基于 Activiti 流程管理关键技术设计与实现

Activiti 是用于管理业务流程的工作流引擎,它的使用降低了复杂业务流程开发与维护的难度。但在实际应用中,流程节点无法自由跳转,给管理和使用带来诸多不便。本文研究了 Activiti 中的系统框架和接口,基于现有接口设计实现了流程节点自由跳转功能,并进行了框架整合。测试结果表明,该功能满足各项既定功能需求,具有一般性,可满足实际工作中相关要求。     

Collapse-free thermal bonding technique for large area microchambers in plastic lab-on-a-chip applications

Bonding is an essential step to form microchannels or microchambers in lab-on-a-chip applications. In this paper, we present a novel plastic thermal bonding technique to seal and form large area microchambers (planar characteristic width and length on the order of 1 mm and characteristic thickness on the order of 10–100 μm) without collapse by introducing a holed pressure equalizing plate (HPEP) that includes holes of the same size and shape as the microchambers. To demonstrate the proposed technique, two types of large area microchambers [(1) 20 × 10 mm and 40 μm thick and (2) 12 × 2.5 mm and 120 μm thick] with microchannels were designed and replicated on plastic substrates by means of hot embossing and injection molding processes with prepared two nickel mold inserts. The replicated large area microchambers as well as the microchannels in the plastic lab-on-a-chip were successfully sealed (i.e., no leakage) and formed without any collapse by the proposed thermal bonding technique with the help of the HPEP.     

Siamese transformer network-based similarity metric learning for cross-source remote sensing image retrieval

Neural Computing and Applications - As a fundamental technique for mining and analysis of remote sensing (RS) big data, content-based remote sensing image retrieval (CBRSIR) has received a lot of...     

Designing Metallic and Insulating Nanocrystal Heterostructures to Fabricate Highly Sensitive and Solution Processed Strain Gauges for Wearable Sensors

All‐solution processed, high‐performance wearable strain sensors are demonstrated using heterostructure nanocrystal (NC) solids. By incorporating insulating artificial atoms of CdSe quantum dot NCs into metallic artificial atoms of Au NC thin film matrix, metal–insulator heterostructures are designed. This hybrid structure results in a shift close to the percolation threshold, modifying the charge transport mechanism and enhancing sensitivity in accordance with the site percolation theory. The number of electrical pathways is also manipulated by creating nanocracks to further increase its sensitivity, inspired from the bond percolation theory. The combination of the two strategies achieves gauge factor up to 5045, the highest sensitivity recorded among NC‐based strain gauges. These strain sensors show high reliability, durability, frequency stability, and negligible hysteresis. The fundamental charge transport behavior of these NC solids is investigated and the combined site and bond percolation theory is developed to illuminate the origin of their enhanced sensitivity. Finally, all NC‐based and solution‐processed strain gauge sensor arrays are fabricated, which effectively measure the motion of each finger joint, the pulse of heart rate, and the movement of vocal cords of human. This work provides a pathway for designing low‐cost and high‐performance electronic skin or wearable devices.     

Synthesis and characterization of novel blue azo‐dye derivatives containing acrylate group for dye‐based color filters

Abstract— Even though dyes have a fine resolution and good chromaticities, they are not widely used as coloring materials for color filters (CFs) due to their low thermal stability and chemical resistance. A series of azo‐dye derivatives, which consist of two cross‐linkable acrylate or methacrylate groups to improve thermal and chemical properties, have been synthesized and used to fabricate color filters. The spectral properties and chemical/thermal stabilities of the fabricated CFs were investigated by comparing dye‐based CFs, without a complicated dispersion process, but with pigment‐based CFs using dispersed pigment. Also, more properties including the development test and surface morphologies lithographic properties were studied. The synthesized azo dyes were characterized by elemental analysis, UV‐visible spectra, IR, mass, and ¹H‐NMR spectra.     

A hybrid data-fusion system using modal data and probabilistic neural network for damage detection

This paper addresses a novel hybrid data-fusion system for damage detection by integrating the data fusion technique, probabilistic neural network (PNN) models and measured modal data. The hybrid system proposed consists of three models, i.e. a feature-level fusion model, a decision-level fusion model and a single PNN classifier model without data fusion. Underlying this system is the idea that we can choose any of these models for damage detection under different circumstances, i.e. the feature-level model is preferable to other models when enormous data are made available through multi-sensors, whereas the confidence level for each of multi-sensors must be determined (as a prerequisite) before the adoption of the decision-level model, and lastly, the single model is applicable only when data collected is somehow limited as in the cases when few sensors have been installed or are known to be functioning properly. The hybrid system is suitable for damage detection and identification of a complex structure, especially when a huge volume of measured data, often with uncertainties, are involved, such as the data available from a large-scale structural health monitoring system. The numerical simulations conducted by applying the proposed system to detect both single- and multi-damage patterns of a 7-storey steel frame show that the hybrid data-fusion system cannot only reliably identify damage with different noise levels, but also have excellent anti-noise capability and robustness.     

Ontology-based mobile augmented reality in cultural heritage sites: information modeling and user study

Augmented reality (AR) has received much attention in the cultural heritage domain as an interactive medium for requesting and accessing information regarding heritage sites. In this study, we developed a mobile AR system based on Semantic Web technology to provide contextual information about cultural heritage sites. Most location-based AR systems are designed to present simple information about a point of interest (POI), but the proposed system offers information related to various aspects of cultural heritage, both tangible and intangible, linked to the POI. This is achieved via an information modeling framework where a cultural heritage ontology is used to aggregate heterogeneous data and semantically connect them with each other. We extracted cultural heritage data from five web databases and modeled contextual information for a target heritage site (Injeongjeon Hall and its vicinity in Changdeokgung Palace in South Korea) using the selected ontology. We then implemented a mobile AR application and conducted a user study to assess the learning and engagement impacts of the proposed system. We found that the application provides an agreeable user experience in terms of its affective, cognitive, and operative features. The results of our analysis showed that specific usage patterns were significant with regard to learning outcomes. Finally, we explored how the study’s key findings can provide practical design guidance for system designers to enhance mobile AR information systems for heritage sites, and to show system designers how to support particular usage patterns in order to accommodate specific user experiences better.