Computing methods in semiconductor problems

2005 ◽  
pp. 441-466 ◽  
Author(s):  
Martin Reiser
Keyword(s):  
Computing Methods

scholarly journals Semi-automatic liver segmentation based on probabilistic models and anatomical constraints

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Doan Cong Le ◽  
Krisana Chinnasarn ◽  
Jirapa Chansangrat ◽  
Nattawut Keeratibharat ◽  
Paramate Horkaew
Keyword(s):  
Probabilistic Models ◽  
Contextual Information ◽  
Automatic Segmentation ◽  
Anatomical Variations ◽  
Graph Cut ◽  
Computing Methods ◽  
Liver Segmentation ◽  
Seed Point ◽  
Tissue Separation ◽  
Human Interactions

AbstractSegmenting a liver and its peripherals from abdominal computed tomography is a crucial step toward computer aided diagnosis and therapeutic intervention. Despite the recent advances in computing methods, faithfully segmenting the liver has remained a challenging task, due to indefinite boundary, intensity inhomogeneity, and anatomical variations across subjects. In this paper, a semi-automatic segmentation method based on multivariable normal distribution of liver tissues and graph-cut sub-division is presented. Although it is not fully automated, the method minimally involves human interactions. Specifically, it consists of three main stages. Firstly, a subject specific probabilistic model was built from an interior patch, surrounding a seed point specified by the user. Secondly, an iterative assignment of pixel labels was applied to gradually update the probabilistic map of the tissues based on spatio-contextual information. Finally, the graph-cut model was optimized to extract the 3D liver from the image. During post-processing, overly segmented nodal regions due to fuzzy tissue separation were removed, maintaining its correct anatomy by using robust bottleneck detection with adjacent contour constraint. The proposed system was implemented and validated on the MICCAI SLIVER07 dataset. The experimental results were benchmarked against the state-of-the-art methods, based on major clinically relevant metrics. Both visual and numerical assessments reported herein indicated that the proposed system could improve the accuracy and reliability of asymptomatic liver segmentation.

scholarly journals Understanding Natural Disaster Scenes from Mobile Images Using Deep Learning

2021 ◽  
Vol 11 (9) ◽  
pp. 3952
Author(s):  
Shimin Tang ◽  
Zhiqiang Chen
Keyword(s):  
Deep Learning ◽  
Natural Disaster ◽  
Scene Understanding ◽  
Computing Methods ◽  
Classification Model ◽  
Learning Approach ◽  
Learning Models ◽  
Damage Level ◽  
Feature Extractor ◽  
Mobile Imaging

With the ubiquitous use of mobile imaging devices, the collection of perishable disaster-scene data has become unprecedentedly easy. However, computing methods are unable to understand these images with significant complexity and uncertainties. In this paper, the authors investigate the problem of disaster-scene understanding through a deep-learning approach. Two attributes of images are concerned, including hazard types and damage levels. Three deep-learning models are trained, and their performance is assessed. Specifically, the best model for hazard-type prediction has an overall accuracy (OA) of 90.1%, and the best damage-level classification model has an explainable OA of 62.6%, upon which both models adopt the Faster R-CNN architecture with a ResNet50 network as a feature extractor. It is concluded that hazard types are more identifiable than damage levels in disaster-scene images. Insights are revealed, including that damage-level recognition suffers more from inter- and intra-class variations, and the treatment of hazard-agnostic damage leveling further contributes to the underlying uncertainties.

scholarly journals Private and rateless adaptive coded matrix-vector multiplication

2021 ◽  
Vol 2021 (1) ◽  
Author(s):  
Rawad Bitar ◽  
Yuxuan Xing ◽  
Yasaman Keshtkarjahromi ◽  
Venkat Dasari ◽  
Salim El Rouayheb ◽  
...  
Keyword(s):  
Computing Methods ◽  
Erasure Codes ◽  
Time Varying ◽  
New Paradigm ◽  
Matrix Vector Multiplication ◽  
Processing Data ◽  
Computationally Intensive ◽  
Matrix Vector ◽  
Monitoring Devices ◽  
Theoretical Results

AbstractEdge computing is emerging as a new paradigm to allow processing data near the edge of the network, where the data is typically generated and collected. This enables critical computations at the edge in applications such as Internet of Things (IoT), in which an increasing number of devices (sensors, cameras, health monitoring devices, etc.) collect data that needs to be processed through computationally intensive algorithms with stringent reliability, security and latency constraints. Our key tool is the theory of coded computation, which advocates mixing data in computationally intensive tasks by employing erasure codes and offloading these tasks to other devices for computation. Coded computation is recently gaining interest, thanks to its higher reliability, smaller delay, and lower communication costs. In this paper, we develop a private and rateless adaptive coded computation (PRAC) algorithm for distributed matrix-vector multiplication by taking into account (1) the privacy requirements of IoT applications and devices, and (2) the heterogeneous and time-varying resources of edge devices. We show that PRAC outperforms known secure coded computing methods when resources are heterogeneous. We provide theoretical guarantees on the performance of PRAC and its comparison to baselines. Moreover, we confirm our theoretical results through simulations and implementations on Android-based smartphones.

scholarly journals Evaluation of several soft computing methods in monthly evapotranspiration modelling

2017 ◽  
Vol 25 (1) ◽  
pp. 128-138 ◽  
Author(s):  
Siavash Gavili ◽  
Hadi Sanikhani ◽  
Ozgur Kisi ◽  
Mohammad Hasan Mahmoudi
Keyword(s):  
Soft Computing ◽  
Computing Methods ◽  
Soft Computing Methods

Research on the Pressure-Measuring Uncertainty of Standard Internal Crusher Gauge

2013 ◽  
Vol 300-301 ◽  
pp. 874-881
Author(s):  
Chuan Rong Zhao ◽  
De Ren Kong ◽  
Fang Wang ◽  
Li Xia Yang ◽  
Li Ping Li
Keyword(s):  
Theoretical Foundation ◽  
Evaluation Model ◽  
Computing Methods ◽  
Selection Methods ◽  
Pressure Source ◽  
True Value ◽  
Individual Character ◽  
Copper Cylinder ◽  
The Individual ◽  
Random Fluctuations

This article introduces the function, the method of selection and related criterion of standard internal crusher gauge, and systematically analyzes three factors that affect the measuring uncertainty of standard internal crusher gauge, including: inconsistency of pressure’s true value from pressure source, the uncertainty imported by standard copper-cylinder and the random fluctuations of the individual character of pressure measuring gauge. According to usage characteristics and selection methods of the standard internal crusher gauge, discusses computing methods of components of the measuring uncertainty and establishes evaluation model for measuring uncertainty of standard internal crusher gauge. The model can quantitatively calculate through experimental data of selection, which lay a theoretical foundation for the control of the pressure measuring uncertainty of standard internal crusher gauge.

scholarly journals CAD Tools and Computing in Architectural and Urban Acoustics

Buildings ◽  
2021 ◽  
Vol 11 (6) ◽  
pp. 235
Author(s):  
Joanna Jablonska ◽  
Roman Czajka
Keyword(s):  
Computer Aided Design ◽  
Three Dimensional ◽  
Computing Methods ◽  
Building Industry ◽  
Two Dimensional ◽  
Cad Tools ◽  
Architectural Acoustics ◽  
Urban Level ◽  
Aided Design ◽  
Three Dimensional Simulations

Contemporary architectural and urban planning aims at optimal development of the environment, including in terms of acoustics. As such, support with computer-aided design (CAD) tools is, nowadays, obligatory. The authors present investigation outcomes of three different CAD and computing methods extracted for the study. The scope covers different scales of considerations from architectural acoustics to the urban level, which relates to the standard architect’s commissions field. The described approaches are applicable for both academics and professionals in the broadly understood building industry There were analysed and synthesized experiences from the use of two-dimensional and three-dimensional simulations, computing based on standardized formulas, and an acoustic meter (here: the SVAN 979 for RT60, LAeq measurement). The article concludes with an assessment, which shows possible uses of methods and confirmations of their usability.

Evaluation of lubricant condition and engine health based on soft computing methods

2021 ◽  
Author(s):  
Mohammad-Reza Pourramezan ◽  
Abbas Rohani ◽  
Nemat Keramat Siavash ◽  
Mohammad Zarein
Keyword(s):  
Soft Computing ◽  
Computing Methods ◽  
Soft Computing Methods
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