electron paramagnetic resonance (epr) spectroscopy, also known as electron spin resonance(esr) especially among physicists, is a strong and versatile spectroscopic method forinvestigation of paramagnetic systems, i.e. systems like free radicals and most transition metalions, which have unpaired electrons. the sensitivity and selectivity of epr are notable andintriguing as compared to other spec...

Multi-label classification is an important task in many modern machine learning applications. Accurate methods model the correlations and relationships between labels, either by assuming a low-dimensional embedding of the labels or a graph structure of label dependencies. While such interactions can be achieved using feed-forward predictors, problems with tight coupling between labels are bette...

background and objective: formalin-fixed paraffin-embedded tissues are a valuable source of dna for molecular studies. we designed and optimized an efficient procedure for dna extraction from formalin-fixed paraffin embedded tissues. materials and methods: seventy three blocks of cervical paraffin-embedded tissues were investigated. dna was extracted using 45 minutes boiling in alkaline solutio...

To deal with ambiguities in partial multi-label learning (PML), existing popular PML research attempts to perform disambiguation by direct ground-truth label identification. However, these approaches can be easily misled noisy false-positive labels the iteration of updating model parameter and latent variables. When labeling information is ambiguous, we should depend more on underlying structur...

labeling theory is one of the most famous theories in criminology domain. the pivots of this theory consist of the role of power owners in definition of crime and determination of offender, effects of labeling and solutions for prevention of entering label. with study the pivots of labeling theory in islamic sources, we observe that however there is no similarity between religious bases and bas...

We extend the powerful Pullback-Pushout (PBPO) approach for graph rewriting with strong matching. Our approach, called PBPO $$^{+}$$ , exerts more control over embedding of pattern in host graph, which is important a large class rewrite systems. In addition, we show that well-suited labeled graphs and certain classes attributed graphs. For this purpose, employ lattice structure on label set use...

Confounded information is an objective fact when using multi-instance learning (MIL) to classify bags of instances, which may be inherited by MIL embedding methods and lead questionable bag label prediction. To respond this problem, we propose the with deconfounded instance-level prediction algorithm. Unlike traditional embedding-based strategies, design a optimization goal maximize distinction...

The investigation presented in this paper is a novel method in question answering (QA) that enables a QA system to gain performance through reuse of information in the answer to one question to answer another related question. Our analysis shows that a pair of question in a general open domain QA can have embedding relation through their mentions of noun phrase expressions. We present methods f...

Few-shot learning can adapt the classification model to new labels with only a few labeled examples. Previous studies mainly focus on scenario of single category label per example but have not solved more challenging multi-label exponential-sized output space and low-data effectively. In this paper, we propose semantic-aware meta-learning for few-shot learning. Our approach learn infer semantic...