A high-accuracy offline handwritten numeral recognition system.

Handwritten numeral recognition has been confronted with the problems of recognizing infinite varieties of patterns produced from writers with different writing habits, styles, and artistic flavors. As one of the most important topics in pattern recognition, there has been, and still is a significant performance gap between human beings and machines since the late 1960s. The primary objective of this research is to develop a high accuracy offline handwritten numeral recognition system. This thesis focuses on the architecture and performance improvement of handwritten numeral recognition systems through proper preprocessing, feature extraction, classifier design and combining different classifiers. Hybrid architectures of recognition systems are proved to be a very efficient method in recent research. This thesis proposes a multi-stage and multiexpert classification method integrated with complementary extracted features. It consists of a ruled-based classifier for one feature and neural network classifiers for all features. The final result is made from the fuzzy integral fusion of the outputs from the neural network classifiers. The experiments show that the approach achieves a better result.Dept. of Electrical and Computer Engineering. Paper copy at Leddy Library: Theses & Major Papers - Basement, West Bldg. / Call Number: Thesis2001 .Y44. Source: Masters Abstracts International, Volume: 40-06, page: 1596. Adviser: M. Ahmadi. Thesis (M.A.Sc.)--University of Windsor (Canada), 2001

Pseudo-Bag Mixup Augmentation for Multiple Instance Learning Based Whole Slide Image Classification

Given the special situation of modeling gigapixel images, multiple instance learning (MIL) has become one of the most important frameworks for Whole Slide Image (WSI) classification. In current practice, most MIL networks often face two unavoidable problems in training: i) insufficient WSI data, and ii) the data memorization nature inherent in neural networks. These problems may hinder MIL models from adequate and efficient training, suppressing the continuous performance promotion of classification models on WSIs. Inspired by the basic idea of Mixup, this paper proposes a Pseudo-bag Mixup (PseMix) data augmentation scheme to improve the training of MIL models. This scheme generalizes the Mixup strategy for general images to special WSIs via pseudo-bags so as to be applied in MIL-based WSI classification. Cooperated by pseudo-bags, our PseMix fulfills the critical size alignment and semantic alignment in Mixup strategy. Moreover, it is designed as an efficient and decoupled method adaptive to MIL, neither involving time-consuming operations nor relying on MIL model predictions. Comparative experiments and ablation studies are specially designed to evaluate the effectiveness and advantages of our PseMix. Test results show that PseMix could often improve the performance of MIL networks in WSI classification. Besides, it could also boost the generalization capacity of MIL models, and promote their robustness to patch occlusion and noisy labels. Our source code is available at https://github.com/liupei101/PseMix.Comment: 10 pages, 6 figures, 8 table

Are humorous frontline employees hotels’ secret weapons? Investigating when and why employee sense of humor promotes service performance

Despite the growing efforts devoted to exploring humor, the extant humor literature neglects the impact of employee sense of humor in the workplace, especially in the hospitality industry, an important yet understudied context. Based on person–environment fit theory, our research examines why and when employee sense of humor can influence frontline hospitality employees’ service performance. Our multi-wave research of 232 frontline hospitality employees in two Chinese hotels unveils that employee sense of humor promotes service performance by enhancing person–service job fit. Moreover, customer contact frequency strengthens the direct impact of employee sense of humor on person–service job fit and the indirect effect of employee sense of humor on service performance through person–service job fit. Our research underlines the pivotal role of humorous frontline employees in hospitality organizations

Impact of Water Mixing and Ice Formation on the Warming of Lake Superior: A Model-guided Mechanism Study

The Laurentian Great Lakes are one of the most prominent hotspots for the study of climate change induced lake warming. Warming trends in large, deep lakes, which are often inferred by the observations of lake surface temperature (LST) in most studies, are strongly linked to the total lake heat content. In this study, we use a 3D hydrodynamic model to examine the nonlinear processes of water mixing and ice formation that cause changes in lake heat content and further variation of LST. With a focus on mechanism study, a series of process-oriented experiments is carried out to understand the interactions among these processes and their relative importance to the lake heat budget. Using this hydrodynamic model, we estimate the lake heat content by integrating over the entire 3D volume. Our analysis reveals that (1) Heat content trends do not necessarily follow (can even be opposed to) trends in LST. Hence, using LST as a warming indicator can be problematic; (2) vertical mixing in water column may play a more important role in regulating lake warming than traditionally expected. Changes in the water mixing pattern can have a prolonged effect on the thermal structure; (3) Ice albedo feedback, even in cold winters, has little impact on lake thermal structure, and its influence on lake warming may have been overestimated. Our results indicate that climate change will not only affect the air-lake energy exchange but can also alter lake internal dynamics, therefore, the lake\u27s response to a changing climate may vary with time

Synthesis, Crystal Structure and Biological Activity of Two Triketone-Containing Quinoxalines as HPPD Inhibitors

Two new triketone-containing quinoxaline derivatives were designed by fragment splicing strategy and synthesized using 3,4-diaminobenzoic acid and substituted cyclohexanedione as starting materials. Both compounds were characterized by IR, 1H and 13C NMR, HRMS and X-ray diffraction. 3-Hydroxy-5-methyl-2-(quinoxaline-6-carbonyl)cyclohex-2-en-1-one (6a) crystallized in the triclinic system, space group Pī, a = 7.9829(2) Å, b = 8.1462(2) Å, c = 10.7057(3) Å, α = 84.3590(10)°, β = 89.7760(10)°, γ = 87.4190(10)°, Z = 2, V = 692.12(3) Å3, F(000) = 296, Dc = 1.335 Mg/m3, m(MoKa) = 0.095 mm–1, R = 0.0683 and wR= 0.1983. 3-Hydroxy-5,5-dimethyl-2-(3-ethoxyquinoxaline-6-carbonyl)cyclohex-2-en-1-one (6b) crystallized in the monoclinic system, space group P21/c, a = 10.1554(6) Å, b = 9.6491(6) Å, c = 17.7645(10) Å, β = 90.784(2)°, Z = 4, V = 1740.59(18) Å3, F(000) = 720, Dc = 1.299 Mg/m3, m(MoKa) = 0.092 mm–1, R = 0.0462 and wR = 0.1235. Physicochemical property comparison and ADMET prediction showed that compound 6a had similar properties to the commercial herbicide mesotrione. Molecular docking results showed that the interactions between 6a and AtHPPD were similar to mesotrione. Moreover, the extended aromatic ring system and the additional alkyl form more interactions with the surrounding residues. Examination of AtHPPD inhibition and herbicidal activity showed that 6a had similar inhibition values to mesotrione and had a superior inhibitory effect on Echinochloa crus-galli