Impacts of hub nodes on the spread of Name-Your-Own-Price auction

In the Name-Your-Own-Price (NYOP) auction, the spread of bidding information among buyers is incredibly important for both buyers and sellers. However, the impact of hub nodes on the spread of bidding information is less investigated. In this research, we proposed a directed distance index, and used it to explore the roles of hub nodes during an NYOP auction. The results showed significant impacts of hub nodes on buyers’ behaviors and seller profits, but the impacts highly depend on the fading speed of information. When information fades fast, the hub nodes should be more valued to increase buyers’ bidding intention and make them bid more wisely. Seller’s profits will also be increased. While information fades slow, the hub nodes and the regular nodes should be approximately valued. Moreover, we explored the case of sharing failed bids, and found that the roles of hub nodes become more salient when buyers are more willing to share the failed bids.

RELATIONSHIP BETWEEN ACADEMIC SELF-EFFICACY AND COGNITIVE LOAD FOR STUDENTS IN DISTANCE LEARNING

The COVID-19 global pandemic has forced the education process worldwide to change its form to distance learning. This empirical study contributes to recently limited knowledge about the remote learning process. The study aimed to determine how academic self-efficacy is related to subjective cognitive load to predict achievement results in different forms of distance learning. The research method used was a quasi-experimental pilot study. The research questions were: (1) What is the relationship between academic self-efficacy, subjective cognitive load, and achievement results in teacher-directed distance learning? (2) What is the relationship between academic self-efficacy, subjective cognitive load, and achievement in student-directed distance learning? (3) What is the difference between teacher-directed and student self-directed distance learning settings regarding relationships between academic self-efficacy, subjective cognitive load, and achievement results? The measurement of academic self-efficacy and subjective cognitive load in the context of task assessment results were compared in different distance learning settings in two independent groups of 9th graders. The results suggest a significant relationship between subjective cognitive load and achievement results in student self-directed but non-significant between all variables in teacher-directed distance learning settings. In contrast, settings themselves demonstrated no influence on any measured factors.

The Distance and Median Problems in the Single-Cut-or-Join model with Single-Gene Duplications

Background: In the field of genome rearrangement algorithms, models accounting for gene duplication lead often to hard problems. For example, while computing the pairwise distance is tractable in most duplication-free models, it is NP-complete for most extensions of these models accounting for duplicated genes. Moreover, problems involving more than two genomes, such as the genome median and the Small Parsimony problem, are intractable for most duplication-free models, with some exceptions, for example the Single-Cut-or-Join (SCJ) model. Result: We introduce a variant of the SCJ distance that accounts for duplicated genes, in the context of directed evolution from an ancestral genome to a descendant genome where orthology relations between ancestral genes and their descendant are known. Our model includes two duplication mechanisms: single-gene tandem duplication and the creation of single-gene circular chromosomes. We prove that in this model, computing the directed distance and a parsimonious evolutionary scenario in terms of SCJ and single-gene duplication events can be done in linear time. We also show that the directed median problem is tractable for this distance, while the rooted median problem, where we assume that one of the given genomes is ancestral to the median, is NP-complete. We also describe an Integer Linear Program for solving this problem. We evaluate the directed distance and rooted median algorithms on simulated data. Conclusion: Our results provide a simple genome rearrangement model, extending the SCJ model to account for single-gene duplications, for which we prove a mix of tractability and hardness results. For the NP-complete rooted median problem, we design a simple Integer Linear Program. Our publicly available implementation of these algorithms for the directed distance and median problems allow to solve efficiently these problems on large instances. Availability: https://github.com/cchauve/SCJ-with-SGD

Learning Together

Creatively fostering peer-to-peer (P2P) learning reduces the distance in distance education. E-learners become teachers and learners through animated, adult oriented, self-directed distance education. Ways to mitigate social distance are discussed as are ways to enhance social capital through P2P learning. Factors that increase success in P2P e-learning are unencumbered connectivity, adult oriented facilitation, increased criticality, and learning collaboratively. The dynamic roles of learners, facilitators, and administrators are articulated along with plans for future environments conducive to learning and change. The concept onisagogy, meaning “together learning” is introduced as an approach to accelerate learning, increase satisfaction, and reduce social distance.

Research of Control Track Calculating Methods for Free Curved Surface NC Grinding

In this paper the basic principle for the free curved surface NC grinding is introduced, and then the influencing factor of envelope control track, the key question of free curved surface NC grinding, is analyzed. Finally, in this foundation, according to the principle of “minimum directed distance” the thought of the free curved surface NC grinding control track calculating method is put forward.

ROBUST OBJECT MATCHING USING A MODIFIED VERSION OF THE HAUSDORFF MEASURE

The Hausdorff distance (HD) between planar sets of points is known to be an effective measure for determining the degree of resemblance between binary images. In this paper, we analyze the conventional HD measure and propose a new Robust HD (RHD) measure. The proposed RHD measure takes into account not only the location information of the edge points, but also other factors such as the total number of the edge points whose nearest neighbors are within a specified directed distance, spurious edge segments defined by a small number of points, outliers, and occlusions. Experimental results for both synthetic and real images show that the proposed RHD measure is more efficient than the conventional HD measure.