A Basic Algorithm of a Target Environment Analyzer

2018 ◽  
Author(s):  
Iakov Korovin ◽  
Maxim Khisamutdinov ◽  
Donat Ivanov
Keyword(s):  
Basic Algorithm ◽  
Target Environment

An Alternate Algorithm for (3x3) Median Filtering of Digital Images

2012 ◽  
Vol 2 (1) ◽  
pp. 7-9 ◽  
Author(s):  
Satinderjit Singh
Keyword(s):  
Median Filter ◽  
Computational Cost ◽  
Spatial Coherence ◽  
General Purpose ◽  
Median Filtering ◽  
Basic Algorithm ◽  
Temporal Complexity ◽  
Filter Kernel ◽  
One Step ◽  
High Computational Cost

Median filtering is a commonly used technique in image processing. The main problem of the median filter is its high computational cost (for sorting N pixels, the temporal complexity is O(N·log N), even with the most efficient sorting algorithms). When the median filter must be carried out in real time, the software implementation in general-purpose processorsdoes not usually give good results. This Paper presents an efficient algorithm for median filtering with a 3x3 filter kernel with only about 9 comparisons per pixel using spatial coherence between neighboring filter computations. The basic algorithm calculates two medians in one step and reuses sorted slices of three vertical neighboring pixels. An extension of this algorithm for 2D spatial coherence is also examined, which calculates four medians per step.

New Algorithm for Modeling of Bronchial Trees

2012 ◽  
Vol 17 (4) ◽  
pp. 179-190
Author(s):  
Kacper Pluta ◽  
Marcin Janaszewski ◽  
Michał Postolski
Keyword(s):  
Quantitative Analysis ◽  
3D Model ◽  
Ct Images ◽  
Basic Algorithm ◽  
New Model ◽  
Comparison Of Results ◽  
Basic Model ◽  
New Models ◽  
Bronchial Tubes

Abstract The article presents new conception of 3D model of human bronchial tubes, which represents bronchial tubes extracted from CT images of the chest. The new algorithm which generates new model is an extension of the algorithm (basic algorithm) proposed by Hiroko Kitaoka, Ryuji Takaki and Bela Suki. The basic model has been extended by geometric deformations of branches and noise which occur in bronchial trees extracted from CT images. The article presents comparison of results obtained with the use of the new algorithm and the basic one. Moreover, the discussion of usefulness of generated new models for testing of algorithms for quantitative analysis of bronchial tubes based on CT images is also included.

scholarly journals Bridging Ride and Play Comfort

Information ◽  
2021 ◽  
Vol 12 (3) ◽  
pp. 119
Author(s):  
Zeliang Zhang ◽  
Kang Xiaohan ◽  
Mohd Nor Akmal Khalid ◽  
Hiroyuki Iida
Keyword(s):  
Physical Performance ◽  
Ride Comfort ◽  
Roller Coaster ◽  
Mental Experience ◽  
The Law ◽  
Target Environment ◽  
Rider Comfort ◽  
The Relationship ◽  
Suitable Environment ◽  
The Way

The notion of comfort with respect to rides, such as roller coasters, is typically addressed from the perspective of a physical ride, where the convenience of transportation is redefined to minimize risk and maximize thrill. As a popular form of entertainment, roller coasters sit at the nexus of rides and games, providing a suitable environment to measure both mental and physical experiences of rider comfort. In this paper, the way risk and comfort affect such experiences is investigated, and the connection between play comfort and ride comfort is explored. A roller coaster ride simulation is adopted as the target environment for this research, which combines the feeling of being thrill and comfort simultaneously. At the same time, this paper also expands research on roller coaster rides while bridging the rides and games via the analogy of the law of physics, a concept currently known as motion in mind. This study’s contribution involves a roller coaster ride model, which provides an extended understanding of the relationship between physical performance and the mental experience relative to the concept of motion in mind while establishing critical criteria for a comfortable experience of both the ride and play.

scholarly journals Deep Q-Learning for Two-Hop Communications of Drone Base Stations

Sensors ◽  
2021 ◽  
Vol 21 (6) ◽  
pp. 1960
Author(s):  
Azade Fotouhi ◽  
Ming Ding ◽  
Mahbub Hassan
Keyword(s):  
Degrees Of Freedom ◽  
Network Performance ◽  
Learning Model ◽  
Base Stations ◽  
Communication Model ◽  
Complex Environments ◽  
End User ◽  
Q Learning ◽  
Trajectory Simulation ◽  
Target Environment

In this paper, we address the application of the flying Drone Base Stations (DBS) in order to improve the network performance. Given the high degrees of freedom of a DBS, it can change its position and adapt its trajectory according to the users movements and the target environment. A two-hop communication model, between an end-user and a macrocell through a DBS, is studied in this work. We propose Q-learning and Deep Q-learning based solutions to optimize the drone’s trajectory. Simulation results show that, by employing our proposed models, the drone can autonomously fly and adapts its mobility according to the users’ movements. Additionally, the Deep Q-learning model outperforms the Q-learning model and can be applied in more complex environments.

Genomic composition of 4x–2x potato hybrids: influence of Solanum chacoense

Genome ◽  
1991 ◽  
Vol 34 (3) ◽  
pp. 413-420 ◽  
Author(s):  
Fouzia Bani-Aameur ◽  
F. I. Lauer ◽  
R. E. Veilleux ◽  
A. Hilali
Keyword(s):  
Solanum Tuberosum ◽  
Interspecific Hybrids ◽  
Tuber Yield ◽  
Solanum Chacoense ◽  
Solanum Phureja ◽  
2N Pollen ◽  
Fall Season ◽  
Tuber Set ◽  
Target Environment ◽  
Breeding Selections

Tetraploid potato hybrids representing three genomic compositions (TTTT, TTPP, and TTPC (T, Solanum tuberosum; P, Solanum phureja; C, Solanum chacoense)) were constructed by crossing S. tuberosum (2n = 4x = 48) cultivars or advanced breeding selections among themselves or with 2n pollen producing selections of either S. phureja (2n = 2x = 24) or F1 hybrids between S. phureja and S. chacoense (2n = 2x = 24). Seedling families were evaluated in the fall season and selections within each family were evaluated in spring trials at Ait-Melloul, Morocco. Genomic composition was the greatest source of variance for yield-attributing traits, with TTPC outperforming other hybrids in fall trials for vine vigor, tuber set, and tuber yield and TTPP outperforming other hybrids in spring trials for the same traits. The results imply that analytic breeding for potato by construction of complex interspecific hybrids may result in clones surpassing a previously proposed heterotic threshold if the target environment is conducive to expression of favorable traits from alien germ plasm.Key words: Solanum phureja, Solanum chacoense, Solanum tuberosum, 4x–2x hybrids, potato, analytic breeding.

Estimation of the Automated Video Control Device’s Target Functions Performance Probability

2021 ◽  
Vol 26 (3-4) ◽  
pp. 291-301
Author(s):  
N.V. Stepanov ◽  
Keyword(s):  
Estimation Method ◽  
Target Function ◽  
Video Camera ◽  
Optimal Receiver ◽  
Efficiency Estimation ◽  
Use Efficiency ◽  
Target Environment ◽  
Receiver Model ◽  
Video Control

Operating quality of automated video control systems depends on optical specifications of video camera and peculiar features of video algorithm. Specified target function performance probability can serve as criterion of automated video control use efficiency. In this work, a new performance efficiency estimation method for automated equipment of target environment video control is suggested: to estimate the probability of target functions’ (object detection, capture, and auto tracking) performance. Theoretical prediction of target functions performance probability was built upon Johnson’s criterion and the use of optimal receiver model. The results of suggested method’s experimental verification have shown that target detection occurred when signal/noise ratio level was above 6. This level can be regarded as low value to ensure that object is detected with probability 0.9.

Description of basic algorithm DETAB/65 preprocessor

1967 ◽  
Vol 10 (7) ◽  
pp. 441-446 ◽  
Author(s):  
Michael D. Callahan ◽  
Anson E. Chapman
Keyword(s):  
Basic Algorithm
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