Adaptive Inter-Organizational Workflow Management for E-Business Integration

As the collaboration between companies is facilitated in e-business environment, inter-organizational workflow management becomes an important issue. Because the inter-organizational workflow consists of autonomous organizational workflow, the coordination of these autonomous processes is required. In this paper, a local viewed inter-organizational workflow model is proposed, in which an inter-organizational workflow is defined as a set of block activities. Exception handling rules for internal process are defined with pertinent block activities. Based on the suggested model, a multi-agent system and a coordination algorithm are proposed. For the illustration of the suggested model, an example interorganizational workflow about book order process is presented

Deriving Technology Intelligence from Patents: Preposition-based Semantic Analysis

Patents are one of the most reliable sources of technology intelligence, and the true value of patent analysis stems from its capability of describing the content of technology based on the relationships between keywords. To date a number of techniques for analyzing the information contained in patent documents that focus on the relationships between keywords have been suggested. However, a drawback of the existing keyword approaches is that they cannot yet determine the types of relationships between the keywords. This study proposes a novel approach based on preposition semantic analysis network which overcomes the limitations of the existing keywords-based network analysis and demonstrates its potential through an application. A preposition is a word that defines the relationship between two neighboring words, and, in the case of patents, prepositions aid in revealing the relationships between keywords related to technologies. To demonstrate the approach, patents regarding an electric vehicle were employed. 13 prepositions were identified which could be used to define 5 relationships between neighboring technological terms: “inclusion (utilization),” “objective (purpose),” “effect,” “process,” and “likeness.” The proposed approach is expected to improve the usability of keyword-based patent analyses and support more elaborate studies on patent documents

MarioNETte: Few-shot Face Reenactment Preserving Identity of Unseen Targets

When there is a mismatch between the target identity and the driver identity, face reenactment suffers severe degradation in the quality of the result, especially in a few-shot setting. The identity preservation problem, where the model loses the detailed information of the target leading to a defective output, is the most common failure mode. The problem has several potential sources such as the identity of the driver leaking due to the identity mismatch, or dealing with unseen large poses. To overcome such problems, we introduce components that address the mentioned problem: image attention block, target feature alignment, and landmark transformer. Through attending and warping the relevant features, the proposed architecture, called MarioNETte, produces high-quality reenactments of unseen identities in a few-shot setting. In addition, the landmark transformer dramatically alleviates the identity preservation problem by isolating the expression geometry through landmark disentanglement. Comprehensive experiments are performed to verify that the proposed framework can generate highly realistic faces, outperforming all other baselines, even under a significant mismatch of facial characteristics between the target and the driver.Comment: In AAAI 202

MetaMix: Meta-state Precision Searcher for Mixed-precision Activation Quantization

Mixed-precision quantization of efficient networks often suffer from activation instability encountered in the exploration of bit selections. To address this problem, we propose a novel method called MetaMix which consists of bit selection and weight training phases. The bit selection phase iterates two steps, (1) the mixed-precision-aware weight update, and (2) the bit-search training with the fixed mixed-precision-aware weights, both of which combined reduce activation instability in mixed-precision quantization and contribute to fast and high-quality bit selection. The weight training phase exploits the weights and step sizes trained in the bit selection phase and fine-tunes them thereby offering fast training. Our experiments with efficient and hard-to-quantize networks, i.e., MobileNet v2 and v3, and ResNet-18 on ImageNet show that our proposed method pushes the boundary of mixed-precision quantization, in terms of accuracy vs. operations, by outperforming both mixed- and single-precision SOTA methods

Water-Soluble Epitaxial NaCl Thin Film for Fabrication of Flexible Devices

We studied growth mechanisms of water-soluble NaCl thin films on single crystal substrates. Epitaxial growth of NaCl(100) on Si(100) and domain-matched growth of NaCl(111) on c-sapphire were obtained at thicknesses below 100 nm even at room temperature from low lattice mismatches in both cases. NaCl thin film, which demonstrates high solubility selectivity for water, was successfully applied as a water-soluble sacrificial layer for fabrication of several functional materials, such as WO3 nano-helix and Sn doped In2O3 nano-branches.111Ysciescopu

What factors of early-stage innovative projects are likely to drive projects’ success? A longitudinal analysis of Korean entrepreneurial firms

Previous studies have identified the factors affecting successful technology commercialization as outcomes of R&D projects. However, most of them have used cross‐sectional data, whereas there is a dearth of literature using longitudinal data analysis. Longitudinal analysis is essential for investigating the characteristics of early‐stage innovative projects due to the inherent time lag between project evaluation and commercialization. Therefore, this study examines the early‐stage project characteristics that can be used as meaningful evaluation criteria for predicting success, particularly in technology commercialization. We collected data on the ex‐ante evaluation results and ex‐post commercialization results of R&D projects pursued by entrepreneurial firms. We then conducted a logistic regression analysis and identified three market‐related factors as significant in driving technology commercialization success in the early stages of technology development: market potential, commercialization plan, and market condition