A Proposed Theoretical Model of Discontinuous Usage of Voice-Activated Intelligent Personal Assistants (IPAs)

Based on the contradictory phenomenon of rapid development of Voice-Activated Intelligent Personal Assistants (Voice-Activated IPAs) and discontinuous usage of it, this paper investigates the antecedents of discontinuous usage of Voice-Activated IPAs. We first analyze the topic of Siri usage discussion from Zhihu\u27s Q&A website, and then propose a theoretical model which hypothesized that discontinuous usage of Voice-Activated IPAs are affected by perceived ambiguity, cognitive overload, privacy concern, social embarrassment and lack of integration. It is hypothesized that perceived ambiguity will exert nonlinear impacts on discontinuous usage. Meanwhile, perceived ambiguity is also affected by level of personification in a nonlinear way. Scale development and data collection would be conducted for the future work. It is expected that the results our research could provide theoretical and practical implications for the design of Voice-Activated IPAs

Quantitative Comparison of Tree Ensemble Learning Methods for Perfume Identification Using a Portable Electronic Nose

Perfume identification (PI) based on an electronic nose (EN) can be used for exposing counterfeit perfumes more time-efficiently and cost-effectively than using gas chromatography and mass spectrometry instruments. During the past five years, decision-tree-based ensemble learning methods, also called tree ensemble learning methods, have demonstrated excellent performance when solving multi-class classification problems. However, the performance of tree ensemble learning methods for the EN-based PI problem remains uncertain. In this paper, four well-known tree ensemble learning classification methods, random forest (RF), stagewise additive modeling using a multi-class exponential loss function (SAMME), gradient-boosting decision tree (GBDT), and extreme gradient boosting (XGBoost), were implemented for PI using our self-designed EN. For fair comparison, all the tested classification methods used as input the same feature data extracted using principal component analysis. Moreover, two benchmark methods, neural network and support vector machine, were also tested with the same experimental setup. The quantitative results of experiments undertaken demonstrated that the mean PI accuracy achieved by XGBoost was up to 97.5%, and that XGBoost outperformed other tested methods in terms of accuracy mean and variance based on our self-designed EN

The complete mitochondrial genome of Heteropriacanthus cruentatus and implication of phylogenetic status

The complete mitochondrial genome of Heteropriacanthus cruentatus has been obtained and annotated through Illumina next-generation sequencing. This mitogenome was found to be 16,506 bp in length, containing 13 protein-coding genes (PCGs), 22 transfer RNA genes (tRNA), and 2 ribosomal RNA genes (rRNA). This overall base composition of the complete mitogenome for this species included 27.52% A, 24.46% T, 16.99% G and 31.04% C. The phylogenetic analysis revealed that the H. cruentatus has the closest relationship with Pristigenys niphonia. This study provides an important resource for reviewing the phylogenetic relationships and taxonomic status of this species

Improved Dark Channel Defogging Algorithm for Defect Detection in Underwater Structures

Underwater structures are crucial for national economic and social development. However, because of their complex environment, they are susceptible to damage during service. This damage should be prevented to minimize casualties and economic loss. Therefore, this study investigates the problems of disease identification and area statistics of underwater structures. To this end, the Dark-Retinex (DR) algorithm that can enhance the image of underwater structure defects is proposed. The algorithm consists of a combination of a dark channel algorithm and the Retinex algorithm. This study analyzes the current research status of underwater image processing technology, designs the overall framework of the DR algorithm, and uses the underwater structure disease image to verify the algorithm. Comparing the effect of the image with only the dark channel defogging and DR algorithm processing, the DR algorithm is observed to achieve “defogging” processing of underwater structural disease images to achieve better enhancement effects. Moreover, for accurate disease area statistics, the binary morphology and optimal threshold segmentation theories are combined to perform disease edge screening and remove interference information. Finally, accurate statistics of the proportion of diseased pixels are achieved, as well as the quantitative detection of surface diseases of underwater structures. After actual operational verification, the improved image dehazing and parallel boundary screening algorithms can achieve better application results to detect underwater structure defects and disease statistics. The objective evaluation shows that the DR algorithm facilitates image processing, can obtain relatively high-quality target images, and can solve the problems of time-consuming and labor-intensive detection of underwater structures, with significant risks and limitations. This helps pave the way for (1) the actual engineering of surface structure detection of underwater structures, (2) future storage in the database and assessment of hazard levels, and (3) a guide for engineering technicians to take corresponding maintenance measures

Estimate of drag coefficient for a finite patch of rigid cylinders

This note presents laboratory measurements of the drag coefficient for a finite patch of vegetation that was simulated with a limited number of rigid cylindrical rods. The experiment was designed based on an analogy between the drag imposed by a vegetation patch in an open-channel flow and that experienced by the patch settling in a water tank. The results show that the average drag coefficient calculated from the measured settling velocity can be expressed as a function of the patch porosity. The experimental data are also consistent with previous predictions by large eddy simulations

Iridium(III)- and rhodium(III)- catalyzed coupling of anilines with alpha-diazoesters via chelation- assisted C-H activation

Iridium and rhodium complexes exhibited complementary activity in the coupling of N-functionalized anilines with alpha-diazoesters via C-H activation. The coupling with alpha-diazo beta-ketoesters was realized under Ir(III) catalysis to afford ester-functionalized indoles. In contrast, coupling with alpha-diazomalonates under Rh(III) catalysis afforded alkylation products without any annulation. Mechanistic studies have been performed and an iridacycle has been isolated as an intermediate

A Coordination of Risk Management for Supply Chains Organized as Virtual Enterprises

As a new management mode, great attention has been paid to virtual enterprise (VE). While there is much research material on risk management of VE, a relationship perspective on owner and partner performance assessment and management can bring an added dimension. The coordination of risk management in fashion and textiles (FTs) supply chain organized as a VE is studied in this paper. The aim of this study is to find proper decision mechanisms that can improve the overall performance of risk management for the whole VE as well as each member. For the risk management problem in VE, a centralized mechanism is given as the base case, and then a distributed decision-making (DDM) mechanism with incentive scheme is introduced to establish a practicable strategic partnership. Under the DDM mechanism, a relationship performance definition that incorporates the financial dimension is investigated. For the two resulting optimization problems, a particle swarm optimization (PSO) algorithm is designed. In the numerical examples, the study shows that the DDM mechanism with incentive scheme can improve the overall benefit of risk management beyond the centralized one. Additionally, sensitivity analysis is conducted with respect to the bonus parameter, and suggestions are made for further research

ANALYSIS AND TEST OF COMBINED FATIGUE LOADING SYSTEM OF CERTAIN ENGINE FAN BLADE

During the combined fatigue test of certain engine fan blade,the difficulty was how to combine low cycle fatigue and high cycle fatigue,and applied them to the assessment location of the blade. The modal analysis and test was carried to obtain the natural frequency of the blade and verify the accuracy of the model. By the static analysis and transient analysis of blade-wheel system,the critical part and the frequency of high cycle fatigue was acquired. Besides,the holder was designed and combined the blade into a system. Through the demonstration of simulation analysis and fracture analysis,high-low cycle combined loading was successfully applied to the assessment location of the blade. The results show that for the third-level fan blade,the regularity distributions of equivalent stress have a similarity under different revolving speed loads. The dangerous part of the blade is on the lug,and the max stress reached to 503 MPa. There are 2 risky resonance revolving speeds in the bladewheel system,which are n = 9 890. 92 r/min and n = 10 979. 8 r/min. The resonance frequencies are f = 1 318. 92 Hz and f =1 439. 65 Hz. There are typical characteristics of high-low cycle compound fatigue fracture on the cracked areas of the blade,such as fatigue line and fatigue striation