scholarly journals Indexing algorithm based on storing additional distances in metric space for multi-vantage-point tree

2021 ◽  
pp. 18-27
Author(s):  
Igor Akeksandrov ◽  
Vladimir Fomin
Keyword(s):  
Metric Space ◽  
Similarity Search ◽  
Structural Changes ◽  
Search Algorithm ◽  
Accurate Determination ◽  
Classical Problem ◽  
Search Algorithms ◽  
Vantage Point ◽  
Complex Data ◽  
Access Methods

Introduction: The similarity search paradigm is used in various computational tasks, such as classification, data mining, pattern recognition, etc. Currently, the technology of tree-like metric access methods occupies a significant place among search algorithms. The classical problem of reducing the time of similarity search in metric space is relevant for modern systems when processing big complex data. Due to multidimensional nature of the search algorithm effectiveness problem, local research in this direction is in demand, constantly bringing useful results. Purpose: To reduce the computational complexity of tree search algorithms in problems involving metric proximity. Results: We developed a search algorithm for a multi-vantage-point tree, based on the priority node-processing queue. We mathematically formalized the problems of additional calculations and ways to solve them. To improve the performance of similarity search, we have proposed procedures for forming a priority queue of processing nodes and reducing the number of intersections of same level nodes. Structural changes in the multi-vantage-point tree and the use of minimum distances between vantage points and node subtrees provide better search efficiency. More accurate determination of the distance from the search object to the nodes and the fact that the search area intersects with a tree node allows you to reduce the amount of calculations. Practical relevance: The resulting search algorithms need less time to process information due to an insignificant increase in memory requirements. Reducing the information processing time expands the application boundaries of tree metric indexing methods in search problems involving large data sets.

scholarly journals Visualizing the Bohr effect in hemoglobin: neutron structure of equine cyanomethemoglobin in the R state and comparison with human deoxyhemoglobin in the T state

2016 ◽  
Vol 72 (7) ◽  
pp. 892-903 ◽  
Author(s):  
Steven Dajnowicz ◽  
Sean Seaver ◽  
B. Leif Hanson ◽  
S. Zoë Fisher ◽  
Paul Langan ◽  
...  
Keyword(s):  
Structural Changes ◽  
Accurate Determination ◽  
Bohr Effect ◽  
Salt Bridges ◽  
Histidine Residues ◽  
Regions Of Stability ◽  
The Individual ◽  
T State

Neutron crystallography provides direct visual evidence of the atomic positions of deuterium-exchanged H atoms, enabling the accurate determination of the protonation/deuteration state of hydrated biomolecules. Comparison of two neutron structures of hemoglobins, human deoxyhemoglobin (T state) and equine cyanomethemoglobin (R state), offers a direct observation of histidine residues that are likely to contribute to the Bohr effect. Previous studies have shown that the T-state N-terminal and C-terminal salt bridges appear to have a partial instead of a primary overall contribution. Four conserved histidine residues [αHis72(EF1), αHis103(G10), αHis89(FG1), αHis112(G19) and βHis97(FG4)] can become protonated/deuterated from the R to the T state, while two histidine residues [αHis20(B1) and βHis117(G19)] can lose a proton/deuteron. αHis103(G10), located in the α1:β1dimer interface, appears to be a Bohr group that undergoes structural changes: in the R state it is singly protonated/deuterated and hydrogen-bonded through a water network to βAsn108(G10) and in the T state it is doubly protonated/deuterated with the network uncoupled. The very long-term H/D exchange of the amide protons identifies regions that are accessible to exchange as well as regions that are impermeable to exchange. The liganded relaxed state (R state) has comparable levels of exchange (17.1% non-exchanged) compared with the deoxy tense state (T state; 11.8% non-exchanged). Interestingly, the regions of non-exchanged protons shift from the tetramer interfaces in the T-state interface (α1:β2and α2:β1) to the cores of the individual monomers and to the dimer interfaces (α1:β1and α2:β2) in the R state. The comparison of regions of stability in the two states allows a visualization of the conservation of fold energy necessary for ligand binding and release.

scholarly journals Circumspect descent prevails in solving random constraint satisfaction problems

2008 ◽  
Vol 105 (40) ◽  
pp. 15253-15257 ◽  
Author(s):  
Mikko Alava ◽  
John Ardelius ◽  
Erik Aurell ◽  
Petteri Kaski ◽  
Supriya Krishnamurthy ◽  
...  
Keyword(s):  
Local Search ◽  
Linear Time ◽  
Search Algorithm ◽  
Solution Space ◽  
Search Algorithms ◽  
Constraint Satisfaction Problems ◽  
Problem Instance ◽  
Stochastic Local Search ◽  
Local Search Algorithms ◽  
Local Energy Minimum

We study the performance of stochastic local search algorithms for random instances of the K-satisfiability (K-SAT) problem. We present a stochastic local search algorithm, ChainSAT, which moves in the energy landscape of a problem instance by never going upwards in energy. ChainSAT is a focused algorithm in the sense that it focuses on variables occurring in unsatisfied clauses. We show by extensive numerical investigations that ChainSAT and other focused algorithms solve large K-SAT instances almost surely in linear time, up to high clause-to-variable ratios α; for example, for K = 4 we observe linear-time performance well beyond the recently postulated clustering and condensation transitions in the solution space. The performance of ChainSAT is a surprise given that by design the algorithm gets trapped into the first local energy minimum it encounters, yet no such minima are encountered. We also study the geometry of the solution space as accessed by stochastic local search algorithms.

Distributed similarity search algorithm in distributed heterogeneous multimedia databases

2000 ◽  
Vol 75 (1-2) ◽  
pp. 35-42 ◽  
Author(s):  
Ju-Hong Lee ◽  
Deok-Hwan Kim ◽  
Seok-Lyong Lee ◽  
Chin-Wan Chung ◽  
Guang-Ho Cha
Keyword(s):  
Similarity Search ◽  
Search Algorithm ◽  
Multimedia Databases

scholarly journals Finding A Small Vertex Cover in Massive Sparse Graphs: Construct, Local Search, and Preprocess

2017 ◽  
Vol 59 ◽  
pp. 463-494 ◽  
Author(s):  
Shaowei Cai ◽  
Jinkun Lin ◽  
Chuan Luo
Keyword(s):  
Local Search ◽  
Real World ◽  
Large Scale ◽  
Heuristic Algorithms ◽  
Search Algorithm ◽  
Vertex Cover ◽  
Search Algorithms ◽  
Theory And Practice ◽  
Sparse Graphs ◽  
Massive Graphs

The problem of finding a minimum vertex cover (MinVC) in a graph is a well known NP-hard combinatorial optimization problem of great importance in theory and practice. Due to its NP-hardness, there has been much interest in developing heuristic algorithms for finding a small vertex cover in reasonable time. Previously, heuristic algorithms for MinVC have focused on solving graphs of relatively small size, and they are not suitable for solving massive graphs as they usually have high-complexity heuristics. This paper explores techniques for solving MinVC in very large scale real-world graphs, including a construction algorithm, a local search algorithm and a preprocessing algorithm. Both the construction and search algorithms are based on low-complexity heuristics, and we combine them to develop a heuristic algorithm for MinVC called FastVC. Experimental results on a broad range of real-world massive graphs show that, our algorithms are very fast and have better performance than previous heuristic algorithms for MinVC. We also develop a preprocessing algorithm to simplify graphs for MinVC algorithms. By applying the preprocessing algorithm to local search algorithms, we obtain two efficient MinVC solvers called NuMVC2+p and FastVC2+p, which show further improvement on the massive graphs.

On the Similarity Search With Hamming Space Sketches

2021 ◽  
pp. 97-127
Author(s):  
Vladimir Mic ◽  
Pavel Zezula
Keyword(s):  
Computational Complexity ◽  
Metric Space ◽  
Similarity Search ◽  
Space Model ◽  
Similarity Query ◽  
Speed Up ◽  
Hamming Space ◽  
Definition Of ◽  
Metric Function ◽  
Selection Of

This chapter focuses on data searching, which is nowadays mostly based on similarity. The similarity search is challenging due to its computational complexity, and also the fact that similarity is subjective and context dependent. The authors assume the metric space model of similarity, defined by the domain of objects and the metric function that measures the dissimilarity of object pairs. The volume of contemporary data is large, and the time efficiency of similarity query executions is essential. This chapter investigates transformations of metric space to Hamming space to decrease the memory and computational complexity of the search. Various challenges of the similarity search with sketches in the Hamming space are addressed, including the definition of sketching transformation and efficient search algorithms that exploit sketches to speed-up searching. The indexing of Hamming space and a heuristic to facilitate the selection of a suitable sketching technique for any given application are also considered.

Quantum dialogue protocol based on Grover’s search algorithms

2019 ◽  
Vol 34 (21) ◽  
pp. 1950169
Author(s):  
Aihan Yin ◽  
Kemeng He ◽  
Ping Fan
Keyword(s):  
Heuristic Search ◽  
Search Algorithm ◽  
Search Algorithms ◽  
Quantum Dialogue ◽  
Quantum Search ◽  
Decoy State ◽  
Quantum Search Algorithm ◽  
Heuristic Search Algorithms ◽  
Security Information

Among many classic heuristic search algorithms, the Grover quantum search algorithm (QSA) can play a role of secondary acceleration. Based on the properties of the two-qubit Grover QSA, a quantum dialogue (QD) protocol is proposed. In addition, our protocol also utilizes the unitary operations and single-particle measurements. The transmitted quantum state (except for the decoy state used for detection) can transmit two-bits of security information simultaneously. Theoretical analysis shows that the proposed protocol has high security.

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