M-N Hashing: Search Time Optimization with Collision Resolution Using Balanced Tree

2020 ◽  
pp. 196-209
Author(s):  
Arushi Agarwal ◽  
Sashakt Pathak ◽  
Sakshi Agarwal
Keyword(s):  
Search Time ◽  
Collision Resolution ◽  
Time Optimization ◽  
Balanced Tree

Acceleratingk-nearest-neighbor searches

2016 ◽  
Vol 49 (5) ◽  
pp. 1471-1477 ◽  
Author(s):  
Herbert J. Bernstein ◽  
Lawrence C. Andrews
Keyword(s):  
Nearest Neighbor ◽  
Search Time ◽  
Data Sets ◽  
Acceleration Techniques ◽  
Probe Point ◽  
Nearest Point ◽  
Particle Simulations ◽  
Balanced Tree ◽  
Point Distance ◽  
The Cost

The search for whichkpoints are closest to a given probe point in a space ofNknown points, the `k-nearest-neighbor' or `KNN' problem, is a computationally challenging problem of importance in many disciplines, such as the design of numerical databases, analysis of multi-dimensional experimental data sets, multi-particle simulations and data mining. A standard approach is to preprocess the data into a tree and make use of the triangle inequality to prune the search time to the order of the logarithm ofNfor a single nearest point in a well balanced tree. All known approaches suffer from the `curse of dimensionality', which causes the search to explore many more branches of the tree than one might wish as the dimensionality of the problem increases, driving search times closer to the order ofN. Looking forknearest points can sometimes be done in approximately the time needed to search for one nearest point, but more often it requiresksearches because the results are distributed widely. The result is very long search times, especially when the search radius is large andkis large, and individual distance calculations are very expensive, because the same probe-to-data-point distance calculations need to be executed repeatedly as the top of the tree is re-explored. Combining two acceleration techniques was found to improve the search time dramatically: (i) organizing the search into nested searches in non-overlapping annuli of increasing radii, using an estimation of the Hausdorff dimension applicable to this data instance from the results of earlier annuli to help set the radius of the next annulus; and (ii) caching all distance calculations involving the probe point to reduce the cost of repeated use of the same distances. The result of this acceleration in a search of the combined macromolecular and small-molecule data in a combined six-dimensional database of nearly 900 000 entries has been an improvement in the overall time of the searches by one to two orders of magnitude.

Studi Perilaku Anggota Unit Pengambil Keputusan Dalam Pembelian Organisasional: Sebuah Review Literatur

2017 ◽  
Vol 24 (1) ◽  
pp. 71-86
Author(s):  
Amin Wibowo
Keyword(s):  
Decision Making ◽  
Information Search ◽  
Search Time ◽  
Integrated Approach ◽  
Review Literature ◽  
Buying Behavior ◽  
Organizational Buying ◽  
Decision Making Unit ◽  
Behavior Based ◽  
Sharing Responsibility

Up to now, organizational buying is still interesting topic discussed. There are divergences among the findings in organizational buying researches. Different perspectives, fenomena observed, research domains and methods caused the divergences. This paper will discusse organizational buying behavior based on literature review, focused on behavior of decision making unit mainly on equipment buying. From this review literatures, it would be theoritical foundation that is valid and reliable to develop propositions in organizational buying behavior. Based on review literature refferences, variables are classified into: purchase situation, member of decision making unit perception, conflict among the members, information search, influences among members of decision making unit. Integrated approach is used to develop propositions relating to: purchasing complexity, sharing responsibility among the members, conflict in decision making unit, information search, time pressure as moderating variable between sharing responsibility and conflict in decision making unit, the influence among the members inside decision making unit and decision making outcome

A Methodological Approach to Conceptual Menu Design for an Electronic Newspaper

2013 ◽  
Author(s):  
Elaine G. Toms
Keyword(s):  
Information Systems ◽  
Methodological Approach ◽  
Search Time ◽  
Presentation Style ◽  
Menu Design

Menues are a key access tool for most information systems. Yet much of the significant body of research concerning menues is devoted to presentation style, selection, organization, search time, and the breadth-depth issue. Of particular interest to this research was the development of a user-centred approach to menu generation. Categories were generated from the data. . .

The Influence of Memory-Aware Computation on Distributed BLAST

2019 ◽  
Vol 14 (2) ◽  
pp. 157-163
Author(s):  
Majid Hajibaba ◽  
Mohsen Sharifi ◽  
Saeid Gorgin
Keyword(s):  
Search Time ◽  
Genomic Research ◽  
Local Alignment ◽  
Negative Effects ◽  
Sequencing Technologies ◽  
Percent Improvement ◽  
Fast Processing ◽  
Search Tool ◽  
Memory Awareness ◽  
Generation Sequencing

Background: One of the pivotal challenges in nowadays genomic research domain is the fast processing of voluminous data such as the ones engendered by high-throughput Next-Generation Sequencing technologies. On the other hand, BLAST (Basic Local Alignment Search Tool), a longestablished and renowned tool in Bioinformatics, has shown to be incredibly slow in this regard. Objective: To improve the performance of BLAST in the processing of voluminous data, we have applied a novel memory-aware technique to BLAST for faster parallel processing of voluminous data. Method: We have used a master-worker model for the processing of voluminous data alongside a memory-aware technique in which the master partitions the whole data in equal chunks, one chunk for each worker, and consequently each worker further splits and formats its allocated data chunk according to the size of its memory. Each worker searches every split data one-by-one through a list of queries. Results: We have chosen a list of queries with different lengths to run insensitive searches in a huge database called UniProtKB/TrEMBL. Our experiments show 20 percent improvement in performance when workers used our proposed memory-aware technique compared to when they were not memory aware. Comparatively, experiments show even higher performance improvement, approximately 50 percent, when we applied our memory-aware technique to mpiBLAST. Conclusion: We have shown that memory-awareness in formatting bulky database, when running BLAST, can improve performance significantly, while preventing unexpected crashes in low-memory environments. Even though distributed computing attempts to mitigate search time by partitioning and distributing database portions, our memory-aware technique alleviates negative effects of page-faults on performance.

scholarly journals University Students’ Perception of the Usefulness of the Flipped Classroom Methodology

2020 ◽  
Vol 10 (10) ◽  
pp. 275
Author(s):  
Ernesto Colomo-Magaña ◽  
Roberto Soto-Varela ◽  
Julio Ruiz-Palmero ◽  
Melchor Gómez-García
Keyword(s):  
Flipped Classroom ◽  
Education Students ◽  
Time Optimization ◽  
Educational Processes ◽  
Constant Change ◽  
Relevant Role ◽  
Educational Sciences ◽  
The University ◽  
Validated Instrument ◽  
Positive Evaluation

In a digital and interconnected context, where educational processes are in constant change, active methodologies take on a relevant role by making students the protagonists of their learning. Among the different possibilities, the flipped classroom stands out for its time optimization, the incorporation of technological resources, and the personalization of the processes. The aim of this research is to analyze the perception of higher education students about the usefulness of the flipped classroom as a methodology. The information was collected with a validated instrument, which was applied to a sample of 123 students from the Faculty of Educational Sciences of the University of Málaga (Spain). A positive evaluation of the usefulness of the flipped classroom as a learning methodology was reflected in the results, highlighting its instrumental dimension. Significant differences were perceived regarding the usefulness of the flipped classroom for the promotion of autonomous learning, which had a superior valuation according to women. In conclusion, the flipped classroom stands as a methodological alternative to promote learning that has a positive evaluation from the students that made up the sample.

scholarly journals Research on path planning of three-neighbor search A* algorithm combined with artificial potential field

2021 ◽  
Vol 18 (3) ◽  
pp. 172988142110264
Author(s):  
Jiqing Chen ◽  
Chenzhi Tan ◽  
Rongxian Mo ◽  
Hongdu Zhang ◽  
Ganwei Cai ◽  
...  
Keyword(s):  
Path Planning ◽  
Mobile Robot ◽  
Obstacle Avoidance ◽  
Potential Field ◽  
Path Length ◽  
Search Time ◽  
Experimental Results ◽  
Artificial Potential Field ◽  
A Algorithm ◽  
Neighbor Search

Among the shortcomings of the A* algorithm, for example, there are many search nodes in path planning, and the calculation time is long. This article proposes a three-neighbor search A* algorithm combined with artificial potential fields to optimize the path planning problem of mobile robots. The algorithm integrates and improves the partial artificial potential field and the A* algorithm to address irregular obstacles in the forward direction. The artificial potential field guides the mobile robot to move forward quickly. The A* algorithm of the three-neighbor search method performs accurate obstacle avoidance. The current pose vector of the mobile robot is constructed during obstacle avoidance, the search range is narrowed to less than three neighbors, and repeated searches are avoided. In the matrix laboratory environment, grid maps with different obstacle ratios are compared with the A* algorithm. The experimental results show that the proposed improved algorithm avoids concave obstacle traps and shortens the path length, thus reducing the search time and the number of search nodes. The average path length is shortened by 5.58%, the path search time is shortened by 77.05%, and the number of path nodes is reduced by 88.85%. The experimental results fully show that the improved A* algorithm is effective and feasible and can provide optimal results.

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