An empirical learning-based validation procedure for simulation workflow

Simulation workflow is a top-level model for the design and control of simulation process. It connects multiple simulation components with time and interaction restrictions to form a complete simulation system. Before the construction and evaluation of the component models, the validation of upper-layer simulation workflow is of the most importance in a simulation system. However, the methods especially for validating simulation workflow is very limit. Many of the existing validation techniques are domain-dependent with cumbersome questionnaire design and expert scoring. Therefore, this paper present an empirical learning-based validation procedure to implement a semi-automated evaluation for simulation workflow. First, representative features of general simulation workflow and their relations with validation indices are proposed. The calculation process of workflow credibility based on Analytic Hierarchy Process (AHP) is then introduced. In order to make full use of the historical data and implement more efficient validation, four learning algorithms, including back propagation neural network (BPNN), extreme learning machine (ELM), evolving new-neuron (eNFN) and fast incremental gaussian mixture model (FIGMN), are introduced for constructing the empirical relation between the workflow credibility and its features. A case study on a landing-process simulation workflow is established to test the feasibility of the proposed procedure. The experimental results also provide some useful overview of the state-of-the-art learning algorithms on the credibility evaluation of simulation models

Double-Layer No-Flow Underfill Process for Flip-Chip Applications

©2003 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or distribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE. This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. In most cases, these works may not be reposted without the explicit permission of the copyright holder.No-flow underfill technology shows potential advances over the conventional underfill technology toward a low-cost flop-chip underfill process. However, due to the filler entrapment in between solder bumps and contact pads on board, no-flow underfills are mostly unfilled or filled with very low filler loading. The high coefficient of thermal expansion (CTE) of the polymer material has significantly lowered the reliability of flip chip assembly and has limited its application to large chip assemblies. This paper presents a double-layer no-flow underfill process approach to incorporate silica filler into a no-flow underfill. Two layers of underfills are applied on to the substrate before chip placement. The bottom underfill layer facing the substrate is fluxed and unfilled; the upper layer facing the chip is filled with silica fillers. The total filler loading of the mixture is estimated to be around 55 wt%. The material properties of each layer of underfills, the underfill mixture, and a control unfilled underfill are characterized using differential scanning calorimeter (DCS), thermo-mechanical analyzer (TMA), dynamic mechanical analyzer (DMA), and a stress rheometer. FB250 daisy-chained test chips are assembled on FR-4 boards using the novel approach. A 100% assembly yield of solder Interconnect is achieved with the double-layer no-flow underfill while in the single-layer no-flow underfill process, no solder joint yield is observed. Scanning electronic microscope (SEM) and optical microscope are used to investigate the cross-section of both assemblies. A US provisional patent has been filed for this invention

Liaison amid disorder: non-native interactions may underpin long-range coupling in proteins

A lattice-model study of double-mutant cycles published in BMC Structural Biology underscores how interactions in non-native conformations can lead to thermodynamic coupling between distant residues in globular proteins, adding to recent advances in delineating the often crucial roles played by disordered conformational ensembles in protein behavior

Big Data-driven Technology Innovation: Concept and Key Problems

In the background of big data, technological innovation has met some new opportunities and challenges. Based on expounding the concept and key technologies of big data, the concept, main data resources and characteristics of data driven technological innovation are analyzed. And some key problems of data driven technological innovation are discussed from technological and management perspective. From technological perspective, the key processes of data-driven technological innovation such as data acquisition, data processing, technology opportunity discovery and identification technology etc. are discussed and a technological framework is proposed based on Hadoop ecosystem. From management view, the idea of using big data to carry on operation and decision, matched decision-making culture and appropriate process, overall planning of large data applications and the stage of the target are analyzed as the main factors to affect the data-driven mode realization. This study has good values to the enterprises to build data driven innovative mode

SAGDA: Achieving O(ϵ−2)\mathcal{O}(\epsilon^{-2}) Communication Complexity in Federated Min-Max Learning

To lower the communication complexity of federated min-max learning, a natural approach is to utilize the idea of infrequent communications (through multiple local updates) same as in conventional federated learning. However, due to the more complicated inter-outer problem structure in federated min-max learning, theoretical understandings of communication complexity for federated min-max learning with infrequent communications remain very limited in the literature. This is particularly true for settings with non-i.i.d. datasets and partial client participation. To address this challenge, in this paper, we propose a new algorithmic framework called stochastic sampling averaging gradient descent ascent (SAGDA), which i) assembles stochastic gradient estimators from randomly sampled clients as control variates and ii) leverages two learning rates on both server and client sides. We show that SAGDA achieves a linear speedup in terms of both the number of clients and local update steps, which yields an $\mathcal{O}(\epsilon^{-2})$ communication complexity that is orders of magnitude lower than the state of the art. Interestingly, by noting that the standard federated stochastic gradient descent ascent (FSGDA) is in fact a control-variate-free special version of SAGDA, we immediately arrive at an $\mathcal{O}(\epsilon^{-2})$ communication complexity result for FSGDA. Therefore, through the lens of SAGDA, we also advance the current understanding on communication complexity of the standard FSGDA method for federated min-max learning.Comment: Published as a conference paper at NeurIPS 202

Localization of BEN1-LIKE protein and nuclear degradation during development of metaphloem sieve elements in Triticum aestivum L.

Metaphloem sieve elements (MSEs) in the developing caryopsis of Triticum aestivum L. undergo a unique type of programmed cell death (PCD); cell organelles gradually degrade with the MSE differentiation while mature sieve elements keep active. This study focuses on locating BEN1-LIKE protein and nuclear degradation in differentiating MSEs of wheat. Transmission electron microscopy (TEM) showed that nuclei degraded in MSE development. First, the degradation started at 2–3 days after flowering (DAF). The degraded fragments were then swallowed by phagocytic vacuoles at 4 DAF. Finally, nuclei almost completely degraded at 5 DAF. We measured the BEN1-LIKE protein expression in differentiating MSEs. In situ hybridization showed that BEN1-LIKE mRNA was a more obvious hybridization signal at 3–4 DAF at the microscopic level. Immuno-electron microscopy further revealed that BEN1-LIKE protein was mainly localized in MSE nuclei. Furthermore, MSE differentiation was tested using a TSQ Zn2+ fluorescence probe which showed that the dynamic change of Zn2+ accumulation was similar to BEN1-LIKE protein expression. These results suggest that nucleus degradation in wheat MSEs is associated with BEN1-LIKE protein and that the expression of this protein may be regulated by Zn2+ accumulation variation

Within-season decline in the call consistency of individual male Common Cuckoo (Cuculus canorus)

Numerous studies have identified individually distinctive vocal characteristics and call consistency in different bird species. If these are to be utilised as non-invasive markers for monitoring purposes, then these vocal characteristics must remain stable over time. Three recent studies have shown that it is possible to identify individual male Common Cuckoo (Cuculus canorus) based on vocal characteristics but whether these are stable over the duration of a breeding season, remains unknown. We recorded 1032 syllables from 30 male Common Cuckoos in a Northeast Asian population. We colour-banded six of these males and made repeated recordings of their cu-coo advertisement call across a 19-day period of the breeding season in China. We used three methods to identify individuals: discriminant function analyses (DFA), correlation analysis (CA) and spectrographic cross-correlation (SPCC). We also used repeatability analysis to test whether call consistency (the number of syllables in each calling bout) was repeatable within individuals. Based on the same day recordings, calls from the same male were more similar in their characteristics than those of different males, and yielded correct rates of classifying individuals of 93.6% (SPCC), 90.8 % (DFA), and 71.5% (CA). However, these rates declined to 40.5% (SPCC), 40.7% (DFA) and 27% (CA) when using recordings over the 19-day period. Call consistency was repeatable within individuals across two successive calling bouts, but this individual repeatability disappeared when several (more than two) calling bouts from the same day or bouts from the different days were included in the analyses. Declines in the correct rate of identifying individual male cuckoos and call consistency in this study raises concerns that individual male cuckoo calls may be more variable than previously thought