Extending the Classical Multidimensional Scaling Algorithm Given Partial Pairwise Distance Measurements

Road sensor network is an important part of vehicle networks system and is critical for many intelligent automobile scenarios, such as vehicle safety monitoring and transportation efficiency supporting. Localization of sensors is an active and crucial issue to most applications of road sensor network. Generally, given some anchor nodes’ positions and certain pairwise distance measurements, estimating the positions of all nonanchor nodes embodies a nonconvex optimization problem. However, due to the small number of anchor nodes and low sensor node connectivity degree in road sensor networks, the existing localization solutions are ineffective. In order to tackle this problem, a novel distributed localization method based on game theory for road sensor networks is proposed in this paper. Formally, we demonstrate that our proposed localization game is a potential game. Furthermore, we present several techniques to accelerate the convergence to the optimal solution. Simulation results demonstrate the effectiveness of our proposed algorithm.

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Assessing the Ability of Multidimensional Scaling and Pathfinder Networks to Measure Spatial Knowledge

Proceedings of the Human Factors and Ergonomics Society Annual Meeting ◽

10.1177/1071181320641070 ◽

2020 ◽

Vol 64 (1) ◽

pp. 303-307

Author(s):

Caleb Furlough ◽

Douglas J. Gillan

Keyword(s):

Multidimensional Scaling ◽

Dimensional Space ◽

Cognitive Maps ◽

Semantic Knowledge ◽

Spatial Knowledge ◽

Pairwise Distance ◽

Pathfinder Networks ◽

Sketch Maps ◽

Highly Correlated ◽

Study Participants

Cognitive maps, or mental representations of external environments, aid spatial navigation. Typically, researchers study cognitive maps by having participants provide a sketched map. However, multidimensional scaling (MDS) and Pathfinder, statistical techniques which represent a set of input proximities as a n-dimensional space or a network, respectively, can both be used as measures of cognitive maps. Previous research with semantic knowledge suggests that Pathfinder is better than MDS for mental modelling. In the present study, participants drew maps of a familiar environment from memory and provided pairwise distance ratings for landmarks present in those locations. Using those distance ratings as inputs for MDS solutions and Pathfinder networks, the extent to which MDS and Pathfinder related to the participant sketch maps was assessed. Results indicated that MDS solutions were more highly correlated with sketch maps than were Pathfinder networks.

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Relationships, derived from optimum alignments, among amino acid sequences of plant peroxidases

Canadian Journal of Botany ◽

10.1139/b92-069 ◽

1992 ◽

Vol 70 (3) ◽

pp. 543-556 ◽

Cited By ~ 9

Author(s):

Hugh Tyson

Keyword(s):

Amino Acid ◽

Dna Sequences ◽

Average Distance ◽

Amino Acid Sequences ◽

Pairwise Distance ◽

Distance Measurements ◽

Plant Peroxidases ◽

Optimum Alignment ◽

Sequence Relationships ◽

Sequence Similarities

The amino acid and (or) DNA sequences of 13 plant peroxidases (EC 1.11.1.7), which include isozymes within species, are currently available in data bases; all have similar lengths of approximately 300 amino acids. Sequence relationships among these 13, plus 2 microbial peroxidases of similar length, were examined. The 15 sequences were compared in all 105 pairwise combinations using optimum alignment procedures. Gap penalties were determined from analysis of penalty change effects. Distances between sequences generated by optimum alignments were analysed by clustering techniques to generate dendrograms. Specific distances, which provided pairwise distance measurements independent of the average distance for a sequence, were used to evaluate sequence similarities; closely related sequences produce closely correlated specific distances. Among the seven plant species, five subgroups were established: (1) horseradish isoperoxidases, (2) turnip and wheat, (3) cucumber and tobacco, (4) potato and tomato, and (5) in which cytochrome c peroxidase showed some similarity to ligninase, but both were only distantly related to plant peroxidases. Horseradish isoperoxidases were related to sequences in subgroups 2, 3, and 4 but resembled subgroups 2 and 3 more closely than 4. Subgroup 2 was more related to 3 than any other. Key words: plant peroxidases, sequence relationships, peroxidase profiles.

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