scholarly journals HyBiX: A novel encoding bitmap index for space- and time-efficient query processing

2019 ◽  
pp. 1504-1522
Author(s):  
NAPHAT KEAWPIBA ◽  
LADDA PREECHAVEERAKUL ◽  
SIRIRUT VANICHAYOBON
Keyword(s):  
Execution Time ◽  
Low Cost ◽  
Range Queries ◽  
Query Execution ◽  
Bitmap Index ◽  
Trade Off ◽  
Space And Time ◽  
Indexing Method ◽  
Efficient Query Processing ◽  
Space Requirements

A bitmap-based index is an effective and efficient indexing method for answering selective queries in a read- only environment. It offers improved query execution time by applying low-cost Boolean operators on the index directly, before accessing raw data. A drawback of the bitmap index is that index size increases with the cardinality of indexed attributes, which additionally has an impact on a query execution time. This impact is related to an increase of query execution time due to the scanning of bitmap vectors to answer the queries. In this paper, we propose a new encoding bitmap index, called the HyBiX bitmap index. The HyBiX bitmap index was experimentally compared to existing encoding bitmap indexes in terms of space requirement, query execution time, and space and time trade-off for equality and range queries. As experimental results, the HyBiX bitmap index can reduce space requirements with high cardinality attributes with satisfactory execution times for both equality and range queries. The performance of the HyBiX bitmap index provides the second-best results for equality queries and the first-best for range queries in terms of space and time trade-off.

scholarly journals Optimizing Range Query Processing for Dual Bitmap Index

2018 ◽  
Vol 16 (2) ◽  
pp. 133-142
Author(s):  
Naphat KEAWPIBAL ◽  
Ladda PREECHAVEERAKUL ◽  
Sirirut VANICHAYOBON
Keyword(s):  
Query Processing ◽  
Range Query ◽  
Range Queries ◽  
Boolean Operations ◽  
Bitmap Index ◽  
Indexing Method ◽  
Overall Performance ◽  
Optimizing Algorithm ◽  
Bitmap Indexes ◽  
Range Query Processing

Bitmap-based indexes are known to be the most effective indexing method for retrieving and answering selective queries in a read-only environment. Various types of encoding bitmap indexes significantly improve query time efficiency by utilizing fast Boolean operations directly on the index before retrieving the raw data. In particular, the dual bitmap index improves the performance of equality queries in terms of the space vs. time trade-off. However, the performance of range queries is unsatisfactory. In this paper, an optimizing algorithm is proposed to improve the range query processing for the dual bitmap index. The results of the experiment conducted show that the proposed algorithm, called Dual-simRQ, reduces the number of bitmap vectors scanned and the Boolean operations performed, which impacts the overall performance for range query processing.

scholarly journals Diagnostic Capabilities of a Smartphone- Based Low-Cost Microscope

2020 ◽  
Vol 6 (3) ◽  
pp. 522-525
Author(s):  
Dorina Hasselbeck ◽  
Max B. Schäfer ◽  
Kent W. Stewart ◽  
Peter P. Pott
Keyword(s):  
Low Cost ◽  
Field Of View ◽  
Parasitic Diseases ◽  
Optical Parameters ◽  
Trade Off ◽  
Resource Limited ◽  
Wide Range ◽  
Diagnostic Applications ◽  
Diagnostic Capabilities

AbstractMicroscopy enables fast and effective diagnostics. However, in resource-limited regions microscopy is not accessible to everyone. Smartphone-based low-cost microscopes could be a powerful tool for diagnostic and educational purposes. In this paper, the imaging quality of a smartphone-based microscope with four different optical parameters is presented and a systematic overview of the resulting diagnostic applications is given. With the chosen configuration, aiming for a reasonable trade-off, an average resolution of 1.23 μm and a field of view of 1.12 mm2 was achieved. This enables a wide range of diagnostic applications such as the diagnosis of Malaria and other parasitic diseases.

A Low-Cost Hexa Platform for Efficient Force Control Systems Using Industrial Manipulators

2009 ◽  
Vol 147-149 ◽  
pp. 1-6 ◽  
Author(s):  
Rafal Osypiuk ◽  
Torsten Kröger
Keyword(s):  
Control Systems ◽  
Force Control ◽  
Execution Time ◽  
Low Cost ◽  
Degree Of Freedom ◽  
Industrial Manipulators ◽  
Control Concept ◽  
Six Dof ◽  
Parallel Platform ◽  
Six Degree Of Freedom

This contribution presents a new force control concept for industrial six-degree of freedom (DOF) manipulators, which uses a Hexa platform that provides an active environmental stiffness for all six DOFs. The paper focuses on the Hexa platform and is split into two essential parts: (i) parallel platform construction, and (ii) application of force control with industrial manipulators using a six-DOF environmental stiffness. This mechatronic solution almost gives one hundred percent robustness for stiffness changes in the environment, what guaranties a significant shortening of execution time.

scholarly journals Uncertainty aware query execution time prediction

2014 ◽  
Vol 7 (14) ◽  
pp. 1857-1868 ◽  
Author(s):  
Wentao Wu ◽  
Xi Wu ◽  
Hakan Hacigümüş ◽  
Jeffrey F. Naughton
Keyword(s):  
Execution Time ◽  
Query Execution ◽  
Time Prediction ◽  
Query Execution Time Prediction ◽  
Execution Time Prediction

scholarly journals Plant Leaf Detection and Counting in a Greenhouse during Day and Nighttime Using a Raspberry Pi NoIR Camera

Sensors ◽  
2021 ◽  
Vol 21 (19) ◽  
pp. 6659
Author(s):  
Aryuanto Soetedjo ◽  
Evy Hendriarianti
Keyword(s):  
Execution Time ◽  
Low Cost ◽  
Infrared Camera ◽  
Raspberry Pi ◽  
Camera System ◽  
Detection And Counting ◽  
Outdoor Environments ◽  
Static Images ◽  
Leaf Detection ◽  
Non Destructive

A non-destructive method using machine vision is an effective way to monitor plant growth. However, due to the lighting changes and complicated backgrounds in outdoor environments, this becomes a challenging task. In this paper, a low-cost camera system using an NoIR (no infrared filter) camera and a Raspberry Pi module is employed to detect and count the leaves of Ramie plants in a greenhouse. An infrared camera captures the images of leaves during the day and nighttime for a precise evaluation. The infrared images allow Otsu thresholding to be used for efficient leaf detection. A combination of numbers of thresholds is introduced to increase the detection performance. Two approaches, consisting of static images and image sequence methods are proposed. A watershed algorithm is then employed to separate the leaves of a plant. The experimental results show that the proposed leaf detection using static images achieves high recall, precision, and F1 score of 0.9310, 0.9053, and 0.9167, respectively, with an execution time of 551 ms. The strategy of using sequences of images increases the performances to 0.9619, 0.9505, and 0.9530, respectively, with an execution time of 516.30 ms. The proposed leaf counting achieves a difference in count (DiC) and absolute DiC (ABS_DiC) of 2.02 and 2.23, respectively, with an execution time of 545.41 ms. Moreover, the proposed method is evaluated using the benchmark image datasets, and shows that the foreground–background dice (FBD), DiC, and ABS_DIC are all within the average values of the existing techniques. The results suggest that the proposed system provides a promising method for real-time implementation.

scholarly journals Development and Validation of a Homemade, Low-Cost Laparoscopic Simulator for Resident Surgeons (LABOT)

2020 ◽  
Vol 17 (1) ◽  
pp. 323 ◽  
Author(s):  
Domenico Soriero ◽  
Giulia Atzori ◽  
Fabio Barra ◽  
Davide Pertile ◽  
Andrea Massobrio ◽  
...  
Keyword(s):  
Surgical Training ◽  
Execution Time ◽  
Low Cost ◽  
Technical Skills ◽  
Training Simulator ◽  
Rating Score ◽  
Laparoscopic Skills ◽  
Laparoscopic Simulator ◽  
Development And Validation

Several studies have demonstrated that training with a laparoscopic simulator improves laparoscopic technical skills. We describe how to build a homemade, low-cost laparoscopic training simulator (LABOT) and its validation as a training instrument. First, sixty surgeons filled out a survey characterized by 12 closed-answer questions about realism, ergonomics, and usefulness for surgical training (global scores ranged from 1—very insufficient to 5—very good). The results of the questionnaires showed a mean (±SD) rating score of 4.18 ± 0.65 for all users. Then, 15 students (group S) and 15 residents (group R) completed 3 different tasks (T1, T2, T3), which were repeated twice to evaluate the execution time and the number of users’ procedural errors. For T1, the R group had a lower mean execution time and a lower rate of procedural errors than the S group; for T2, the R and S groups had a similar mean execution time, but the R group had a lower rate of errors; and for T3, the R and S groups had a similar mean execution time and rate of errors. On a second attempt, all the participants tended to improve their results in doing these surgical tasks; nevertheless, after subgroup analysis of the T1 results, the S group had a better improvement of both parameters. Our laparoscopic simulator is simple to build, low-cost, easy to use, and seems to be a suitable resource for improving laparoscopic skills. In the future, further studies should evaluate the potential of this laparoscopic box on long-term surgical training with more complex tasks and simulation attempts.

Predicting SQL Query Execution Time with a Cost Model for Spark Platform

2020 ◽  
Author(s):  
Aleksey Burdakov ◽  
Viktoria Proletarskaya ◽  
Andrey Ploutenko ◽  
Oleg Ermakov ◽  
Uriy Grigorev
Keyword(s):  
Execution Time ◽  
Cost Model ◽  
Query Execution ◽  
Sql Query
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