Histopathological image classification through discriminative feature learning and mutual information-based multi-channel joint sparse representation

Histopathological image classification is a very challenging task because of the biological heterogeneities and rich geometrical structures. In this paper, we propose a novel histopathological image classification framework, which includes the discriminative feature learning and the mutual information-based multi-channel joint sparse representation. We first propose a stack-based discriminative prediction sparse decomposition (SDPSD) model by incorporating the class labels information to predict deep discriminant features automatically. Subsequently, a mutual information-based multi-channel joint sparse model (MIMCJSM) is presented to jointly encode the common component and particular components of the discriminative features. Especially, the main advantage of the MIMCJSM is the construction of a joint dictionary using a mutual information criterion, which contains a common sub-dictionary and three particular sub-dictionaries. Based on the joint dictionary, the MIMCJSM captures the relationship of multi-channel features, which can improve discriminative ability of joint sparse representation coefficients. Finally, the joint sparse representation coefficients of different levels can be aggregated using the spatial pyramid matching (SPM) model, and the linear support vector machine (SVM) is used as the classifier. Experimental results on ADL and BreaKHis datasets demonstrate that our proposed framework consistently performs better than popular existing classification frameworks. Additionally, it can show promising strong-robustness performance for histopathological image classification.     

An empirical study on consumer online shopping channel choice behavior in omni-channel environment

With the rapid diffusion of smart devices, retailers provide new forms of interactive communication channels, enabling their consumers to access through the mobile channel. The retailers recognize the importance of the mobile channel as an efficient sales channel and as a tool for CRM (Customer Relationship Management). However, CRM has become increasingly complex after adopting it to the mobile channel. It is imperative for retailers to understand consumer behavior in an omni-channel circumstance. Using the four-year transaction data obtained from the online home-shopping provider that expanded its online service (telephone, ARS, Internet website) onto a mobile platform, this research analyzes the consumer channel choice behavior in the perspectives of consumer sociodemographic information, consumer behavior, and corporate communication strategies. To explain channel choices in the omni-channel environment, we use multivariate probit model with sociodemographic variables, communication strategies, order hour, and product categories. Our empirical results indicate that age and gender have significant influences on channel choice behavior. Consumer fixates their inflow channel. Communication strategies such as SMS and app push alarm significantly influence consumer channel choice. Consumers using mobile channel are making purchases without time constraints, while others not. We observed that products that have characteristics of experience goods or credence goods tend to be purchased via mobile and Internet channels that provide detailed and additive information like consumer reviews. Finally, the results revealed substitution effect between most of the channels, except for the Internet and telephone. Our investigation contributes to omni-channel online shopping literature by empirically testing the choice behavior, cross-channel effects, and also by providing insights for online retailers.     

A framework for post-disaster communication using wireless ad hoc networks

Disaster management system requires timely delivery of large volumes of accurate messages so that an appropriate decision can be made to minimize the severity. When a disaster strikes, most of the infrastructure for communication gets uprooted. As a result, communication gets hampered. A well designed Internet of things (IoT) can play a significant role in the post-disaster scenario to minimize the losses, and save the precious lives of animals and human beings. In this paper, we have proposed a framework for post-disaster communication using wireless ad hoc networks. The framework includes: (i) a multi-channel MAC protocol to improve the network throughput, (ii) an energy aware multi-path routing to overcome the higher energy depletion rate at nodes associated with single shortest path routing, and (iii) a distributed topology aware scheme to minimize the transmission power. Above proposals, taken together intend to increase the network throughput, reduce the end-to-end delay, and enhance the network lifetime of an ad hoc network deployed for disaster response. A multi-channel MAC protocol permits the transmission from hidden and exposed nodes without interfering with the on-going transmission. We have compared the proposed framework with an existing scheme called Distressnet [1]. Simulation results show that the proposed framework achieves higher throughput, lower end-to-end delay, and an increased network longevity.     

Mechanistic investigation on the multi-channel reaction of Cl+CH2CO

All the geometries, vibrational frequencies and energies of different stationary points involved in the multi-channel reaction of the CH₂CO with Cl are calculated by B3LYP/6-311++G** and the results agree with the experimental values. The vibrational mode analysis is used to elucidate the relationships of the reactant, the transition states, intermediate and the products. Through the analysis, the major reaction channel and the minor reaction channel are confirmed. A new study method of analyzing reaction mechanism is presented.     

Adaptive weight multi-channel center similar deep hashing

To increase the richness of the extracted text modality feature information and deeply explore the semantic similarity between the modalities. In this paper, we propose a novel method, named adaptive weight multi-channel center similar deep hashing (AMCDH). The algorithm first utilizes three channels with different configurations to extract feature information from the text modality; and then adds them according to the learned weight ratio to increase the richness of the information. We also introduce the Jaccard coefficient to measure the semantic similarity level between modalities from 0 to 1, and utilize it as the penalty coefficient of the cross-entropy loss function to increase its role in backpropagation. Besides, we propose a method of constructing center similarity, which makes the hash codes of similar data pairs close to the same center point, and dissimilar data pairs are scattered at different center points to generate high-quality hash codes. Extensive experimental evaluations on four benchmark datasets show that the performance of our proposed model AMCDH is significantly better than other competing baselines. The code can be obtained from https://github.com/DaveLiu6/AMCDH.git.     

6MS局与某端局间异常话务的分析和处理

通过试呼观察和分析，找出了６ ＭＳ 局与某端局之间出现接通率低这一异常现象的原因，并有针对性地进行了处理，同时为避免其它局也出现类似的问题，提出了改进的建议。     

Students’ understanding of mathematical objects in the context of transformational geometry: Implications for constructing and understanding proofs

This research explored students’ views of geometric objects through the implementation of a curriculum module that allowed them to explore the relationships between transformational geometry and linear algebra. The majority of the students were middle and secondary mathematics education majors enrolled in a one-semester geometry course that is aimed at prospective teachers. A preponderance of the evidence suggests that the participating students, for the most part, viewed isometries operationally and viewed geometric objects (triangle, etc.) as “perceived.” Results also suggest that these two views influenced the students’ abilities to understand and to construct geometric proofs in transformational geometry.     

Lie algebroids,Lie groupoids and TFT

We construct the moduli spaces associated to the solutions of equations of motion (modulo gauge transformations) of the Poisson sigma model with target being an integrable Poisson manifold. The construction can be easily extended to a case of a generic integrable Lie algebroid. Indeed for any Lie algebroid one can associate a BF-like topological field theory which localizes on the space of algebroid morphisms, that can be seen as a generalization of flat connections to the groupoid case. We discuss the finite gauge transformations and discuss the corresponding moduli spaces. We consider the theories both without and with boundaries.     

Phase-locking of a multi-channel radial array CO2 laser

A theoretical analysis of phase-locking in a multi-channel radial array CO₂ laser is presented. The concepts are based on the theories of injection phase-locking and matrix optics. The mutual optical coupling occurring within the central region is demonstrated by theoretical deduction. Interrelated graphs of the coupling coefficient and the distance between the coupling position and the cavity mirror are calculated by numerical simulation. The results of the analysis are in accord with experimental results.     

The spectral curve theory for (k,l)-symmetric CMC surfaces

Constant mean curvature surfaces in $S^3$ can be studied via their associated family of flat connections. In the case of tori this approach has led to a deep understanding of the moduli space of all CMC tori. For compact CMC surfaces of higher genus the theory is far more involved due to the non abelian nature of their fundamental group. In this paper we extend the spectral curve theory for tori developed in Hitchin (1990), Pinkall and Sterling (1989) and for genus 2 surfaces (Heller, 2014) to CMC surfaces in $S^3$ of genus $g=k\cdot l$ with commuting ${\mathbb{Z}}_{k+1}$ and ${\mathbb{Z}}_{l+1}$ symmetries. We determine their associated family of flat connections via certain flat line bundle connections parametrized by the spectral curve. We generalize the flow on spectral data introduced in Heller (2015) and prove the short time existence of this flow for certain families of initial surfaces. In this way we obtain countably many $1-$parameter families of new CMC surfaces of higher genus with prescribed branch points and prescribed umbilics.