A Quantum Protocol for Secure Manhattan Distance Computation [PDF]
IEEE Access, 2020 Secure Manhattan distance computation allows two parties to privately compute the Manhattan distance of their points, which is important and has broad applications.
Wen Liu, Wei Zhang
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A KNN Model Based on Manhattan Distance to Identify the SNARE Proteins [PDF]
IEEE Access, 2020 SNARE proteins, known as membrane fusion proteins, play a primary role to mediate vesicle fusion. Loss of function of the SNARE protein can lead to a variety of diseases. A method to accurately identify the SNARE protein is important and necessary.
Xing Gao, Guilin Li
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Securely Computing the Manhattan Distance under the Malicious Model and Its Applications
Applied Sciences, 2022 Manhattan distance is mainly used to calculate the total absolute wheelbase of two points in the standard coordinate system. The secure computation of Manhattan distance is a new geometric problem of secure multi-party computation.
Xin Liu +5 more
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Generalising Ward's Method for Use with Manhattan Distances.
PLoS ONE, 2017 The claim that Ward's linkage algorithm in hierarchical clustering is limited to use with Euclidean distances is investigated. In this paper, Ward's clustering algorithm is generalised to use with l1 norm or Manhattan distances.
Trudie Strauss +1 more
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The minimum Manhattan distance and minimum jump of permutations [PDF]
Journal of Combinatorial Theory - Series A, 2019 20 pages, 3 figures.
Simon R Blackburn +2 more
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Comparison of scenario reduction approaches for reservoir inflow timeseries generated by a Bayesian Neural Network. [PDF]
PLoS ONEDealing with uncertainty in predicted inflows presents a major challenge in optimal reservoir flood control. Scenario-based stochastic control approaches address this by generating multiple inflow time series from probabilistic models, each representing ...
Ja-Ho Koo +3 more
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Shortest Path Distance in Manhattan Poisson Line Cox Process [PDF]
Journal of Statistical Physics, 2020 While the Euclidean distance characteristics of the Poisson line Cox process (PLCP) have been investigated in the literature, the analytical characterization of the path distances is still an open problem. In this paper, we solve this problem for the stationary Manhattan Poisson line Cox process (MPLCP), which is a variant of the PLCP. Specifically, we
Vishnu Vardhan Chetlur +2 more
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A New Method for Determining the Embedding Dimension of Financial Time Series Based on Manhattan Distance and Recurrence Quantification Analysis [PDF]
Entropy, 2022 Jingjing Huang
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HUMAN IDENTIFICATION BASED ON FACE RECOGNITION SYSTEM
Journal of Engineering and Sustainable Development, 2021 Due to, the great electronic development, which reinforced the need to define people's identities, different methods, and databases to identification people's identities have emerged. In this paper, we compare the results of two texture analysis methods:
Saba K. Naji
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Ilkom Jurnal Ilmiah, 2020 K-Nearest Neighbor is a data mining algorithm that can be used to classify data. K-Nearest Neighbor works based on the closest distance. This research using the Euclidean and Manhattan distances to calculate the distance of Lhokseumawe-Medan bus ...
Rozzi Kesuma Dinata +2 more
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