Relaxed 2-D Principal Component Analysis by LpL_p Norm for Face Recognition

A relaxed two dimensional principal component analysis (R2DPCA) approach is proposed for face recognition. Different to the 2DPCA, 2DPCA-$L_1$ and G2DPCA, the R2DPCA utilizes the label information (if known) of training samples to calculate a relaxation vector and presents a weight to each subset of training data. A new relaxed scatter matrix is defined and the computed projection axes are able to increase the accuracy of face recognition. The optimal $L_p$-norms are selected in a reasonable range. Numerical experiments on practical face databased indicate that the R2DPCA has high generalization ability and can achieve a higher recognition rate than state-of-the-art methods.Comment: 19 pages, 11 figure

TEQUILA: Temporal Question Answering over Knowledge Bases

Question answering over knowledge bases (KB-QA) poses challenges in handling complex questions that need to be decomposed into sub-questions. An important case, addressed here, is that of temporal questions, where cues for temporal relations need to be discovered and handled. We present TEQUILA, an enabler method for temporal QA that can run on top of any KB-QA engine. TEQUILA has four stages. It detects if a question has temporal intent. It decomposes and rewrites the question into non-temporal sub-questions and temporal constraints. Answers to sub-questions are then retrieved from the underlying KB-QA engine. Finally, TEQUILA uses constraint reasoning on temporal intervals to compute final answers to the full question. Comparisons against state-of-the-art baselines show the viability of our method

On Inner Iterations in the Shift-Invert Residual Arnoldi Method and the Jacobi--Davidson Method

Using a new analysis approach, we establish a general convergence theory of the Shift-Invert Residual Arnoldi (SIRA) method for computing a simple eigenvalue nearest to a given target $\sigma$ and the associated eigenvector. In SIRA, a subspace expansion vector at each step is obtained by solving a certain inner linear system. We prove that the inexact SIRA method mimics the exact SIRA well, that is, the former uses almost the same outer iterations to achieve the convergence as the latter does if all the inner linear systems are iteratively solved with {\em low} or {\em modest} accuracy during outer iterations. Based on the theory, we design practical stopping criteria for inner solves. Our analysis is on one step expansion of subspace and the approach applies to the Jacobi--Davidson (JD) method with the fixed target $\sigma$ as well, and a similar general convergence theory is obtained for it. Numerical experiments confirm our theory and demonstrate that the inexact SIRA and JD are similarly effective and are considerably superior to the inexact SIA.Comment: 20 pages, 8 figure

Application and research of wireless laser methane sensor in drainage pipeline monitoring

Laser methane sensor has been widely promoted and successfully applied in coal mines as a new and effective technology building on the approach of laser-based absorption detection. Compared with the traditional catalytic methane sensor, the laser methane sensor discussed offers the important advantages of a long calibration period, high detection precision, the absence of zero drift and low power consumption, all of which are significant advantages for use in coal mining applications. By compensating for the temperature and pressure of the gases present, the accuracy of the methane sensor is evident across a wide range of temperatures and pressures, making it suitable for gas detection, including methane, in pipelines as well. The wireless laser approach which is incorporated into the methane sensor allows wireless transmission and data uploading to a cloud server through NB-IoT. This tackles the problem in gas pipeline monitoring of the length of many pipelines and thus the wide distribution of the sensors, avoiding complicated wiring and thus high associated cost. Further, remote data management can then be achieved, all of which greatly improves the flexibility and security of the management of the pipeline and the data generated

Cloning and characterization of a putative transcription factor induced by abiotic stress in Zea mays

bZIP transcription factors have been reported to play important roles in plant responses to abiotic stresses. Here, we reported the cloning and characterization of a putative bZIP transcription factor (ZmbZIP17) from maize inbred line Han21, which is up-regulated by drought treatment. The open reading frame sequence of ZmbZIP17 was obtained by using 5’RACE and RT-PCR. Sequence analysis showed that ZmbZIP17 encodes a polypeptide of 563 amino acids with predicted molecular mass of59.8 kDa and pI of 5.6. Southern blot analysis showed that ZmbZIP17 exists as a single copy gene in maize genome. Subcellular localization of ZmbZIP17 was identified in nucleus. The results of real-time PCR analysis indicated that ZmbZIP17 was up-regulated by drought, heat, ABA and NaCl stressimmediately, which suggested that ZmbZIP17 is an early stage responsive gene to various abiotic stresses. The result also showed that ZmbZIP17 expressed much higher in leaves than in other organs in maize seedlings

Complex Temporal Question Answering on Knowledge Graphs

Question answering over knowledge graphs (KG-QA) is a vital topic in IR. Questions with temporal intent are a special class of practical importance, but have not received much attention in research. This work presents EXAQT, the first end-to-end system for answering complex temporal questions that have multiple entities and predicates, and associated temporal conditions. EXAQT answers natural language questions over KGs in two stages, one geared towards high recall, the other towards precision at top ranks. The first step computes question-relevant compact subgraphs within the KG, and judiciously enhances them with pertinent temporal facts, using Group Steiner Trees and fine-tuned BERT models. The second step constructs relational graph convolutional networks (R-GCNs) from the first step's output, and enhances the R-GCNs with time-aware entity embeddings and attention over temporal relations. We evaluate EXAQT on TimeQuestions, a large dataset of 16k temporal questions we compiled from a variety of general purpose KG-QA benchmarks. Results show that EXAQT outperforms three state-of-the-art systems for answering complex questions over KGs, thereby justifying specialized treatment of temporal QA

Distinguishing left- and right-handed molecules by two-step coherent pulses

Chiral molecules with broken parity symmetries can be modeled as quantum systems with cyclic-transition structures. By using these novel properties, we design two-step laser pulses to distinguish left- and right-handed molecules from the enantiomers. After the applied pulse drivings, one kind chiral molecules are trapped in coherent population trapping state, while the other ones are pumped to the highest states for ionizations. Then, different chiral molecules can be separated.Comment: 11 pages, 3 figures

From Supercurrents to Soft Terms

In this paper,hidden sectors of Ferrara-Zumino multiplets with contributions to soft terms coming from quantum supergravity are investigated in framework of gravity mediation. The two-point correlator of Ferrara-Zumino multiplets can be parameterized, which implies the wave function renormalizations of components fields in gravity supermultiplet can be evaluated in relatively simple form. Soft terms are calculated via supercurrent approach. We find gaugino masses are independent of sfermion masses on general grounds. The unification of gaugino masses is not universal. In comparison with general gauge mediation, there are no sum rules for sfermion masses of each generation.Comment: v3, 9 p