A Proximity-Aware Hierarchical Clustering of Faces

In this paper, we propose an unsupervised face clustering algorithm called "Proximity-Aware Hierarchical Clustering" (PAHC) that exploits the local structure of deep representations. In the proposed method, a similarity measure between deep features is computed by evaluating linear SVM margins. SVMs are trained using nearest neighbors of sample data, and thus do not require any external training data. Clusters are then formed by thresholding the similarity scores. We evaluate the clustering performance using three challenging unconstrained face datasets, including Celebrity in Frontal-Profile (CFP), IARPA JANUS Benchmark A (IJB-A), and JANUS Challenge Set 3 (JANUS CS3) datasets. Experimental results demonstrate that the proposed approach can achieve significant improvements over state-of-the-art methods. Moreover, we also show that the proposed clustering algorithm can be applied to curate a set of large-scale and noisy training dataset while maintaining sufficient amount of images and their variations due to nuisance factors. The face verification performance on JANUS CS3 improves significantly by finetuning a DCNN model with the curated MS-Celeb-1M dataset which contains over three million face images

Designing and conducting an open-ended experiment as an organic chemistry laboratory practical

An open-ended laboratory practical has been developed that challenges students to evaluate the synthesis of aspirin, which is a typical experiment of organic synthesis. In contrast to a traditional textbook laboratory practical, the overall grade includes an evaluation of the experimental preparation, process, report, and PowerPoint presentation of the student. This practical improves undergraduate students’ ability to think innovatively and the skills pertaining for team cooperation, which would exhibit importance in the organic chemistry teaching experiment’s course

Plausibility of ultraviolet burst generation in the low solar chromosphere

Ultraviolet (UV) bursts and Ellerman bombs (EBs) are small-scale magnetic reconnection events taking place in the highly stratified, low solar atmosphere. It is still not clear whether UV bursts have to be generated at a higher atmospheric layer than EBs or whether both UV bursts and EBs can occur in the low chromosphere. We numerically studied the low $\beta$ magnetic reconnection process around the solar temperature minimum region (TMR). The time-dependent ionization degrees of hydrogen and helium are included in the MHD code, which lead to a more realistic magnetic diffusion caused by electron-neutral collision and ambipolar diffusion. A more realistic radiative cooling model from Carlsson & Leenaarts 2012 is included in the simulations. Our results in high resolution indicate that the plasmas in the reconnection region are heated up to more than $20,000$ K if the reconnecting magnetic field is as strong as $500$ G, which suggests that UV bursts can be generated in the dense low chromosphere. The dominant mechanism for producing the UV burst in the low chromosphere is heating, as a result of the local compression in the reconnection process. The thermal energy occurring in the reconnection region rapidly increases after the turbulent reconnection mediated by plasmoids is invoked. The average power density of the generated thermal energy in the reconnection region can reach over $1000$ erg cm$^{-3}$ s$^{-1}$, which is comparable to the average power density accounting for a UV burst. With the strength of the reconnecting magnetic field exceeding $900$ G, the width of the synthesized Si IV 1394 A line profile with multiple peaks can reach up to $100$ km s$^{-1}$, which is consistent with observations.Comment: 12 pages, 10 figure

Information Filtering on Coupled Social Networks

In this paper, based on the coupled social networks (CSN), we propose a hybrid algorithm to nonlinearly integrate both social and behavior information of online users. Filtering algorithm based on the coupled social networks, which considers the effects of both social influence and personalized preference. Experimental results on two real datasets, \emph{Epinions} and \emph{Friendfeed}, show that hybrid pattern can not only provide more accurate recommendations, but also can enlarge the recommendation coverage while adopting global metric. Further empirical analyses demonstrate that the mutual reinforcement and rich-club phenomenon can also be found in coupled social networks where the identical individuals occupy the core position of the online system. This work may shed some light on the in-depth understanding structure and function of coupled social networks

A magnetic reconnection model for the hot explosion with both ultraviolet and H{\alpha} wing emissions

Ellerman bombs (EBs) with significant H$\alpha$ wing emissions and ultraviolet bursts (UV bursts) with strong Si IV emissions are two kinds of small transient brightening events that occur in the low solar atmosphere.We numerically investigated the magnetic reconnection process between the emerging arch magnetic field and the lower atmospheric background magnetic field. We aim to find out if the hot UV emissions and much colder H$\alpha$ wing emissions can both appear in the same reconnection process and how they are located in the reconnection region. The open-source code NIRVANA was applied to perform the 2.5D magnetohydrodynamic (MHD) simulation. We developed the related sub-codes to include the more realistic radiative cooling process for the photosphere and chromosphere and the time-dependent ionization degree of hydrogen. The initial background magnetic field is 600 G, and the emerged magnetic field in the solar atmosphere is of the same magnitude, meaning that it results in a low- $\beta$ magnetic reconnection environment. We also used the radiative transfer code RH1.5D to synthesize the Si IV and H$\alpha$ spectral line profiles based on the MHD simulation results. Magnetic reconnection between emerged and background magnetic fields creates a thin, curved current sheet, which then leads to the formation of plasmoid instability and the nonuniform density distributions. The mix of hot tenuous and much cooler dense plasmas in the turbulent reconnection region can appear at about the same height, or even in the same plasmoid. The turbulent current sheet is always in a dense plasma environment with an optical depth larger than 6.5$\times$10$^{-5}$ due to the emerged magnetic field pushing high-density plasmas upward

Video ControlNet: Towards Temporally Consistent Synthetic-to-Real Video Translation Using Conditional Image Diffusion Models

In this study, we present an efficient and effective approach for achieving temporally consistent synthetic-to-real video translation in videos of varying lengths. Our method leverages off-the-shelf conditional image diffusion models, allowing us to perform multiple synthetic-to-real image generations in parallel. By utilizing the available optical flow information from the synthetic videos, our approach seamlessly enforces temporal consistency among corresponding pixels across frames. This is achieved through joint noise optimization, effectively minimizing spatial and temporal discrepancies. To the best of our knowledge, our proposed method is the first to accomplish diverse and temporally consistent synthetic-to-real video translation using conditional image diffusion models. Furthermore, our approach does not require any training or fine-tuning of the diffusion models. Extensive experiments conducted on various benchmarks for synthetic-to-real video translation demonstrate the effectiveness of our approach, both quantitatively and qualitatively. Finally, we show that our method outperforms other baseline methods in terms of both temporal consistency and visual quality

INTUITIVE DECISION THEORY ANALYSIS AND THE EVALUATION MODEL

Intuitive decision-making studies the decision-maker’s decision-making behavior from the perspective of image thinking, which it poses a challenge to the classic decision-making hypothesis pursuing “optimal decision” because the outcomes of intuitive decision-making are difficulty to measure and its process isn’t easy to describe and control. Therefore it has not drawn the experts’ attention. This paper tries to establish an evaluation model of the intuitive decision-making as to giving a direction and inspiration of the quantization of intuitive decision-making, based on the systematic analysis of the existing domestic and international theory of intuitive decision-making. Key words: Intuitive decision-making, Thinking in images, The evaluation mode