradigm into the deep time series clustering research. Specifically, with two parallel views generated from the original time series and their augmentations, we utilize two identical auto-encoders to learn the corresponding representations, and in the meantime perform the cluster distribution learning by incorporating a k-means objective. Further, two levels of contrastive learning are simultaneously enforced to capture the instance-level and cluster-level contrastive information, respectively. With the reconstruction loss of the auto-encoder, the cluster distribution loss, and the two levels of contrastive losses jointly optimized, the network architecture is trained in a self-supervised manner and the clustering result can thereby be obtained. Experiments on a variety of time series datasets demonstrate the superiority of our DTCC approach over the state-of-the-art.

cs.LG↗

arXiv2022

Strict Log-Subadditivity for Overpartition Rank

Bessenrodt and Ono initially found the strict log-subadditivity of partition function $p(n)$, that is, $p(a+b)< p(a)p(b)$ for $a,b>1$ and $a+b>9$. Many other important statistics of partitions are proved to enjoy similar properties. Lovejoy introduced the overpartition rank as an analog of Dyson's rank for partitions from the $q$-series perspective. Let $\overline{N}(a,c,n)$ denote the number of overpartitions with rank congruent to $a$ modulo $c$. Ciolan computed the asymptotic formula of $\overline{N}(a,c,n)$ and showed that $\overline{N}(a, c, n) > \overline{N}(b, c, n)$ for $c\geq7$ and $n$ large enough. In this paper, we derive an upper bound and a lower bound of $\overline{N}(a,c,n)$ for each $c\geq3$ by using the asymptotics of Ciolan. Consequently, we establish the strict log-subadditivity of $\overline{N}(a,c,n)$ analogous to the partition function $p(n)$.

math.CO↗

arXiv2022

Asymptotic formula for the $M_2$-ranks of overpartitions

Let $\overline{N}_2(a,c,n)$ be the number of overpartitions of $n$ whose the $M_2$-rank is congruent to $a$ modulo $c$. In this paper, we obtain the asymptotic formula of $\overline{N}_2(a,c,n)$ utilizing the Ingham Tauberian Theorem. As applications, we derive inequalities concerning with $\overline{N}_2(a,c,n)$ including its strict concavity and log-concavity.

math.CO↗

arXiv2022

Higher order log-concavity of the overpartition function and its consequences

Let $\bar{p}(n)$ denote the overpartition function. In this paper, we study the asymptotic higher order $\log$-concavity property of the overpatition function in a similar framework done by Hou and Zhang for the partition function. This will enable us to move on further in order to prove $\log$-concavity of overpartitions, explicitly by studying the asymptotic expansion of the quotient $\bar{p}(n-1)\bar{p}(n+1)/\bar{p}(n)^2$ upto a certain order so that one can finally ends up with the phenomena of $2$-$\log$-concavity and higher order Turán property of $\bar{p}(n)$ by following a sort of unified approach.

math.NT↗

arXiv2021

DeepAID: Interpreting and Improving Deep Learning-based Anomaly Detection in Security Applications

Unsupervised Deep Learning (DL) techniques have been widely used in various security-related anomaly detection applications, owing to the great promise of being able to detect unforeseen threats and superior performance provided by Deep Neural Networks (DNN). However, the lack of interpretability creates key barriers to the adoption of DL models in practice. Unfortunately, existing interpretation approaches are proposed for supervised learning models and/or non-security domains, which are unadaptable for unsupervised DL models and fail to satisfy special requirements in security domains. In this paper, we propose DeepAID, a general framework aiming to (1) interpret DL-based anomaly detection systems in security domains, and (2) improve the practicality of these systems based on the interpretations. We first propose a novel interpretation method for unsupervised DNNs by formulating and solving well-designed optimization problems with special constraints for security domains. Then, we provide several applications based on our Interpreter as well as a model-based extension Distiller to improve security systems by solving domain-specific problems. We apply DeepAID over three types of security-related anomaly detection systems and extensively evaluate our Interpreter with representative prior works. Experimental results show that DeepAID can provide high-quality interpretations for unsupervised DL models while meeting the special requirements of security domains. We also provide several use cases to show that DeepAID can help security operators to understand model decisions, diagnose system mistakes, give feedback to models, and reduce false positives.

cs.CR↗

arXiv2021

Electrostatic Force Suspended-Air Multilayer (EPAM) Structure for Highly Transparent Energy Efficient Windows

The poor thermal insulating building windows, especially single pane windows, are wasting ~7% of the total energy consumed by the U.S. every year. This paper presents an electrostatic force suspended polymer-air multilayer (EPAM) structure as a highly transparent and energy efficient window retrofitting solution for low-income single pane window users. To provide controllable and stable suspension force between large size compliant polymer films without deteriorating their visual transmittance (Vt), corona discharge (CD) was induced to permanently charge polymer films, leading to controllable permanent surface potential difference between two sides of CD charged films. Liquid-solid contact electrification (CE) was combined with CD to realize precise control of the surface potential of each side of polymer films. CD+CE treated films can obtain programmable and stable electrostatic forces to form resilient EPAM structures for cost and energy effective window retrofitting purpose. The resilient EPAM retrofitted windows can provide U-factor lower than 0.5 Btu/hr/ft2/°F, Vt higher than 70%, haze lower than 1.6% at cost lower than $7.4/ft2, at least 10 times cheaper than double pane windows. The energy saved by EPAM can reach as much as the order of 106 kJ/m2 per year. The CD+CE surface potential programming solution also provides a highly repeatable and controllable way for other electrical potential related technologies.

physics.app-ph↗

arXiv2021

Evaluating and Improving Adversarial Robustness of Machine Learning-Based Network Intrusion Detectors

Machine learning (ML), especially deep learning (DL) techniques have been increasingly used in anomaly-based network intrusion detection systems (NIDS). However, ML/DL has shown to be extremely vulnerable to adversarial attacks, especially in such security-sensitive systems. Many adversarial attacks have been proposed to evaluate the robustness of ML-based NIDSs. Unfortunately, existing attacks mostly focused on feature-space and/or white-box attacks, which make impractical assumptions in real-world scenarios, leaving the study on practical gray/black-box attacks largely unexplored. To bridge this gap, we conduct the first systematic study of the gray/black-box traffic-space adversarial attacks to evaluate the robustness of ML-based NIDSs. Our work outperforms previous ones in the following aspects: (i) practical-the proposed attack can automatically mutate original traffic with extremely limited knowledge and affordable overhead while preserving its functionality; (ii) generic-the proposed attack is effective for evaluating the robustness of various NIDSs using diverse ML/DL models and non-payload-based features; (iii) explainable-we propose an explanation method for the fragile robustness of ML-based NIDSs. Based on this, we also propose a defense scheme against adversarial attacks to improve system robustness. We extensively evaluate the robustness of various NIDSs using diverse feature sets and ML/DL models. Experimental results show our attack is effective (e.g., >97% evasion rate in half cases for Kitsune, a state-of-the-art NIDS) with affordable execution cost and the proposed defense method can effectively mitigate such attacks (evasion rate is reduced by >50% in most cases).

cs.CR↗

arXiv2021

Corona-Enabled Electrostatic Printing for Ultra-Fast R2R Manufacturing of Binder-Free Multifunctional E-Skins

As essential components in intelligent systems, printed soft electronics (PSEs) are playing crucial roles in public health, national security, and economics. Innovations in printing technologies are required to promote the broad application of high-performance PSEs at a low cost. However, current printing techniques are still facing long-lasting challenges in addressing the conflict between printing speed and performance. To overcome this challenge, we developed a new corona-enabled electrostatic printing (CEP) technique for ultra-fast (milliseconds) roll-to-roll (R2R) manufacturing of binder-free multifunctional e-skins. The printing capability and controllability of CEP were investigated through parametric studies and microstructure observation. The electric field generation, material transfer, and particle amount and size selecting mechanisms were numerically and experimentally studied. CEP printed graphene e-skins were demonstrated to possess outstanding strain sensing performance. The binder-free feature of the CEP-assembled networks enables them to provide pressure sensitivity as low as 2.5 Pa, and capability to detect acoustic signals of hundreds of hertz in frequency. Furthermore, the CEP technique was utilized to pattern different types of functional materials (e.g., graphene and thermochromic polymers) onto different substrates (e.g., tape and textile). Overall, this study demonstrated that CEP can be a novel contactless and ultrafast manufacturing platform compatible with R2R process for fabricating high-performance, scalable, and low-cost soft electronics.

physics.app-ph↗

arXiv2020

A System for Worldwide COVID-19 Information Aggregation

The global pandemic of COVID-19 has made the public pay close attention to related news, covering various domains, such as sanitation, treatment, and effects on education. Meanwhile, the COVID-19 condition is very different among the countries (e.g., policies and development of the epidemic), and thus citizens would be interested in news in foreign countries. We build a system for worldwide COVID-19 information aggregation containing reliable articles from 10 regions in 7 languages sorted by topics. Our reliable COVID-19 related website dataset collected through crowdsourcing ensures the quality of the articles. A neural machine translation module translates articles in other languages into Japanese and English. A BERT-based topic-classifier trained on our article-topic pair dataset helps users find their interested information efficiently by putting articles into different categories.

cs.CL↗

arXiv2020

Flow electrification of corona-charged polyethylene terephthalate film

Corona charging a free-standing polymer film can produce a quasi-permanent potential difference across the film thickness, while the absolute amplitude of surface voltage may be highly sensitive to the free charges. To precisely control the voltage distribution, we investigated the flow electrification technology, by exposing corona-charged polyethylene terephthalate films to a variety of sodium salt solutions. The surface voltage and the free charge density were adjusted by the salt concentration, the anion size, and the flow rate. The dipolar component of electric potential remained unchanged. This result has significant scientific interest and technological importance to surface treatment, filtration, energy harvesting, bio-actuation and bio-sensing, among others.

physics.app-ph↗

arXiv2020

Thermal Insulating Polymer-Air Multilayer for Window Energy Efficiency

Polymer-air multilayer (PAM) was developed to decrease the heat loss through window glass panes. A PAM consists of a few polymer films separated from each other by air gaps. Thanks to the excellent optical properties of the polymer films, the visual transmittance of PAM is higher than 70%, and the haze is less than 2%. PAM not only has mechanisms to reduce the conductive and convective heat transfer, but also can obstruct the radiative heat transfer. With a 4~6 mm thick PAM coating, the U-factor of a glass pane can be lowered from above 1 Btu/{{h}{ft}^2{°F}} to 0.5~0.6 Btu/{{h}{ft}^2{°F}} .PAM is resilient and robust, relevant to the window retrofitting applications.

physics.app-ph↗