Experimental characterization of magnetic components has grown to be increasingly important understand and model their behaviours in high-frequency PWM converters. The BH loop measurement is the only available approach separate core loss as an electrical method, which, however, suspective probe phase skew. As alternative regular de-skew approaches based on hardware, this work proposes a novel machine-learning-based method identify correct skew, which builds newly discovered correlation...

Initial coin offerings (ICOs) have emerged as a popular method to raise capital by startups. During the ICO process, issuers release white papers, which serve primary offering documents. Unlike traditional corporate disclosures, disclosures are largely unregulated. We hypothesize that more-readable papers reflect less information obfuscation and cognitively costly for potential investors process understand, thus enabling attract more funding. Utilizing hand-collected global sample, we find...

Higher-order vortices (HOVs) extend the dimensions of optical vortex regulation, which is great significance in communication and tweezers. Herein, we demonstrate an alternative scheme to produce a HOV focus plane using multiple Laguerre-Gaussian (LG) beam interference, termed discrete higher-order lattice (DHOVL). The modulation depth DHOVL exceeds 2π. In this case, topological charge (TC) determined by difference phase period between innermost outermost interference beams. Compared with...

Although in-orbit anomaly detection is extremely important to ensure spacecraft safety, the complex spatial-temporal correlation and sparsity of anomalies in data pose significant challenges. This study proposes new multi-task learning-based time series (MTAD) method, which captures learn generalized normal patterns hence facilitates detection. First, four proxy tasks are implemented for feature extraction through joint learning: (1) Long short-term memory-based prediction; (2)...

Software rejuvenation has been addressed in hundreds of papers since it was proposed 1995 by Huang et al. The growing number research shows the great importance this topic. However, no paper studied yet software real world. This investigates to what extent techniques are integrated IT and Telco solutions. For purpose, conducted an intensive search different sources such as company's product websites, technical papers, white US patents, consultant surveys. results show that companies develop...

The development of Artificial Intelligence (AI) technology brings opportunities and challenges to the education system. It is changing way educational information disseminated at same time triggering a change in model. Based on database CNKI, this paper uses visualization tool CiteSpace software map knowledge structure AI system research conducts bibliometric analysis relevant literature collected field. results showed that 1) In past 20 years, emphasis studies China has shifted from...

This paper introduces our augmented reality platform, Aristo, which aims to provide users with physical feedback when interacting virtual objects. We use Vivepaper, a product we launched on Aristo in 2016, illustrate the platform's performance requirements and key algorithms. specifically depict Vivepaper's tracking gesture recognition algorithms, involve several trade-offs between speed accuracy achieve an immersive experience.

Nuclear masses of even-even nuclei with the proton number $8\leq Z\leq 50$ (O to Sn isotopes) from drip line neutron are investigated using triaxial relativistic Hartree-Bogoliubov (RHB) theory density functional PC-PK1, and dynamical correlation energies (DCEs) associated rotational motion quadrupole shape vibrational taken into account by five-dimensional collective Hamiltonian (5DCH) method. The root-mean-square deviation respect experimental reduces 2.50 MeV 1.59 after consideration...

Since absorption chillers are nonlinear and strongly coupled, it is difficult to build accurate mechanism models. Based on the experimental data, SVM method utilized identify model of refrigeration system, which only contains input output data. The correlation coefficient more than 0.99 mean square error less 0.1%. outlet temperature chilled water system controlled by model-free adaptive control for with time delay PID algorithm respectively suit variable load demand. Simulation experiments...

Although much research work for the operation safety has been taken in railway domain, some accidents still occur because past experiences of accident analysis were not fully accumulated improvement. This study aims to identify potential causal relationships among many factors playing a role accidents. A new interestingness measure, Confidence_interestingness ("C_" Inter) and corresponding improved algorithm, Positive Negative Association Rules Algorithm based on "C_" Inter (PNARA_CI) put...

The future emotion prediction of users on social media has been attracting increasing attention from academics. Previous studies predicting have focused the characteristics individuals’ changes; however, role individual’s neighbors not yet thoroughly researched. To fill this gap, a surrounding-aware individual model (SAEP) based deep encoder–decoder architecture is proposed to predict emotions. In particular, two memory-based networks are constructed: time-evolving network and surrounding...

This paper investigates the effects of auditor-client disagreement disclosure on auditor resignations and audit fee charged by successor auditors. Using a matched sample changes over period 2003-2016, we find that are more often accompanied disagreements. We also Big 4 auditors likely to resign from their engagements when they disagree with clients. Further, document charge higher fees for firms have disagreements predecessor Relative non-Big auditors, even firms.

Minimizing satellite failures and maintaining orbital health is crucial. Current systems spot certain anomalies, relying on expert insight. This paper suggests a data-driven anomaly detection framework, using Deviation Divide Mean over Neighbors (DDMN) to counter fake anomalies from data errors. Long Short-Term Memory (LSTM) models multifaceted time-series data, with Gaussian model for anomalies. We applied our approach two year's telemetry in-orbit satellites demonstrate its superiority....