Grid Jigsaw Representation with CLIP: A New Perspective on Image Clustering

Unsupervised representation learning for image clustering is essential in computer vision. Although the advancement of visual models has improved image clustering with efficient visual representations, challenges still remain. Firstly, these features often lack the ability to represent the internal structure of images, hindering the accurate clustering of visually similar images. Secondly, the existing features tend to lack finer-grained semantic labels, limiting the ability to capture nuanced differences and similarities between images. In this paper, we first introduce Jigsaw based strategy method for image clustering called Grid Jigsaw Representation (GJR) with systematic exposition from pixel to feature in discrepancy against human and computer. We emphasize that this algorithm, which mimics human jigsaw puzzle, can effectively improve the model to distinguish the spatial feature between different samples and enhance the clustering ability. GJR modules are appended to a variety of deep convolutional networks and tested with significant improvements on a wide range of benchmark datasets including CIFAR-10, CIFAR-100/20, STL-10, ImageNet-10 and ImageNetDog-15. On the other hand, convergence efficiency is always an important challenge for unsupervised image clustering. Recently, pretrained representation learning has made great progress and released models can extract mature visual representations. It is obvious that use the pretrained model as feature extractor can speed up the convergence of clustering where our aim is to provide new perspective in image clustering with reasonable resource application and provide new baseline. Further, we innovate pretrain-based Grid Jigsaw Representation (pGJR) with improvement by GJR. The experiment results show the effectiveness on the clustering task with respect to the ACC, NMI and ARI three metrics and super fast convergence speed

Disproof of a conjecture on the minimum spectral radius and the domination number

Let $G_{n,\gamma}$ be the set of all connected graphs on $n$ vertices with domination number $\gamma$. A graph is called a minimizer graph if it attains the minimum spectral radius among $G_{n,\gamma}$. Very recently, Liu, Li and Xie [Linear Algebra and its Applications 673 (2023) 233--258] proved that the minimizer graph over all graphs in $\mathbb{G}_{n,\gamma}$ must be a tree. Moreover, they determined the minimizer graph among $G_{n,\lfloor\frac{n}{2}\rfloor}$ for even $n$, and posed the conjecture on the minimizer graph among $G_{n,\lfloor\frac{n}{2}\rfloor}$ for odd $n$. In this paper, we disprove the conjecture and completely determine the unique minimizer graph among $G_{n,\lfloor\frac{n}{2}\rfloor}$ for odd $n$

Chinese Language Teacher Competency: A Literature Review for a Study Series

This literature study reviews the definition and the most significant research studies of teacher competency. A chronological order, from the 20th to the 21st century, is followed to introduce the development of the teacher competency. The current status of the Chinese (as a foreign language) teacher competency research is also revealed, which shows a big gap that needs to be filled

Chinese Language Teacher Competency: A Literature Review for a Study Series

This literature study reviews the definition and the most significant research studies of teacher competency. A chronological order, from the 20th to the 21st century, is followed to introduce the development of the teacher competency. The current status of the Chinese (as a foreign language) teacher competency research is also revealed, which shows a big gap that needs to be filled

Anisotropic intrinsic lattice thermal conductivity of phosphorene from first principles

Phosphorene, the single layer counterpart of black phosphorus, is a novel two-dimensional semiconductor with high carrier mobility and a large fundamental direct band gap, which has attracted tremendous interest recently. Its potential applications in nano-electronics and thermoelectrics call for a fundamental study of the phonon transport. Here, we calculate the intrinsic lattice thermal conductivity of phosphorene by solving the phonon Boltzmann transport equation (BTE) based on first-principles calculations. The thermal conductivity of phosphorene at $300\,\mathrm{K}$ is $30.15\,\mathrm{Wm^{-1}K^{-1}}$ (zigzag) and $13.65\,\mathrm{Wm^{-1}K^{-1}}$ (armchair), showing an obvious anisotropy along different directions. The calculated thermal conductivity fits perfectly to the inverse relation with temperature when the temperature is higher than Debye temperature ($\Theta_D = 278.66\,\mathrm{K}$). In comparison to graphene, the minor contribution around $5\%$ of the ZA mode is responsible for the low thermal conductivity of phosphorene. In addition, the representative mean free path (MFP), a critical size for phonon transport, is also obtained.Comment: 5 pages and 6 figures, Supplemental Material available as http://www.rsc.org/suppdata/cp/c4/c4cp04858j/c4cp04858j1.pd

Dynamic Flow-Adaptive Spectrum Leasing with Channel Aggregation in Cognitive Radio Networks

Cognitive radio networks (CRNs), which allow secondary users (SUs) to dynamically access a network without affecting the primary users (PUs), have been widely regarded as an effective approach to mitigate the shortage of spectrum resources and the inefficiency of spectrum utilization. However, the SUs suffer from frequent spectrum handoffs and transmission limitations. In this paper, considering the quality of service (QoS) requirements of PUs and SUs, we propose a novel dynamic flow-adaptive spectrum leasing with channel aggregation. Specifically, we design an adaptive leasing algorithm, which adaptively adjusts the portion of leased channels based on the number of ongoing and buffered PU flows. Furthermore, in the leased spectrum band, the SU flows with access priority employ dynamic spectrum access of channel aggregation, which enables one flow to occupy multiple channels for transmission in a dynamically changing environment. For performance evaluation, the continuous time Markov chain (CTMC) is developed to model our proposed strategy and conduct theoretical analyses. Numerical results demonstrate that the proposed strategy effectively improves the spectrum utilization and network capacity, while significantly reducing the forced termination probability and blocking probability of SU flows.publishedVersio