Time series has been a popular research topic over the past decade. Salient subsequences of time that can benefit learning task, e.g., classification or clustering, are called shapelets. Shapelet-based extracts these types salient with highly informative features from series. Most existing methods for shapelet discovery must scan large pool candidate subsequences, which is time-consuming process. A recent work, [1] , uses regression to discover shapelets in series; however, it only considers...

In this paper, we study a new problem of continuous learning from doubly-streaming data where both volume and feature space increase over time. We refer to the as trapezoidal streams corresponding online streams. The is challenging because dimension time, existing <xref ref-type="bibr" rid="ref1"> [1]</xref> , rid="ref2">[2]</xref> selection rid="ref3">[3]</xref> streaming algorithms rid="ref4">[4]</xref> rid="ref5">[5]</xref> are inapplicable. propose Online Learning with Streaming Features...

Abstract Background Inflammatory osteolysis after total joint replacement (TJR) may cause implant failure, periprosthetic fractures, and be a severe threat to global public health. Our previous studies demonstrated that melatonin had therapeutic effect on wear-particles induced osteolysis. Gut microbiota is closely related bone homeostasis, has been proven affected by melatonin. However, whether could play its anti-osteolysis effects through reprogramming gut remains elusive. Results Here,...

This study investigates classroom communication apprehension in Chinese college classrooms reference to perceived instructor verbal and nonverbal immediacy humor orientation, student individual-level power distance. Results of Pearson correlation indicate that both distance perceptions orientation are correlated positively significantly with apprehension, but multiple regression analyses suggest is the only effective predictor apprehension. Perceived not associated Limitations, implications,...

We study efficient algorithms for the Euclidean $k$-Center problem, focusing on regime of large $k$. take approach data reduction by considering $\alpha$-coreset, which is a small subset $S$ dataset $P$ such that any $\beta$-approximation an $(\alpha + \beta)$-approximation $P$. give to construct coresets whose size $k \cdot o(n)$, immediately speeds up existing approximation algorithms. Notably, we obtain near-linear time $O(1)$-approximation when = n^c$ $0 < c 1$. validate performance our...

This study constructs an acupuncture knowledge graph (AcuKG) to systematically organize and represent acupuncture-related in a structured scalable format. By extracting integrating from diverse data sources, covering indication, treatment efficacy, practice guidelines, clinical research etc., AcuKG enhances discovery utilization while improving interoperability the field of acupuncture. To achieve this, we employ multiple methods, including entity recognition, term normalization, semantic...

Conventional wisdom in the software engineering research community says that metrics can make project management more effective. Software range from internal product attributes such as size, complexity, and modularity to external process effort, productivity, reliability. telemetry facilitates local, in-process decision making.

In this study, we used the broaden-and-build theory and emotional response as framework to examine effects of instructors' positive emotions on student engagement critical thinking in U.S. Chinese classrooms, well mediating role students' their relationships. MANOVA results revealed no significant cultural differences reports own across two cultures, but instructors from both cultures displayed more than what students felt or experienced classroom. Hierarchical regression analyses also...

Brain electroencephalography (EEG), the complex, weak, multivariate, nonlinear, and nonstationary time series, has been recently widely applied in neurocognitive disorder diagnoses brain-machine interface developments. With its specific features, unlabeled EEG is not well addressed by conventional unsupervised time-series learning methods. In this article, we handle problem of clustering propose a novel algorithm, that call mwcEEGc. The idea to map maximum-weight clique (MWC) searching an...

Traditional soft margin support vector machine usually uses hinge loss to build a classifier with the "maximum-margin" principle. However, C-SVM depends on vectors causing of data information. Then, least square is proposed ( <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$l_{2}$ </tex-math></inline-formula> -loss). It establishes equality constraints instead inequalities and considering all instances....

Measurement definition, collection, and analysis is an essential component of high quality software engineering practice, thus the curriculum. However, providing students with practical experience measurement in a classroom setting can be so time-consuming intrusive that it's counter-productive-teaching impractical for many development contexts. In this research, we designed evaluated very low-overhead approach to collection using Hackystat system special features use. We deployed two...

We study a new problem of learning from doubly-streaming data where both volume and feature space increase over time. refer to the as mining trapezoidal streams. The is challenging because are increasing, which existing online learning, selection streaming algorithms inapplicable. propose Sparse Trapezoidal Streaming Data algorithm (STSD) its two variants combine enable streams with infinite training instances features. Specifically, when carrying features arrive, classifier updates by...

The purpose of this study was to conduct a cross-cultural test three U.S.-based immediacy–learning models and compare proposed integrating model with the existing in Chinese classrooms. findings suggested that affective learning provided better fit than model, which had motivation Based on U.S.-generated models, an posited teacher immediacy both direct path, indirect path mediated first through then motivation, cognitive learning. finding best data

The estimation of ice forces are critical to Dynamic Positioning (DP) operations in Arctic waters.Ice conditions important for the analysis ice-structure interaction an field.To monitor sea-ice conditions, cameras used as field observation sensors on mobile sensor platforms Arctic.Various image processing techniques, such Otsu thresholding, k-means clustering, distance transform, Gradient Vector Flow (GVF) Snake, mathematical morphology, then applied obtain concentration, types, and floe...

Influence measurement in social networks is vital to various real-world applications, such as online marketing and political campaigns. In this paper, we investigate the problem of measuring time-sensitive topic-specific influence based on streaming texts dynamic networks. A user's can change rapidly response a new event vary different topics. For example, Douglas Jones increased dramatically after winning Alabama special election, then decreased election week. During same period, however,...

This study investigated the effect of perceived teacher burnout on credibility. One hundred eighty-two college students were randomly exposed to a written scenario manipulating level (high or low) and responded scale measuring credibility in reference scenario. Results one-way multivariate analyses variance indicated that has negative impact competence, caring, trustworthiness. Low-burnout teachers are as more credible than high-burnout teachers.

This study examined the dynamic interplays between emotions (i.e., anger and compassion), face threat, forgiveness, reconciliation in relational transgressions U.S. Chinese cultures. Results indicated that participants reported more relationship-oriented forgiveness than participants, but no distinction was uncovered self-oriented forgiveness. also showed that, relative to preforgiveness, there less postforgiveness compassion both Anger had a negative association, positive with Perceived...

Abstract Malignant glioma is a formidable disease that commonly leads to death, mainly due the invasion of tumor cells into neighboring tissues. Therefore, inhibition cell may provide an effective therapy for malignant glioma. Here we report nicotinic acid (NA), essential vitamin, inhibits in vitro and vivo . Treatment U251 with NA results reduced invasion, which accompanied by loss mesenchymal phenotype increase cell-cell adhesion. At molecular level, transcription adherens junction protein...

Precision agriculture is a data-driven farming practice that uses intra-and inter-field information to optimize operations. The "brain" of precision decision support system (DSS) acquires data from various sources, analyzes them, and recommends actions farmers. Recently cloud computing has been used improve the scalability reliability DSS. Cloud-based DSSs present some major challenges for software design:(1) how can cloud-based DSS process diversified profile intra-and/or sources? (2)...

The design method of a real-time FFT processor is presented. By optimizing algorithm memory mapping and generation twiddle factors, radix-4 butterfly can be calculated in one clock cycle. An approach to adaptive overflow control also introduced avoid without interrupting the computing pipeline. implemented on FPGA chip achieves operating frequency at 127 MHz. It complete complex 1024-point within 10.1 μs.