block processing
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2021 ◽  
Vol 95 (9) ◽  
Author(s):  
P. J. G. Teunissen ◽  
L. Massarweh ◽  
S. Verhagen

AbstractIn this contribution, we extend the principle of integer bootstrapping (IB) to a vectorial form (VIB). The mathematical definition of the class of VIB-estimators is introduced together with their pull-in regions and other properties such as probability bounds and success rate approximations. The vectorial formulation allows sequential block-by-block processing of the ambiguities based on a user-chosen partitioning. In this way, flexibility is created, where for specific choices of partitioning, tailored VIB-estimators can be designed. This wide range of possibilities is discussed, supported by numerical simulations and analytical examples. Further guidelines are provided, as well as the possible extension to other classes of estimators.


2021 ◽  
Author(s):  
Koteswara Rao G. ◽  
Subhash Kumawat ◽  
Saidhiraj Amuru ◽  
Kiran Kuchi
Keyword(s):  

2021 ◽  
Vol 15 (4) ◽  
pp. 521-528
Author(s):  
Yuki Takanashi ◽  
Hideki Aoyama ◽  
Song Cheol Won ◽  
◽  

In general, NC programs for machining free-form surfaces using a computer numerical control (CNC) machine tool are generated using a computer-aided manufacturing (CAM) system. The tool paths (CL data) generated by a CAM system are approximated straight-line segments based on tolerance (allowable error). As a result, the tolerance affects the machining accuracy and time. If the tolerance is set to a small value, the lengths of the segments are shortened, and the machining accuracy is improved. The process in which a CNC machine tool reads and analyzes an NC program and controls the motors requires a minimum processing time of an NC program block (block-processing time). Therefore, if the lengths of the approximated straight-line segments are too small, it will be impossible to reach the indicated feed speed, and the machining time will be longer. In this study, by identifying the block-processing time of a CNC controller and deriving the appropriate length of the approximated straight-line segment based on the block-processing time, a CL data creation method that is capable of high-speed and high-accuracy free-form surface machining is proposed. In addition, experimental verification tests of the method are conducted.


2021 ◽  
Author(s):  
Parnasree Chakraborty ◽  
Tharini C

Abstract With rapid development of real-time and dynamic application, Compressive Sensing or Compressed sensing (CS) has been used for medical image and biomedical signal compression in the last decades. The performance of CS based compression is mostly dependent on decoding methods rather than the CS encoding methods used in practice. Many CS encoding and decoding algorithms have been reported in literature. However, the comparative study on performance metrics of CS encoding with block processing and without block processing is not investigated by the researchers so far. This paper proposes block CS based medical images and signals compression technique and the proposed technique is compared with standard CS compression. The proposed algorithm divides the input medical images and signals to blocks and each block is processed parallel to enable faster computation. Three performance indices, i.e., the peak signal to noise ratio (PSNR), reconstruction time (RT) and structural similarity index (SSIM) were tested to observe their changes with respect to compression ratio. The results showed that block CS algorithm had better performance than standard CS based compression. More specifically, the parallel block CS reported the best results than standard CS with respect to less reconstruction time and satisfactory PSNR and SSIM.


2021 ◽  
Vol 1 (1) ◽  
pp. 22-24
Author(s):  
Ashish R. Kale

India is buried under waste stacks as more than 1.50 lakhs ofsolid waste (MT) per day is produced. Worse, nearly 90% of the total volume is collected (135,000 tonnes daily). Almost 15,000 MT of waste remains exposed each day, which leads to a "severe" amount of contamination of some 55 lakh of MT of solid waste disposed of each year in open surface. Just 20% (27 000 tonnes per day) of the total waste collected and 80% (1 08 000 tonnes per day) was disposed of. The remaining 80% is disposed of on site. Progress in the management of solid waste has resulted in materials that replace conventional materials, including bricks, blocks,tiles, aggregates, ceramics, cement, lime, soil, timber and paint. In this research, Eco blocks are generated using waste materials like fly-ash and waste using aggregates of cement and yard. It optimizes materials with various combinations and defines the compression strength of the eco-blocks. Days of 7.71, 5.8 and 9.10 N/mm2 are compressive strengths of 14 and 28. The strength of ecological blocks is equal to or above that of the local company’s regular concrete blocks. The study showed that solid waste can be used for solid block processing. We also analyzed how debris can be recycled to find an alternative to reduce natural resource costs and use.


Author(s):  
Ashish R. Kale ◽  

India is buried under waste stacks as more than 1.50 lakhs ofsolid waste (MT) per day is produced. Worse, nearly 90% of the total volume is collected (135,000 tonnes daily). Almost 15,000 MT of waste remains exposed each day, which leads to a “severe” amount of contamination of some 55 lakh of MT of solid waste disposed of each year in open surface. Just 20% (27 000 tonnes per day) of the total waste collected and 80% (1 08 000 tonnes per day) was disposed of. The remaining 80% is disposed of on site. Progress in the management of solid waste has resulted in materials that replace conventional materials, including bricks, blocks,tiles, aggregates, ceramics, cement, lime, soil, timber and paint. In this research, Eco blocks are generated using waste materials like fly-ash and waste using aggregates of cement and yard. It optimizes materials with various combinations and defines the compression strength of the eco-blocks. Days of 7.71, 5.8 and 9.10 N/mm2 are compressive strengths of 14 and 28. The strength of ecological blocks is equal to or above that of the local company’s regular concrete blocks. The study showed that solid waste can be used for solid block processing. We also analyzed how debris can be recycled to find an alternative to reduce natural resource costs and use


2021 ◽  
Vol 7 ◽  
pp. e352
Author(s):  
David Opeoluwa Oyewola ◽  
Emmanuel Gbenga Dada ◽  
Sanjay Misra ◽  
Robertas Damaševičius

For people in developing countries, cassava is a major source of calories and carbohydrates. However, Cassava Mosaic Disease (CMD) has become a major cause of concern among farmers in sub-Saharan Africa countries, which rely on cassava for both business and local consumption. The article proposes a novel deep residual convolution neural network (DRNN) for CMD detection in cassava leaf images. With the aid of distinct block processing, we can counterbalance the imbalanced image dataset of the cassava diseases and increase the number of images available for training and testing. Moreover, we adjust low contrast using Gamma correction and decorrelation stretching to enhance the color separation of an image with significant band-to-band correlation. Experimental results demonstrate that using a balanced dataset of images increases the accuracy of classification. The proposed DRNN model outperforms the plain convolutional neural network (PCNN) by a significant margin of 9.25% on the Cassava Disease Dataset from Kaggle.


Informatics ◽  
2020 ◽  
Vol 17 (2) ◽  
pp. 7-16
Author(s):  
R. P. Bohush ◽  
I. Yu. Zakharava ◽  
S. V. Ablameyko

In the paper the algorithm for object detection in high resolution images is proposed. The approach uses multiscale image representation followed by block processing with the overlapping value. For each block the object detection with convolutional neural network was performed. Number of pyramid layers is limited by the Convolutional Neural Network layer size and input image resolution. Overlapping blocks splitting to improve the classification and detection accuracy is performed on each layer of pyramid except the highest one. Detected areas are merged into one if they have high overlapping value and the same class. Experimental results for the algorithm are presented in the paper.


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