Practical cross-sensor color constancy using a dual-mapping strategy

Deep Neural Networks (DNNs) have been widely used for illumination estimation, which is time-consuming and requires sensor-specific data collection. Our proposed method uses a dual-mapping strategy and only requires a simple white point from a test sensor under a D65 condition. This allows us to derive a mapping matrix, enabling the reconstructions of image data and illuminants. In the second mapping phase, we transform the re-constructed image data into sparse features, which are then optimized with a lightweight multi-layer perceptron (MLP) model using the re-constructed illuminants as ground truths. This approach effectively reduces sensor discrepancies and delivers performance on par with leading cross-sensor methods. It only requires a small amount of memory (~0.003 MB), and takes ~1 hour training on an RTX3070Ti GPU. More importantly, the method can be implemented very fast, with ~0.3 ms and ~1 ms on a GPU or CPU respectively, and is not sensitive to the input image resolution. Therefore, it offers a practical solution to the great challenges of data recollection that is faced by the industry

Research progress on intelligent optimization techniques for energy-efficient design of ship hull forms

The design optimization of ship hull form based on hydrodynamics theory and simulation-based design (SBD) technologies generally considers ship performance and energy efficiency performance as the design objective, which plays an important role in smart design and manufacturing of green ship. An optimal design of sustainable energy system requires multidisciplinary tools to build ships with the least resistance and energy consumption. Through a systematic approach, this paper presents the research progress of energy-efficient design of ship hull forms based on intelligent optimization techniques. We discuss different methods involved in the optimization procedure, especially the latest developments of intelligent optimization algorithms and surrogate models. Moreover, current development trends and technical challenges of multidisciplinary design optimization and surrogate-assisted evolutionary algorithms for ship design are further analyzed. We explore the gaps and potential future directions, so as to paving the way towards the design of the next generation of more energy-efficient ship hull form.Comment: 30 pages, 8 figure

Optimization of connection architectures and mass distributions for metamaterials with multiple resonators

Metamaterials with multiple resonators have been widely investigated for the purpose of generating multiple stop bands or broadening the attenuation bandwidth. The multiple resonators could be connected end to end in a line, namely, in-series connection, or connected individually to the host structures, namely, in-parallel connection. This paper investigates the influence of the resonator connection methodology on the frequency response functions of metamaterial beams with multiple resonators and exhibits an approach for optimizing their resonator distribution over the structure. The receptance functions of metamaterial beams with various resonator connection architectures are calculated by a transfer matrix model, which is verified through finite element model results. It is demonstrated that resonator interconnection architectures have a great impact on the global dynamic properties of metamaterials. An optimization strategy is subsequently proposed to find out the optimal resonator connection architectures and mass distributions that could minimize the maximal receptance functions in targeted single and multiple frequency ranges. The objective functions within single targeted frequency ranges are solved by the adoption of the genetic algorithm method. The weighted sum method is used to gain an optimal solution for multi-frequency range optimization. The metamaterial beams with optimal resonator connection methods and mass distributions demonstrate greatly enhanced vibration attenuation at frequencies of interest compared with other beams. The work is expected to provide the necessary theoretical basis and incentive for future researchers working on the design of metamaterials with extended, tuned, and optimized stop bands

Autoencoder-assisted latent representation learning for survival prediction and multi-view clustering on multi-omics cancer subtyping

Cancer subtyping (or cancer subtypes identification) based on multi-omics data has played an important role in advancing diagnosis, prognosis and treatment, which triggers the development of advanced multi-view clustering algorithms. However, the high-dimension and heterogeneity of multi-omics data make great effects on the performance of these methods. In this paper, we propose to learn the informative latent representation based on autoencoder (AE) to naturally capture nonlinear omic features in lower dimensions, which is helpful for identifying the similarity of patients. Moreover, to take advantage of survival information or clinical information, a multi-omic survival analysis approach is embedded when integrating the similarity graph of heterogeneous data at the multi-omics level. Then, the clustering method is performed on the integrated similarity to generate subtype groups. In the experimental part, the effectiveness of the proposed framework is confirmed by evaluating five different multi-omics datasets, taken from The Cancer Genome Atlas. The results show that AE-assisted multi-omics clustering method can identify clinically significant cancer subtypes

Structure design, kinematics analysis, and effect evaluation of a novel ankle rehabilitation robot

This paper presents a novel ankle rehabilitation (2-CRS+PU)&R hybrid mechanism, which can meet the size requirements of different adult lower limbs based on the three-movement model of the ankle. This model is related to three types of movement modes of the ankle movement, without axis offset, which can cover the ankle joint movements. The inverse and forward position/kinematics results analysis of the mechanism is established based on the closed-loop vector method and using the optimization of particle groups algorithm. Four groups of position solutions of the mechanism are obtained. The kinematics simulation is analyzed using ADAMS software. The variations of the velocity and acceleration of all limbs are stable, without any sudden changes, which can effectively ensure the safety and comfort of the ankle model end-user. The dexterity of the mechanism is analyzed based on the transport function, and the results indicate that the mechanism has an excellent transfer performance in yielding the structure parameters. Finally, the rehabilitation evaluation is conducted according to the three types of movement modes of the ankle joint. The results show that this ankle rehabilitation mechanism can provide a superior rehabilitation function

PSI-Stats: Private Set Intersection Protocols Supporting Secure Statistical Functions

Private Set Intersection (PSI) enables two parties, each holding a private set to securely compute their intersection without revealing other information. This paper considers settings of secure statistical computations over PSI, where both parties hold sets containing identifiers with one of the parties having an additional positive integer value associated with each of the identifiers in her set. The main objective is to securely compute some desired statistics of the associated values for which its corresponding identifiers occur in the intersection of the two sets. This is achieved without revealing the identifiers of the set intersection. In this paper, we present protocols which enable the secure computations of statistical functions over PSI, which we collectively termed PSI-Stats. Implementations of our constructions are also carried out based on simulated datasets as well as on actual datasets in the business use cases that we defined, in order to demonstrate practicality of our solution. PSI-Stats incurs 5x less monetary cost compared to the current state-of-the-art circuit-based PSI approach due to Pinkas et al. (EUROCRYPT\u2719). Our solution is more tailored towards business applications where monetary cost is the primary consideration

The multiplexed light storage of Orbital Angular Momentum based on atomic ensembles

The improvement of the multi-mode capability of quantum memory can further improve the utilization efficiency of the quantum memory and reduce the requirement of quantum communication for storage units. In this letter, we experimentally investigate the multi-mode light multiplexing storage of orbital angular momentum (OAM) mode based on rubidium vapor, and demultiplexing by a photonic OAM mode splitter which combines a Sagnac loop with two dove prisms. Our results show a mode extinction ratio higher than 80$\%$ at 1 $\mu$s of storage time. Meanwhile, two OAM modes have been multiplexing stored and demultiplexed in our experimental configuration. We believe the experimental scheme may provide a possibility for high channel capacity and multi-mode quantum multiplexed quantum storage based on atomic ensembles

Systems Pharmacology Dissection of Multi-Scale Mechanisms of Action of Huo-Xiang-Zheng-Qi Formula for the Treatment of Gastrointestinal Diseases

Multi-components Traditional Chinese Medicine (TCM) treats various complex diseases (multi-etiologies and multi-symptoms) via herbs interactions to exert curative efficacy with less adverse effects. However, the ancient Chinese compatibility theory of herbs formula still remains ambiguous. Presently, this combination principle is dissected through a systems pharmacology study on the mechanism of action of a representative TCM formula, Huo-xiang-zheng-qi (HXZQ) prescription, on the treatment of functional dyspepsia (FD), a chronic or recurrent clinical disorder of digestive system, as typical gastrointestinal (GI) diseases which burden human physical and mental health heavily and widely. In approach, a systems pharmacology platform which incorporates the pharmacokinetic and pharmaco-dynamics evaluation, target fishing and network pharmacological analyses is employed. As a result, 132 chemicals and 48 proteins are identified as active compounds and FD-related targets, and the mechanism of HXZQ formula for the treatment of GI diseases is based on its three function modules of anti-inflammation, immune protection and gastrointestinal motility regulation mainly through four, i.e., PIK-AKT, JAK-STAT, Toll-like as well as Calcium signaling pathways. In addition, HXZQ formula conforms to the ancient compatibility rule of “Jun-Chen-Zuo-Shi” due to the different, while cooperative roles that herbs possess, specifically, the direct FD curative effects of GHX (serving as Jun drug), the anti-bacterial efficacy and major accompanying symptoms-reliving bioactivities of ZS and BZ (as Chen), the detoxication and ADME regulation capacities of GC (as Shi), as well as the minor symptoms-treating efficacy of the rest 7 herbs (as Zuo). This work not only provides an insight of the therapeutic mechanism of TCMs on treating GI diseases from a multi-scale perspective, but also may offer an efficient way for drug discovery and development from herbal medicine as complementary drugs