scholarly journals Non-Extensive Thermodynamics of Algorithmic Processing - the Case of Insertion Sort Algorithm

10.5772/13173 ◽  
2011 ◽  
Author(s):  
Dominik Strzaka ◽  
Franciszek Grabowski
Keyword(s):  
Sort Algorithm

scholarly journals Deep Learning-Based Object Detection, Localisation and Tracking for Smart Wheelchair Healthcare Mobility

2020 ◽  
Vol 18 (1) ◽  
pp. 91
Author(s):  
Louis Lecrosnier ◽  
Redouane Khemmar ◽  
Nicolas Ragot ◽  
Benoit Decoux ◽  
Romain Rossi ◽  
...  
Keyword(s):  
Object Detection ◽  
Object Tracking ◽  
Indoor Environment ◽  
Distance Estimation ◽  
Depth Estimation ◽  
Detection Algorithm ◽  
Use Case ◽  
Detection Distance ◽  
Detection Depth ◽  
Sort Algorithm

This paper deals with the development of an Advanced Driver Assistance System (ADAS) for a smart electric wheelchair in order to improve the autonomy of disabled people. Our use case, built from a formal clinical study, is based on the detection, depth estimation, localization and tracking of objects in wheelchair’s indoor environment, namely: door and door handles. The aim of this work is to provide a perception layer to the wheelchair, enabling this way the detection of these keypoints in its immediate surrounding, and constructing of a short lifespan semantic map. Firstly, we present an adaptation of the YOLOv3 object detection algorithm to our use case. Then, we present our depth estimation approach using an Intel RealSense camera. Finally, as a third and last step of our approach, we present our 3D object tracking approach based on the SORT algorithm. In order to validate all the developments, we have carried out different experiments in a controlled indoor environment. Detection, distance estimation and object tracking are experimented using our own dataset, which includes doors and door handles.

Compression evaluation of surgery video recordings retaining diagnostic credibility (compression evaluation of surgery video)

2008 ◽  
Vol 16 (4) ◽  
Author(s):  
M. Duplaga ◽  
M. Leszczuk ◽  
Z. Papir ◽  
A. Przelaskowski
Keyword(s):  
Digital Video ◽  
Vector Measure ◽  
Lossless Compression ◽  
Video Content ◽  
Video Recordings ◽  
Subjective Tests ◽  
Objective Tests ◽  
Correlated Factors ◽  
Sort Algorithm

AbstractWider dissemination of medical digital video libraries is affected by two correlated factors, resource effective content compression that directly influences its diagnostic credibility. It has been proved that it is possible to meet these contradictory requirements halfway for long-lasting and low motion surgery recordings at compression ratios close to 100 (bronchoscopic procedures were a case study investigated). As the main supporting assumption, it has been accepted that the content can be compressed as far as clinicians are not able to sense a loss of video diagnostic fidelity (a visually lossless compression).Different market codecs were inspected by means of the combined subjective and objective tests toward their usability in medical video libraries. Subjective tests involved a panel of clinicians who had to classify compressed bronchoscopic video content according to its quality under the bubble sort algorithm. For objective tests, two metrics (hybrid vector measure and hosaka Plots) were calculated frame by frame and averaged over a whole sequence.

Implementation of Selection Sort Algorithm in Various Programming Languages

2021 ◽  
Vol 10 (4) ◽  
pp. 2249-2255
Keyword(s):  
Programming Languages ◽  
Data Science ◽  
Efficient Algorithms ◽  
Huge Number ◽  
Running Time ◽  
Fast Running ◽  
Python Language ◽  
Sort Algorithm

Sorting algorithmdeals with the arrangement of alphanumeric data in static order.It plays an important roleinthe field of data science. Selection sort is one ofthe simplest and efficient algorithms which can be applied for the huge number of elements it works likeby giving list of unsorted information, the calculation which breaksintotwo partitions. One section has all the sorted information and another sectionhas all thestaying unsorted information. The calculation rehashes itself, by finding the smallestcomponentinside the rundown of unsorted information and swappingitwith the furthest left component, in the end setting everything straight information.This researchpresents the implementationof selection sort usingC/C++, Python, and Rust and measuredthetime complexity. After experiment,we have collectedtheresults in terms of running time, andanalyzed the outcomes.It was observed that python language hasvery smallamount of line of code, and it also consumesless storage and fast running time then other two languages.

Analisis Kinerja Algoritma Quick Double Merge Sort Paralel Menggunakan openMP

2020 ◽  
Vol 11 (2) ◽  
pp. 95-102
Author(s):  
I Nyoman Aditya Yudiswara ◽  
Abba Suganda
Keyword(s):  
Parallel Algorithms ◽  
The Other ◽  
Sorting Algorithm ◽  
Data Parallelism ◽  
Parallel Sorting ◽  
Sequential Algorithms ◽  
Sorting Algorithms ◽  
Merge Sort ◽  
Sort Algorithm ◽  
Quick Sort

Processor technology currently tends to increase the number of cores more than increasing the clock speed. This development is very useful and becomes an opportunity to improve the performance of sequential algorithms that are only done by one core. This paper discusses the sorting algorithm that is executed in parallel by several logical CPUs or cores using the openMP library. This algorithm is named QDM Sort which is a combination of sequential quick sort algorithm and double merge algorithm. This study uses a data parallelism approach to design parallel algorithms from sequential algorithms. The data used in this study are the data that have not been sorted and also the data that has been sorted is integer type which is stored in advance in a file. The parameter measured to determine the performance of the QDM Sort algorithm is speedup. In a condition where a large amount of data is above 4096 and the number of threads in QDM Sort is the same as the number of logical CPUs, the QDM Sort algorithm has a better speedup compared to the other parallel sorting algorithms discussed in this study. For small amounts of data it is still better to use sequential sorting algorithm.

Bubbling Sort Algorithm Application Based on C Programming Language

2013 ◽  
Vol 380-384 ◽  
pp. 1734-1737
Author(s):  
Xiang Ping Xiao
Keyword(s):  
Programming Language ◽  
Teaching Method ◽  
C Language ◽  
C Programming Language ◽  
Java Language ◽  
C Programming ◽  
Mathematical Thought ◽  
Sort Algorithm ◽  
International Status

As its international status, mastering C programming language is very important, for example the java language, popular and widely used at present, which has all kinds of connections with C programming language. In the C language, the bubbling sort, which has the knowledge of the cycle and array, has been seen as classic examples to explain, and also is used in a variety of computer exams. One important reason is the bubbling sort itself more classic; another is that it is not easy for students to grasp and understand the bubbling sort. This paper will explore a new teaching method--introduction of mathematical thought--to help students to understand and master the bubbling sort.

BigGIS With Hadoop in MapReduce Environment

2019 ◽  
pp. 25-32
Author(s):  
Nada M. Alhakkak
Keyword(s):  
Big Data ◽  
Scheduling Algorithm ◽  
Real Data ◽  
Map Reduce ◽  
Data Types ◽  
Simulated Environment ◽  
Merge Sort ◽  
Data Source ◽  
Sort Algorithm ◽  
And Storage

BigGIS is a new product that resulted from developing GIS in the “Big Data” area, which is used in storing and processing big geographical data and helps in solving its issues. This chapter describes an optimized Big GIS framework in Map Reduce Environment M2BG. The suggested framework has been integrated into Map Reduce Environment in order to solve the storage issues and get the benefit of the Hadoop environment. M2BG include two steps: Big GIS warehouse and Big GIS Map Reduce. The first step contains three main layers: Data Source and Storage Layer (DSSL), Data Processing Layer (DPL), and Data Analysis Layer (DAL). The second layer is responsible for clustering using swarms as inputs for the Hadoop phase. Then it is scheduled in the mapping part with the use of a preempted priority scheduling algorithm; some data types are classified as critical and some others are ordinary data type; the reduce part used, merge sort algorithm M2BG, should solve security and be implemented with real data in the simulated environment and later in the real world.

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