Developing a multimodal biometric authentication system using soft computing methods.
Malcangi, Mario
2015-01-01
Robust personal authentication is becoming ever more important in computer-based applications. Among a variety of methods, biometric offers several advantages, mainly in embedded system applications. Hard and soft multi-biometric, combined with hard and soft computing methods, can be applied to improve the personal authentication process and to generalize the applicability. This chapter describes the embedded implementation of a multi-biometric (voiceprint and fingerprint) multimodal identification system based on hard computing methods (DSP) for feature extraction and matching, an artificial neural network (ANN) for soft feature pattern matching, and a fuzzy logic engine (FLE) for data fusion and decision.
Management of health care expenditure by soft computing methodology
NASA Astrophysics Data System (ADS)
Maksimović, Goran; Jović, Srđan; Jovanović, Radomir; Aničić, Obrad
2017-01-01
In this study was managed the health care expenditure by soft computing methodology. The main goal was to predict the gross domestic product (GDP) according to several factors of health care expenditure. Soft computing methodologies were applied since GDP prediction is very complex task. The performances of the proposed predictors were confirmed with the simulation results. According to the results, support vector regression (SVR) has better prediction accuracy compared to other soft computing methodologies. The soft computing methods benefit from the soft computing capabilities of global optimization in order to avoid local minimum issues.
Water demand forecasting: review of soft computing methods.
Ghalehkhondabi, Iman; Ardjmand, Ehsan; Young, William A; Weckman, Gary R
2017-07-01
Demand forecasting plays a vital role in resource management for governments and private companies. Considering the scarcity of water and its inherent constraints, demand management and forecasting in this domain are critically important. Several soft computing techniques have been developed over the last few decades for water demand forecasting. This study focuses on soft computing methods of water consumption forecasting published between 2005 and 2015. These methods include artificial neural networks (ANNs), fuzzy and neuro-fuzzy models, support vector machines, metaheuristics, and system dynamics. Furthermore, it was discussed that while in short-term forecasting, ANNs have been superior in many cases, but it is still very difficult to pick a single method as the overall best. According to the literature, various methods and their hybrids are applied to water demand forecasting. However, it seems soft computing has a lot more to contribute to water demand forecasting. These contribution areas include, but are not limited, to various ANN architectures, unsupervised methods, deep learning, various metaheuristics, and ensemble methods. Moreover, it is found that soft computing methods are mainly used for short-term demand forecasting.
Technical Development and Application of Soft Computing in Agricultural and Biological Engineering
USDA-ARS?s Scientific Manuscript database
Soft computing is a set of “inexact” computing techniques, which are able to model and analyze very complex problems. For these complex problems, more conventional methods have not been able to produce cost-effective, analytical, or complete solutions. Soft computing has been extensively studied and...
Development of Soft Computing and Applications in Agricultural and Biological Engineering
USDA-ARS?s Scientific Manuscript database
Soft computing is a set of “inexact” computing techniques, which are able to model and analyze very complex problems. For these complex problems, more conventional methods have not been able to produce cost-effective, analytical, or complete solutions. Soft computing has been extensively studied and...
Greene, Samuel M; Batista, Victor S
2017-09-12
We introduce the "tensor-train split-operator Fourier transform" (TT-SOFT) method for simulations of multidimensional nonadiabatic quantum dynamics. TT-SOFT is essentially the grid-based SOFT method implemented in dynamically adaptive tensor-train representations. In the same spirit of all matrix product states, the tensor-train format enables the representation, propagation, and computation of observables of multidimensional wave functions in terms of the grid-based wavepacket tensor components, bypassing the need of actually computing the wave function in its full-rank tensor product grid space. We demonstrate the accuracy and efficiency of the TT-SOFT method as applied to propagation of 24-dimensional wave packets, describing the S 1 /S 2 interconversion dynamics of pyrazine after UV photoexcitation to the S 2 state. Our results show that the TT-SOFT method is a powerful computational approach for simulations of quantum dynamics of polyatomic systems since it avoids the exponential scaling problem of full-rank grid-based representations.
Soft tissue deformation estimation by spatio-temporal Kalman filter finite element method.
Yarahmadian, Mehran; Zhong, Yongmin; Gu, Chengfan; Shin, Jaehyun
2018-01-01
Soft tissue modeling plays an important role in the development of surgical training simulators as well as in robot-assisted minimally invasive surgeries. It has been known that while the traditional Finite Element Method (FEM) promises the accurate modeling of soft tissue deformation, it still suffers from a slow computational process. This paper presents a Kalman filter finite element method to model soft tissue deformation in real time without sacrificing the traditional FEM accuracy. The proposed method employs the FEM equilibrium equation and formulates it as a filtering process to estimate soft tissue behavior using real-time measurement data. The model is temporally discretized using the Newmark method and further formulated as the system state equation. Simulation results demonstrate that the computational time of KF-FEM is approximately 10 times shorter than the traditional FEM and it is still as accurate as the traditional FEM. The normalized root-mean-square error of the proposed KF-FEM in reference to the traditional FEM is computed as 0.0116. It is concluded that the proposed method significantly improves the computational performance of the traditional FEM without sacrificing FEM accuracy. The proposed method also filters noises involved in system state and measurement data.
Mesoscopic modelling and simulation of soft matter.
Schiller, Ulf D; Krüger, Timm; Henrich, Oliver
2017-12-20
The deformability of soft condensed matter often requires modelling of hydrodynamical aspects to gain quantitative understanding. This, however, requires specialised methods that can resolve the multiscale nature of soft matter systems. We review a number of the most popular simulation methods that have emerged, such as Langevin dynamics, dissipative particle dynamics, multi-particle collision dynamics, sometimes also referred to as stochastic rotation dynamics, and the lattice-Boltzmann method. We conclude this review with a short glance at current compute architectures for high-performance computing and community codes for soft matter simulation.
Investigating the impact of spatial priors on the performance of model-based IVUS elastography
Richards, M S; Doyley, M M
2012-01-01
This paper describes methods that provide pre-requisite information for computing circumferential stress in modulus elastograms recovered from vascular tissue—information that could help cardiologists detect life-threatening plaques and predict their propensity to rupture. The modulus recovery process is an ill-posed problem; therefore additional information is needed to provide useful elastograms. In this work, prior geometrical information was used to impose hard or soft constraints on the reconstruction process. We conducted simulation and phantom studies to evaluate and compare modulus elastograms computed with soft and hard constraints versus those computed without any prior information. The results revealed that (1) the contrast-to-noise ratio of modulus elastograms achieved using the soft prior and hard prior reconstruction methods exceeded those computed without any prior information; (2) the soft prior and hard prior reconstruction methods could tolerate up to 8 % measurement noise; and (3) the performance of soft and hard prior modulus elastogram degraded when incomplete spatial priors were employed. This work demonstrates that including spatial priors in the reconstruction process should improve the performance of model-based elastography, and the soft prior approach should enhance the robustness of the reconstruction process to errors in the geometrical information. PMID:22037648
A new ChainMail approach for real-time soft tissue simulation.
Zhang, Jinao; Zhong, Yongmin; Smith, Julian; Gu, Chengfan
2016-07-03
This paper presents a new ChainMail method for real-time soft tissue simulation. This method enables the use of different material properties for chain elements to accommodate various materials. Based on the ChainMail bounding region, a new time-saving scheme is developed to improve computational efficiency for isotropic materials. The proposed method also conserves volume and strain energy. Experimental results demonstrate that the proposed ChainMail method can not only accommodate isotropic, anisotropic and heterogeneous materials but also model incompressibility and relaxation behaviors of soft tissues. Further, the proposed method can achieve real-time computational performance.
Simulating Soft Shadows with Graphics Hardware,
1997-01-15
This radiance texture is analogous to the mesh of radiosity values computed in a radiosity algorithm. Unlike a radiosity algorithm, however, our...discretely. Several researchers have explored continuous visibility methods for soft shadow computation and radiosity mesh generation. With this approach...times of several seconds [9]. Most radiosity methods discretize each surface into a mesh of elements and then use discrete methods such as ray
Deformation of Soft Tissue and Force Feedback Using the Smoothed Particle Hydrodynamics
Liu, Xuemei; Wang, Ruiyi; Li, Yunhua; Song, Dongdong
2015-01-01
We study the deformation and haptic feedback of soft tissue in virtual surgery based on a liver model by using a force feedback device named PHANTOM OMNI developed by SensAble Company in USA. Although a significant amount of research efforts have been dedicated to simulating the behaviors of soft tissue and implementing force feedback, it is still a challenging problem. This paper introduces a kind of meshfree method for deformation simulation of soft tissue and force computation based on viscoelastic mechanical model and smoothed particle hydrodynamics (SPH). Firstly, viscoelastic model can present the mechanical characteristics of soft tissue which greatly promotes the realism. Secondly, SPH has features of meshless technique and self-adaption, which supply higher precision than methods based on meshes for force feedback computation. Finally, a SPH method based on dynamic interaction area is proposed to improve the real time performance of simulation. The results reveal that SPH methodology is suitable for simulating soft tissue deformation and force feedback calculation, and SPH based on dynamic local interaction area has a higher computational efficiency significantly compared with usual SPH. Our algorithm has a bright prospect in the area of virtual surgery. PMID:26417380
Local deformation for soft tissue simulation
Omar, Nadzeri; Zhong, Yongmin; Smith, Julian; Gu, Chengfan
2016-01-01
ABSTRACT This paper presents a new methodology to localize the deformation range to improve the computational efficiency for soft tissue simulation. This methodology identifies the local deformation range from the stress distribution in soft tissues due to an external force. A stress estimation method is used based on elastic theory to estimate the stress in soft tissues according to a depth from the contact surface. The proposed methodology can be used with both mass-spring and finite element modeling approaches for soft tissue deformation. Experimental results show that the proposed methodology can improve the computational efficiency while maintaining the modeling realism. PMID:27286482
NASA Astrophysics Data System (ADS)
Bhardwaj, Jyotirmoy; Gupta, Karunesh K.; Gupta, Rajiv
2018-02-01
New concepts and techniques are replacing traditional methods of water quality parameter measurement systems. This paper introduces a cyber-physical system (CPS) approach for water quality assessment in a distribution network. Cyber-physical systems with embedded sensors, processors and actuators can be designed to sense and interact with the water environment. The proposed CPS is comprised of sensing framework integrated with five different water quality parameter sensor nodes and soft computing framework for computational modelling. Soft computing framework utilizes the applications of Python for user interface and fuzzy sciences for decision making. Introduction of multiple sensors in a water distribution network generates a huge number of data matrices, which are sometimes highly complex, difficult to understand and convoluted for effective decision making. Therefore, the proposed system framework also intends to simplify the complexity of obtained sensor data matrices and to support decision making for water engineers through a soft computing framework. The target of this proposed research is to provide a simple and efficient method to identify and detect presence of contamination in a water distribution network using applications of CPS.
Exploiting the Dynamics of Soft Materials for Machine Learning
Hauser, Helmut; Li, Tao; Pfeifer, Rolf
2018-01-01
Abstract Soft materials are increasingly utilized for various purposes in many engineering applications. These materials have been shown to perform a number of functions that were previously difficult to implement using rigid materials. Here, we argue that the diverse dynamics generated by actuating soft materials can be effectively used for machine learning purposes. This is demonstrated using a soft silicone arm through a technique of multiplexing, which enables the rich transient dynamics of the soft materials to be fully exploited as a computational resource. The computational performance of the soft silicone arm is examined through two standard benchmark tasks. Results show that the soft arm compares well to or even outperforms conventional machine learning techniques under multiple conditions. We then demonstrate that this system can be used for the sensory time series prediction problem for the soft arm itself, which suggests its immediate applicability to a real-world machine learning problem. Our approach, on the one hand, represents a radical departure from traditional computational methods, whereas on the other hand, it fits nicely into a more general perspective of computation by way of exploiting the properties of physical materials in the real world. PMID:29708857
Exploiting the Dynamics of Soft Materials for Machine Learning.
Nakajima, Kohei; Hauser, Helmut; Li, Tao; Pfeifer, Rolf
2018-06-01
Soft materials are increasingly utilized for various purposes in many engineering applications. These materials have been shown to perform a number of functions that were previously difficult to implement using rigid materials. Here, we argue that the diverse dynamics generated by actuating soft materials can be effectively used for machine learning purposes. This is demonstrated using a soft silicone arm through a technique of multiplexing, which enables the rich transient dynamics of the soft materials to be fully exploited as a computational resource. The computational performance of the soft silicone arm is examined through two standard benchmark tasks. Results show that the soft arm compares well to or even outperforms conventional machine learning techniques under multiple conditions. We then demonstrate that this system can be used for the sensory time series prediction problem for the soft arm itself, which suggests its immediate applicability to a real-world machine learning problem. Our approach, on the one hand, represents a radical departure from traditional computational methods, whereas on the other hand, it fits nicely into a more general perspective of computation by way of exploiting the properties of physical materials in the real world.
Finite-Element Methods for Real-Time Simulation of Surgery
NASA Technical Reports Server (NTRS)
Basdogan, Cagatay
2003-01-01
Two finite-element methods have been developed for mathematical modeling of the time-dependent behaviors of deformable objects and, more specifically, the mechanical responses of soft tissues and organs in contact with surgical tools. These methods may afford the computational efficiency needed to satisfy the requirement to obtain computational results in real time for simulating surgical procedures as described in Simulation System for Training in Laparoscopic Surgery (NPO-21192) on page 31 in this issue of NASA Tech Briefs. Simulation of the behavior of soft tissue in real time is a challenging problem because of the complexity of soft-tissue mechanics. The responses of soft tissues are characterized by nonlinearities and by spatial inhomogeneities and rate and time dependences of material properties. Finite-element methods seem promising for integrating these characteristics of tissues into computational models of organs, but they demand much central-processing-unit (CPU) time and memory, and the demand increases with the number of nodes and degrees of freedom in a given finite-element model. Hence, as finite-element models become more realistic, it becomes more difficult to compute solutions in real time. In both of the present methods, one uses approximate mathematical models trading some accuracy for computational efficiency and thereby increasing the feasibility of attaining real-time up36 NASA Tech Briefs, October 2003 date rates. The first of these methods is based on modal analysis. In this method, one reduces the number of differential equations by selecting only the most significant vibration modes of an object (typically, a suitable number of the lowest-frequency modes) for computing deformations of the object in response to applied forces.
Web mining in soft computing framework: relevance, state of the art and future directions.
Pal, S K; Talwar, V; Mitra, P
2002-01-01
The paper summarizes the different characteristics of Web data, the basic components of Web mining and its different types, and the current state of the art. The reason for considering Web mining, a separate field from data mining, is explained. The limitations of some of the existing Web mining methods and tools are enunciated, and the significance of soft computing (comprising fuzzy logic (FL), artificial neural networks (ANNs), genetic algorithms (GAs), and rough sets (RSs) are highlighted. A survey of the existing literature on "soft Web mining" is provided along with the commercially available systems. The prospective areas of Web mining where the application of soft computing needs immediate attention are outlined with justification. Scope for future research in developing "soft Web mining" systems is explained. An extensive bibliography is also provided.
Fuzzy logic, neural networks, and soft computing
NASA Technical Reports Server (NTRS)
Zadeh, Lofti A.
1994-01-01
The past few years have witnessed a rapid growth of interest in a cluster of modes of modeling and computation which may be described collectively as soft computing. The distinguishing characteristic of soft computing is that its primary aims are to achieve tractability, robustness, low cost, and high MIQ (machine intelligence quotient) through an exploitation of the tolerance for imprecision and uncertainty. Thus, in soft computing what is usually sought is an approximate solution to a precisely formulated problem or, more typically, an approximate solution to an imprecisely formulated problem. A simple case in point is the problem of parking a car. Generally, humans can park a car rather easily because the final position of the car is not specified exactly. If it were specified to within, say, a few millimeters and a fraction of a degree, it would take hours or days of maneuvering and precise measurements of distance and angular position to solve the problem. What this simple example points to is the fact that, in general, high precision carries a high cost. The challenge, then, is to exploit the tolerance for imprecision by devising methods of computation which lead to an acceptable solution at low cost. By its nature, soft computing is much closer to human reasoning than the traditional modes of computation. At this juncture, the major components of soft computing are fuzzy logic (FL), neural network theory (NN), and probabilistic reasoning techniques (PR), including genetic algorithms, chaos theory, and part of learning theory. Increasingly, these techniques are used in combination to achieve significant improvement in performance and adaptability. Among the important application areas for soft computing are control systems, expert systems, data compression techniques, image processing, and decision support systems. It may be argued that it is soft computing, rather than the traditional hard computing, that should be viewed as the foundation for artificial intelligence. In the years ahead, this may well become a widely held position.
Lautenschlager, Stephan; Bright, Jen A; Rayfield, Emily J
2014-04-01
Gross dissection has a long history as a tool for the study of human or animal soft- and hard-tissue anatomy. However, apart from being a time-consuming and invasive method, dissection is often unsuitable for very small specimens and often cannot capture spatial relationships of the individual soft-tissue structures. The handful of comprehensive studies on avian anatomy using traditional dissection techniques focus nearly exclusively on domestic birds, whereas raptorial birds, and in particular their cranial soft tissues, are essentially absent from the literature. Here, we digitally dissect, identify, and document the soft-tissue anatomy of the Common Buzzard (Buteo buteo) in detail, using the new approach of contrast-enhanced computed tomography using Lugol's iodine. The architecture of different muscle systems (adductor, depressor, ocular, hyoid, neck musculature), neurovascular, and other soft-tissue structures is three-dimensionally visualised and described in unprecedented detail. The three-dimensional model is further presented as an interactive PDF to facilitate the dissemination and accessibility of anatomical data. Due to the digital nature of the data derived from the computed tomography scanning and segmentation processes, these methods hold the potential for further computational analyses beyond descriptive and illustrative proposes. © 2013 The Authors. Journal of Anatomy published by John Wiley & Sons Ltd on behalf of Anatomical Society.
NASA Technical Reports Server (NTRS)
Frank, Andreas O.; Twombly, I. Alexander; Barth, Timothy J.; Smith, Jeffrey D.; Dalton, Bonnie P. (Technical Monitor)
2001-01-01
We have applied the linear elastic finite element method to compute haptic force feedback and domain deformations of soft tissue models for use in virtual reality simulators. Our results show that, for virtual object models of high-resolution 3D data (>10,000 nodes), haptic real time computations (>500 Hz) are not currently possible using traditional methods. Current research efforts are focused in the following areas: 1) efficient implementation of fully adaptive multi-resolution methods and 2) multi-resolution methods with specialized basis functions to capture the singularity at the haptic interface (point loading). To achieve real time computations, we propose parallel processing of a Jacobi preconditioned conjugate gradient method applied to a reduced system of equations resulting from surface domain decomposition. This can effectively be achieved using reconfigurable computing systems such as field programmable gate arrays (FPGA), thereby providing a flexible solution that allows for new FPGA implementations as improved algorithms become available. The resulting soft tissue simulation system would meet NASA Virtual Glovebox requirements and, at the same time, provide a generalized simulation engine for any immersive environment application, such as biomedical/surgical procedures or interactive scientific applications.
Evaluation of Pseudo-Haptic Interactions with Soft Objects in Virtual Environments.
Li, Min; Sareh, Sina; Xu, Guanghua; Ridzuan, Maisarah Binti; Luo, Shan; Xie, Jun; Wurdemann, Helge; Althoefer, Kaspar
2016-01-01
This paper proposes a pseudo-haptic feedback method conveying simulated soft surface stiffness information through a visual interface. The method exploits a combination of two feedback techniques, namely visual feedback of soft surface deformation and control of the indenter avatar speed, to convey stiffness information of a simulated surface of a soft object in virtual environments. The proposed method was effective in distinguishing different sizes of virtual hard nodules integrated into the simulated soft bodies. To further improve the interactive experience, the approach was extended creating a multi-point pseudo-haptic feedback system. A comparison with regards to (a) nodule detection sensitivity and (b) elapsed time as performance indicators in hard nodule detection experiments to a tablet computer incorporating vibration feedback was conducted. The multi-point pseudo-haptic interaction is shown to be more time-efficient than the single-point pseudo-haptic interaction. It is noted that multi-point pseudo-haptic feedback performs similarly well when compared to a vibration-based feedback method based on both performance measures elapsed time and nodule detection sensitivity. This proves that the proposed method can be used to convey detailed haptic information for virtual environmental tasks, even subtle ones, using either a computer mouse or a pressure sensitive device as an input device. This pseudo-haptic feedback method provides an opportunity for low-cost simulation of objects with soft surfaces and hard inclusions, as, for example, occurring in ever more realistic video games with increasing emphasis on interaction with the physical environment and minimally invasive surgery in the form of soft tissue organs with embedded cancer nodules. Hence, the method can be used in many low-budget applications where haptic sensation is required, such as surgeon training or video games, either using desktop computers or portable devices, showing reasonably high fidelity in conveying stiffness perception to the user.
Soft Computing Methods for Disulfide Connectivity Prediction.
Márquez-Chamorro, Alfonso E; Aguilar-Ruiz, Jesús S
2015-01-01
The problem of protein structure prediction (PSP) is one of the main challenges in structural bioinformatics. To tackle this problem, PSP can be divided into several subproblems. One of these subproblems is the prediction of disulfide bonds. The disulfide connectivity prediction problem consists in identifying which nonadjacent cysteines would be cross-linked from all possible candidates. Determining the disulfide bond connectivity between the cysteines of a protein is desirable as a previous step of the 3D PSP, as the protein conformational search space is highly reduced. The most representative soft computing approaches for the disulfide bonds connectivity prediction problem of the last decade are summarized in this paper. Certain aspects, such as the different methodologies based on soft computing approaches (artificial neural network or support vector machine) or features of the algorithms, are used for the classification of these methods.
The soft computing-based approach to investigate allergic diseases: a systematic review.
Tartarisco, Gennaro; Tonacci, Alessandro; Minciullo, Paola Lucia; Billeci, Lucia; Pioggia, Giovanni; Incorvaia, Cristoforo; Gangemi, Sebastiano
2017-01-01
Early recognition of inflammatory markers and their relation to asthma, adverse drug reactions, allergic rhinitis, atopic dermatitis and other allergic diseases is an important goal in allergy. The vast majority of studies in the literature are based on classic statistical methods; however, developments in computational techniques such as soft computing-based approaches hold new promise in this field. The aim of this manuscript is to systematically review the main soft computing-based techniques such as artificial neural networks, support vector machines, bayesian networks and fuzzy logic to investigate their performances in the field of allergic diseases. The review was conducted following PRISMA guidelines and the protocol was registered within PROSPERO database (CRD42016038894). The research was performed on PubMed and ScienceDirect, covering the period starting from September 1, 1990 through April 19, 2016. The review included 27 studies related to allergic diseases and soft computing performances. We observed promising results with an overall accuracy of 86.5%, mainly focused on asthmatic disease. The review reveals that soft computing-based approaches are suitable for big data analysis and can be very powerful, especially when dealing with uncertainty and poorly characterized parameters. Furthermore, they can provide valuable support in case of lack of data and entangled cause-effect relationships, which make it difficult to assess the evolution of disease. Although most works deal with asthma, we believe the soft computing approach could be a real breakthrough and foster new insights into other allergic diseases as well.
Genetic algorithms in teaching artificial intelligence (automated generation of specific algebras)
NASA Astrophysics Data System (ADS)
Habiballa, Hashim; Jendryscik, Radek
2017-11-01
The problem of teaching essential Artificial Intelligence (AI) methods is an important task for an educator in the branch of soft-computing. The key focus is often given to proper understanding of the principle of AI methods in two essential points - why we use soft-computing methods at all and how we apply these methods to generate reasonable results in sensible time. We present one interesting problem solved in the non-educational research concerning automated generation of specific algebras in the huge search space. We emphasize above mentioned points as an educational case study of an interesting problem in automated generation of specific algebras.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Pichierri, Fabio, E-mail: fabio@che.tohoku.ac.jp
Using computational quantum chemistry methods we design novel 2D and 3D soft materials made of cucurbituril macrocycles covalently connected with each other via rigid linkers. Such covalent cucurbituril networks might be useful for the capture of radioactive Cs-137 (present as Cs{sup +}) in the contaminated environment.
Soft computing in design and manufacturing of advanced materials
NASA Technical Reports Server (NTRS)
Cios, Krzysztof J.; Baaklini, George Y; Vary, Alex
1993-01-01
The potential of fuzzy sets and neural networks, often referred to as soft computing, for aiding in all aspects of manufacturing of advanced materials like ceramics is addressed. In design and manufacturing of advanced materials, it is desirable to find which of the many processing variables contribute most to the desired properties of the material. There is also interest in real time quality control of parameters that govern material properties during processing stages. The concepts of fuzzy sets and neural networks are briefly introduced and it is shown how they can be used in the design and manufacturing processes. These two computational methods are alternatives to other methods such as the Taguchi method. The two methods are demonstrated by using data collected at NASA Lewis Research Center. Future research directions are also discussed.
Generating soft shadows with a depth buffer algorithm
NASA Technical Reports Server (NTRS)
Brotman, L. S.; Badler, N. I.
1984-01-01
Computer-synthesized shadows used to appear with a sharp edge when cast onto a surface. At present the production of more realistic, soft shadows is considered. However, significant costs arise in connection with such a representation. The current investigation is concerned with a pragmatic approach, which combines an existing shadowing method with a popular visible surface rendering technique, called a 'depth buffer', to generate soft shadows resulting from light sources of finite extent. The considered method represents an extension of Crow's (1977) shadow volume algorithm.
Soft computing methods in design of superalloys
NASA Technical Reports Server (NTRS)
Cios, K. J.; Berke, L.; Vary, A.; Sharma, S.
1995-01-01
Soft computing techniques of neural networks and genetic algorithms are used in the design of superalloys. The cyclic oxidation attack parameter K(sub a), generated from tests at NASA Lewis Research Center, is modeled as a function of the superalloy chemistry and test temperature using a neural network. This model is then used in conjunction with a genetic algorithm to obtain an optimized superalloy composition resulting in low K(sub a) values.
Soft Computing Methods in Design of Superalloys
NASA Technical Reports Server (NTRS)
Cios, K. J.; Berke, L.; Vary, A.; Sharma, S.
1996-01-01
Soft computing techniques of neural networks and genetic algorithms are used in the design of superalloys. The cyclic oxidation attack parameter K(sub a), generated from tests at NASA Lewis Research Center, is modelled as a function of the superalloy chemistry and test temperature using a neural network. This model is then used in conjunction with a genetic algorithm to obtain an optimized superalloy composition resulting in low K(sub a) values.
Fabrication of low cost soft tissue prostheses with the desktop 3D printer
NASA Astrophysics Data System (ADS)
He, Yong; Xue, Guang-Huai; Fu, Jian-Zhong
2014-11-01
Soft tissue prostheses such as artificial ear, eye and nose are widely used in the maxillofacial rehabilitation. In this report we demonstrate how to fabricate soft prostheses mold with a low cost desktop 3D printer. The fabrication method used is referred to as Scanning Printing Polishing Casting (SPPC). Firstly the anatomy is scanned with a 3D scanner, then a tissue casting mold is designed on computer and printed with a desktop 3D printer. Subsequently, a chemical polishing method is used to polish the casting mold by removing the staircase effect and acquiring a smooth surface. Finally, the last step is to cast medical grade silicone into the mold. After the silicone is cured, the fine soft prostheses can be removed from the mold. Utilizing the SPPC method, soft prostheses with smooth surface and complicated structure can be fabricated at a low cost. Accordingly, the total cost of fabricating ear prosthesis is about $30, which is much lower than the current soft prostheses fabrication methods.
Fabrication of low cost soft tissue prostheses with the desktop 3D printer
He, Yong; Xue, Guang-huai; Fu, Jian-zhong
2014-01-01
Soft tissue prostheses such as artificial ear, eye and nose are widely used in the maxillofacial rehabilitation. In this report we demonstrate how to fabricate soft prostheses mold with a low cost desktop 3D printer. The fabrication method used is referred to as Scanning Printing Polishing Casting (SPPC). Firstly the anatomy is scanned with a 3D scanner, then a tissue casting mold is designed on computer and printed with a desktop 3D printer. Subsequently, a chemical polishing method is used to polish the casting mold by removing the staircase effect and acquiring a smooth surface. Finally, the last step is to cast medical grade silicone into the mold. After the silicone is cured, the fine soft prostheses can be removed from the mold. Utilizing the SPPC method, soft prostheses with smooth surface and complicated structure can be fabricated at a low cost. Accordingly, the total cost of fabricating ear prosthesis is about $30, which is much lower than the current soft prostheses fabrication methods. PMID:25427880
Fabrication of low cost soft tissue prostheses with the desktop 3D printer.
He, Yong; Xue, Guang-huai; Fu, Jian-zhong
2014-11-27
Soft tissue prostheses such as artificial ear, eye and nose are widely used in the maxillofacial rehabilitation. In this report we demonstrate how to fabricate soft prostheses mold with a low cost desktop 3D printer. The fabrication method used is referred to as Scanning Printing Polishing Casting (SPPC). Firstly the anatomy is scanned with a 3D scanner, then a tissue casting mold is designed on computer and printed with a desktop 3D printer. Subsequently, a chemical polishing method is used to polish the casting mold by removing the staircase effect and acquiring a smooth surface. Finally, the last step is to cast medical grade silicone into the mold. After the silicone is cured, the fine soft prostheses can be removed from the mold. Utilizing the SPPC method, soft prostheses with smooth surface and complicated structure can be fabricated at a low cost. Accordingly, the total cost of fabricating ear prosthesis is about $30, which is much lower than the current soft prostheses fabrication methods.
NASA Astrophysics Data System (ADS)
Karagiannis, Georgios Th.
2016-04-01
The development of non-destructive techniques is a reality in the field of conservation science. These techniques are usually not so accurate, as the analytical micro-sampling techniques, however, the proper development of soft-computing techniques can improve their accuracy. In this work, we propose a real-time fast acquisition spectroscopic mapping imaging system that operates from the ultraviolet to mid infrared (UV/Vis/nIR/mIR) area of the electromagnetic spectrum and it is supported by a set of soft-computing methods to identify the materials that exist in a stratigraphic structure of paint layers. Particularly, the system acquires spectra in diffuse-reflectance mode, scanning in a Region-Of-Interest (ROI), and having wavelength range from 200 up to 5000 nm. Also, a fuzzy c-means clustering algorithm, i.e., the particular soft-computing algorithm, produces the mapping images. The evaluation of the method was tested on a byzantine painted icon.
Gharghan, Sadik Kamel; Nordin, Rosdiadee; Ismail, Mahamod
2016-08-06
In this paper, we propose two soft computing localization techniques for wireless sensor networks (WSNs). The two techniques, Neural Fuzzy Inference System (ANFIS) and Artificial Neural Network (ANN), focus on a range-based localization method which relies on the measurement of the received signal strength indicator (RSSI) from the three ZigBee anchor nodes distributed throughout the track cycling field. The soft computing techniques aim to estimate the distance between bicycles moving on the cycle track for outdoor and indoor velodromes. In the first approach the ANFIS was considered, whereas in the second approach the ANN was hybridized individually with three optimization algorithms, namely Particle Swarm Optimization (PSO), Gravitational Search Algorithm (GSA), and Backtracking Search Algorithm (BSA). The results revealed that the hybrid GSA-ANN outperforms the other methods adopted in this paper in terms of accuracy localization and distance estimation accuracy. The hybrid GSA-ANN achieves a mean absolute distance estimation error of 0.02 m and 0.2 m for outdoor and indoor velodromes, respectively.
A Wireless Sensor Network with Soft Computing Localization Techniques for Track Cycling Applications
Gharghan, Sadik Kamel; Nordin, Rosdiadee; Ismail, Mahamod
2016-01-01
In this paper, we propose two soft computing localization techniques for wireless sensor networks (WSNs). The two techniques, Neural Fuzzy Inference System (ANFIS) and Artificial Neural Network (ANN), focus on a range-based localization method which relies on the measurement of the received signal strength indicator (RSSI) from the three ZigBee anchor nodes distributed throughout the track cycling field. The soft computing techniques aim to estimate the distance between bicycles moving on the cycle track for outdoor and indoor velodromes. In the first approach the ANFIS was considered, whereas in the second approach the ANN was hybridized individually with three optimization algorithms, namely Particle Swarm Optimization (PSO), Gravitational Search Algorithm (GSA), and Backtracking Search Algorithm (BSA). The results revealed that the hybrid GSA-ANN outperforms the other methods adopted in this paper in terms of accuracy localization and distance estimation accuracy. The hybrid GSA-ANN achieves a mean absolute distance estimation error of 0.02 m and 0.2 m for outdoor and indoor velodromes, respectively. PMID:27509495
Metzger, Tasha E; Kula, Katherine S; Eckert, George J; Ghoneima, Ahmed A
2013-11-01
Orthodontists rely heavily on soft-tissue analysis to determine facial esthetics and treatment stability. The aim of this retrospective study was to determine the equivalence of soft-tissue measurements between the 3dMD imaging system (3dMD, Atlanta, Ga) and the segmented skin surface images derived from cone-beam computed tomography. Seventy preexisting 3dMD facial photographs and cone-beam computed tomography scans taken within minutes of each other for the same subjects were registered in 3 dimensions and superimposed using Vultus (3dMD) software. After reliability studies, 28 soft-tissue measurements were recorded with both imaging modalities and compared to analyze their equivalence. Intraclass correlation coefficients and Bland-Altman plots were used to assess interexaminer and intraexaminer repeatability and agreement. Summary statistics were calculated for all measurements. To demonstrate equivalence of the 2 methods, the difference needed a 95% confidence interval contained entirely within the equivalence limits defined by the repeatability results. Statistically significant differences were reported for the vermilion height, mouth width, total facial width, mouth symmetry, soft-tissue lip thickness, and eye symmetry. There are areas of nonequivalence between the 2 imaging methods; however, the differences are clinically acceptable from the orthodontic point of view. Copyright © 2013 American Association of Orthodontists. Published by Mosby, Inc. All rights reserved.
Van Hemelen, Geert; Van Genechten, Maarten; Renier, Lieven; Desmedt, Maria; Verbruggen, Elric; Nadjmi, Nasser
2015-07-01
Throughout the history of computing, shortening the gap between the physical and digital world behind the screen has always been strived for. Recent advances in three-dimensional (3D) virtual surgery programs have reduced this gap significantly. Although 3D assisted surgery is now widely available for orthognathic surgery, one might still argue whether a 3D virtual planning approach is a better alternative to a conventional two-dimensional (2D) planning technique. The purpose of this study was to compare the accuracy of a traditional 2D technique and a 3D computer-aided prediction method. A double blind randomised prospective study was performed to compare the prediction accuracy of a traditional 2D planning technique versus a 3D computer-aided planning approach. The accuracy of the hard and soft tissue profile predictions using both planning methods was investigated. There was a statistically significant difference between 2D and 3D soft tissue planning (p < 0.05). The statistically significant difference found between 2D and 3D planning and the actual soft tissue outcome was not confirmed by a statistically significant difference between methods. The 3D planning approach provides more accurate soft tissue planning. However, the 2D orthognathic planning is comparable to 3D planning when it comes to hard tissue planning. This study provides relevant results for choosing between 3D and 2D planning in clinical practice. Copyright © 2015 European Association for Cranio-Maxillo-Facial Surgery. Published by Elsevier Ltd. All rights reserved.
Lim, Ju-Shin; Lee, Jae Woo; Han, Chun; Kwon, Jang-Woo
2018-06-01
Our aim in this study was to analyze whether soft palate length and velum obstruction during sleep are correlated and to determine the effects of related parameters on obstructive sleep apnea syndrome (OSAS) severity. We used computed tomography to measure soft palate length and drug-induced sleep endoscopy (DISE) to evaluate velum obstruction severity. Patients also underwent polysomnography (PSG) for evaluation of OSAS severity. A retrospective cohort of 67 patients with OSAS treated between May 1st, 2013 and July 31st, 2016 was analyzed. Each patient underwent DISE, PSG, and computed tomography. Using DISE, velum obstruction was categorized by the VOTE classification method. Using computed tomography, soft palate length was measured as the length of the posterior nasal spine to the uvula. Correlations of velum obstruction in DISE and PSG parameters (obstructive apnea, hypopnea, apnea hypopnea index (AHI), respiratory effort related arousal (RERA), respiratory disturbance index (RDI), baseline SaO 2 , and minimum SaO 2 ) with soft palate length were also analyzed. Among the 67 patients, the average PNS-U length was 39.90±4.19mm. Length was significantly different by age but not by other demographic characteristics such as sex, past history, or BMI. DISE revealed a statistically significant difference of velum obstruction degree; the cutoff value for PNS-U was 39.47mm. The PSG results, obstructive apnea, AHI, RDI, baseline SaO 2 , and minimum SaO 2 were correlated with PNS-U length, while other results such as hypopnea and RERA showed no correlation. Analysis of soft palate length showed that increased PNS-U length was associated with higher rates of obstructive apnea, AHI, and RDI as assessed by PSG. In contrast, lower baseline SaO 2 and minimum SaO 2 values were seen by PSG; more severe velum obstruction was seen by DISE. We propose that when a soft palate is suspected in OSAS, computed tomography measurement of soft palate length is a valid method for estimating the degree of velum obstruction and the severity of OSAS. Copyright © 2017 Elsevier B.V. All rights reserved.
2017-01-26
Includes procedures for hard surface, soil , and water tests. Discusses vehicle preparation, instrumentation method of computing results, data reduction...and amphibious vehicles. 15. SUBJECT TERMS Bollard pull Soft- soil mobility Drawbar pull Vehicle, amphibious Drawbar horsepower Vehicle...4.3 Drawbar Pull in Soft Soil ................................................. 8 4.4 Amphibious Vehicle Tests (Drawbar Pull in Water and Bollard Pull
Zhou, Jianyong; Luo, Zu; Li, Chunquan; Deng, Mi
2018-01-01
When the meshless method is used to establish the mathematical-mechanical model of human soft tissues, it is necessary to define the space occupied by human tissues as the problem domain and the boundary of the domain as the surface of those tissues. Nodes should be distributed in both the problem domain and on the boundaries. Under external force, the displacement of the node is computed by the meshless method to represent the deformation of biological soft tissues. However, computation by the meshless method consumes too much time, which will affect the simulation of real-time deformation of human tissues in virtual surgery. In this article, the Marquardt's Algorithm is proposed to fit the nodal displacement at the problem domain's boundary and obtain the relationship between surface deformation and force. When different external forces are applied, the deformation of soft tissues can be quickly obtained based on this relationship. The analysis and discussion show that the improved model equations with Marquardt's Algorithm not only can simulate the deformation in real-time but also preserve the authenticity of the deformation model's physical properties. Copyright © 2017 Elsevier B.V. All rights reserved.
Shape-programmable magnetic soft matter
Lum, Guo Zhan; Ye, Zhou; Dong, Xiaoguang; Marvi, Hamid; Erin, Onder; Hu, Wenqi; Sitti, Metin
2016-01-01
Shape-programmable matter is a class of active materials whose geometry can be controlled to potentially achieve mechanical functionalities beyond those of traditional machines. Among these materials, magnetically actuated matter is particularly promising for achieving complex time-varying shapes at small scale (overall dimensions smaller than 1 cm). However, previous work can only program these materials for limited applications, as they rely solely on human intuition to approximate the required magnetization profile and actuating magnetic fields for their materials. Here, we propose a universal programming methodology that can automatically generate the required magnetization profile and actuating fields for soft matter to achieve new time-varying shapes. The universality of the proposed method can therefore inspire a vast number of miniature soft devices that are critical in robotics, smart engineering surfaces and materials, and biomedical devices. Our proposed method includes theoretical formulations, computational strategies, and fabrication procedures for programming magnetic soft matter. The presented theory and computational method are universal for programming 2D or 3D time-varying shapes, whereas the fabrication technique is generic only for creating planar beams. Based on the proposed programming method, we created a jellyfish-like robot, a spermatozoid-like undulating swimmer, and an artificial cilium that could mimic the complex beating patterns of its biological counterpart. PMID:27671658
Shape-programmable magnetic soft matter.
Lum, Guo Zhan; Ye, Zhou; Dong, Xiaoguang; Marvi, Hamid; Erin, Onder; Hu, Wenqi; Sitti, Metin
2016-10-11
Shape-programmable matter is a class of active materials whose geometry can be controlled to potentially achieve mechanical functionalities beyond those of traditional machines. Among these materials, magnetically actuated matter is particularly promising for achieving complex time-varying shapes at small scale (overall dimensions smaller than 1 cm). However, previous work can only program these materials for limited applications, as they rely solely on human intuition to approximate the required magnetization profile and actuating magnetic fields for their materials. Here, we propose a universal programming methodology that can automatically generate the required magnetization profile and actuating fields for soft matter to achieve new time-varying shapes. The universality of the proposed method can therefore inspire a vast number of miniature soft devices that are critical in robotics, smart engineering surfaces and materials, and biomedical devices. Our proposed method includes theoretical formulations, computational strategies, and fabrication procedures for programming magnetic soft matter. The presented theory and computational method are universal for programming 2D or 3D time-varying shapes, whereas the fabrication technique is generic only for creating planar beams. Based on the proposed programming method, we created a jellyfish-like robot, a spermatozoid-like undulating swimmer, and an artificial cilium that could mimic the complex beating patterns of its biological counterpart.
Shape-programmable magnetic soft matter
NASA Astrophysics Data System (ADS)
Zhan Lum, Guo; Ye, Zhou; Dong, Xiaoguang; Marvi, Hamid; Erin, Onder; Hu, Wenqi; Sitti, Metin
2016-10-01
Shape-programmable matter is a class of active materials whose geometry can be controlled to potentially achieve mechanical functionalities beyond those of traditional machines. Among these materials, magnetically actuated matter is particularly promising for achieving complex time-varying shapes at small scale (overall dimensions smaller than 1 cm). However, previous work can only program these materials for limited applications, as they rely solely on human intuition to approximate the required magnetization profile and actuating magnetic fields for their materials. Here, we propose a universal programming methodology that can automatically generate the required magnetization profile and actuating fields for soft matter to achieve new time-varying shapes. The universality of the proposed method can therefore inspire a vast number of miniature soft devices that are critical in robotics, smart engineering surfaces and materials, and biomedical devices. Our proposed method includes theoretical formulations, computational strategies, and fabrication procedures for programming magnetic soft matter. The presented theory and computational method are universal for programming 2D or 3D time-varying shapes, whereas the fabrication technique is generic only for creating planar beams. Based on the proposed programming method, we created a jellyfish-like robot, a spermatozoid-like undulating swimmer, and an artificial cilium that could mimic the complex beating patterns of its biological counterpart.
Sarkar, Kanchan; Sharma, Rahul; Bhattacharyya, S P
2010-03-09
A density matrix based soft-computing solution to the quantum mechanical problem of computing the molecular electronic structure of fairly long polythiophene (PT) chains is proposed. The soft-computing solution is based on a "random mutation hill climbing" scheme which is modified by blending it with a deterministic method based on a trial single-particle density matrix [P((0))(R)] for the guessed structural parameters (R), which is allowed to evolve under a unitary transformation generated by the Hamiltonian H(R). The Hamiltonian itself changes as the geometrical parameters (R) defining the polythiophene chain undergo mutation. The scale (λ) of the transformation is optimized by making the energy [E(λ)] stationary with respect to λ. The robustness and the performance levels of variants of the algorithm are analyzed and compared with those of other derivative free methods. The method is further tested successfully with optimization of the geometry of bipolaron-doped long PT chains.
Results from the First Two Flights of the Static Computer Memory Integrity Testing Experiment
NASA Technical Reports Server (NTRS)
Hancock, Thomas M., III
1999-01-01
This paper details the scientific objectives, experiment design, data collection method, and post flight analysis following the first two flights of the Static Computer Memory Integrity Testing (SCMIT) experiment. SCMIT is designed to detect soft-event upsets in passive magnetic memory. A soft-event upset is a change in the logic state of active or passive forms of magnetic memory, commonly referred to as a "Bitflip". In its mildest form a soft-event upset can cause software exceptions, unexpected events, start spacecraft safeing (ending data collection) or corrupted fault protection and error recovery capabilities. In it's most severe form loss of mission or spacecraft can occur. Analysis after the first flight (in 1991 during STS-40) identified possible soft-event upsets to 25% of the experiment detectors. Post flight analysis after the second flight (in 1997 on STS-87) failed to find any evidence of soft-event upsets. The SCMIT experiment is currently scheduled for a third flight in December 1999 on STS-101.
Dynamic deformation of soft soil media: Experimental studies and mathematical modeling
NASA Astrophysics Data System (ADS)
Balandin, V. V.; Bragov, A. M.; Igumnov, L. A.; Konstantinov, A. Yu.; Kotov, V. L.; Lomunov, A. K.
2015-05-01
A complex experimental-theoretical approach to studying the problem of high-rate strain of soft soil media is presented. This approach combines the following contemporary methods of dynamical tests: the modified Hopkinson-Kolsky method applied tomedium specimens contained in holders and the method of plane wave shock experiments. The following dynamic characteristics of sand soils are obtained: shock adiabatic curves, bulk compressibility curves, and shear resistance curves. The obtained experimental data are used to study the high-rate strain process in the system of a split pressure bar, and the constitutive relations of Grigoryan's mathematical model of soft soil medium are verified by comparing the results of computational and natural test experiments of impact and penetration.
Amiri, Shahram; Wilson, David R.
2012-01-01
Bicruciate retaining knee arthroplasty, although has shown improved functions and patient satisfaction compared to other designs of total knee replacement, remains a technically demanding option for treating severe cases of arthritic knees. One of the main challenges in bicruciate retaining arthroplasty is proper balancing of the soft tissue during the surgery. In this study biomechanics of soft tissue balancing was investigated using a validated computational model of the knee joint with high fidelity definitions of the soft tissue structures along with a Taguchi method for design of experiments. The model was used to simulate intraoperative balancing of soft tissue structures following the combinations suggested by an orthogonal array design. The results were used to quantify the corresponding effects on the laxity of the joint under anterior-posterior, internal-external, and varus-valgus loads. These effects were ranked for each ligament bundle to identify the components of laxity which were most sensitive to the corresponding surgical modifications. The resulting map of sensitivity for all the ligament bundles determined the components of laxity most suitable for examination during intraoperative balancing of the soft tissue. Ultimately, a sequence for intraoperative soft tissue balancing was suggested for a bicruciate retaining knee arthroplasty. PMID:23082090
Advanced soft computing diagnosis method for tumour grading.
Papageorgiou, E I; Spyridonos, P P; Stylios, C D; Ravazoula, P; Groumpos, P P; Nikiforidis, G N
2006-01-01
To develop an advanced diagnostic method for urinary bladder tumour grading. A novel soft computing modelling methodology based on the augmentation of fuzzy cognitive maps (FCMs) with the unsupervised active Hebbian learning (AHL) algorithm is applied. One hundred and twenty-eight cases of urinary bladder cancer were retrieved from the archives of the Department of Histopathology, University Hospital of Patras, Greece. All tumours had been characterized according to the classical World Health Organization (WHO) grading system. To design the FCM model for tumour grading, three experts histopathologists defined the main histopathological features (concepts) and their impact on grade characterization. The resulted FCM model consisted of nine concepts. Eight concepts represented the main histopathological features for tumour grading. The ninth concept represented the tumour grade. To increase the classification ability of the FCM model, the AHL algorithm was applied to adjust the weights of the FCM. The proposed FCM grading model achieved a classification accuracy of 72.5%, 74.42% and 95.55% for tumours of grades I, II and III, respectively. An advanced computerized method to support tumour grade diagnosis decision was proposed and developed. The novelty of the method is based on employing the soft computing method of FCMs to represent specialized knowledge on histopathology and on augmenting FCMs ability using an unsupervised learning algorithm, the AHL. The proposed method performs with reasonably high accuracy compared to other existing methods and at the same time meets the physicians' requirements for transparency and explicability.
Virtopsy: postmortem imaging of laryngeal foreign bodies.
Oesterhelweg, Lars; Bolliger, Stephan A; Thali, Michael J; Ross, Steffen
2009-05-01
Death from corpora aliena in the larynx is a well-known entity in forensic pathology. The correct diagnosis of this cause of death is difficult without an autopsy, and misdiagnoses by external examination alone are common. To determine the postmortem usefulness of modern imaging techniques in the diagnosis of foreign bodies in the larynx, multislice computed tomography, magnetic resonance imaging, and postmortem full-body computed tomography-angiography were performed. Three decedents with a suspected foreign body in the larynx underwent the 3 different imaging techniques before medicolegal autopsy. Multislice computed tomography has a high diagnostic value in the noninvasive localization of a foreign body and abnormalities in the larynx. The differentiation between neoplasm or soft foreign bodies (eg, food) is possible, but difficult, by unenhanced multislice computed tomography. By magnetic resonance imaging, the discrimination of the soft tissue structures and soft foreign bodies is much easier. In addition to the postmortem multislice computed tomography, the combination with postmortem angiography will increase the diagnostic value. Postmortem, cross-sectional imaging methods are highly valuable procedures for the noninvasive detection of corpora aliena in the larynx.
Role of Soft Computing Approaches in HealthCare Domain: A Mini Review.
Gambhir, Shalini; Malik, Sanjay Kumar; Kumar, Yugal
2016-12-01
In the present era, soft computing approaches play a vital role in solving the different kinds of problems and provide promising solutions. Due to popularity of soft computing approaches, these approaches have also been applied in healthcare data for effectively diagnosing the diseases and obtaining better results in comparison to traditional approaches. Soft computing approaches have the ability to adapt itself according to problem domain. Another aspect is a good balance between exploration and exploitation processes. These aspects make soft computing approaches more powerful, reliable and efficient. The above mentioned characteristics make the soft computing approaches more suitable and competent for health care data. The first objective of this review paper is to identify the various soft computing approaches which are used for diagnosing and predicting the diseases. Second objective is to identify various diseases for which these approaches are applied. Third objective is to categories the soft computing approaches for clinical support system. In literature, it is found that large number of soft computing approaches have been applied for effectively diagnosing and predicting the diseases from healthcare data. Some of these are particle swarm optimization, genetic algorithm, artificial neural network, support vector machine etc. A detailed discussion on these approaches are presented in literature section. This work summarizes various soft computing approaches used in healthcare domain in last one decade. These approaches are categorized in five different categories based on the methodology, these are classification model based system, expert system, fuzzy and neuro fuzzy system, rule based system and case based system. Lot of techniques are discussed in above mentioned categories and all discussed techniques are summarized in the form of tables also. This work also focuses on accuracy rate of soft computing technique and tabular information is provided for each category including author details, technique, disease and utility/accuracy.
ChainMail based neural dynamics modeling of soft tissue deformation for surgical simulation.
Zhang, Jinao; Zhong, Yongmin; Smith, Julian; Gu, Chengfan
2017-07-20
Realistic and real-time modeling and simulation of soft tissue deformation is a fundamental research issue in the field of surgical simulation. In this paper, a novel cellular neural network approach is presented for modeling and simulation of soft tissue deformation by combining neural dynamics of cellular neural network with ChainMail mechanism. The proposed method formulates the problem of elastic deformation into cellular neural network activities to avoid the complex computation of elasticity. The local position adjustments of ChainMail are incorporated into the cellular neural network as the local connectivity of cells, through which the dynamic behaviors of soft tissue deformation are transformed into the neural dynamics of cellular neural network. Experiments demonstrate that the proposed neural network approach is capable of modeling the soft tissues' nonlinear deformation and typical mechanical behaviors. The proposed method not only improves ChainMail's linear deformation with the nonlinear characteristics of neural dynamics but also enables the cellular neural network to follow the principle of continuum mechanics to simulate soft tissue deformation.
SoftLab: A Soft-Computing Software for Experimental Research with Commercialization Aspects
NASA Technical Reports Server (NTRS)
Akbarzadeh-T, M.-R.; Shaikh, T. S.; Ren, J.; Hubbell, Rob; Kumbla, K. K.; Jamshidi, M
1998-01-01
SoftLab is a software environment for research and development in intelligent modeling/control using soft-computing paradigms such as fuzzy logic, neural networks, genetic algorithms, and genetic programs. SoftLab addresses the inadequacies of the existing soft-computing software by supporting comprehensive multidisciplinary functionalities from management tools to engineering systems. Furthermore, the built-in features help the user process/analyze information more efficiently by a friendly yet powerful interface, and will allow the user to specify user-specific processing modules, hence adding to the standard configuration of the software environment.
NASA Astrophysics Data System (ADS)
Yilmaz, Işik; Marschalko, Marian; Bednarik, Martin
2013-04-01
The paper presented herein compares and discusses the use of bivariate, multivariate and soft computing techniques for collapse susceptibility modelling. Conditional probability (CP), logistic regression (LR) and artificial neural networks (ANN) models representing the bivariate, multivariate and soft computing techniques were used in GIS based collapse susceptibility mapping in an area from Sivas basin (Turkey). Collapse-related factors, directly or indirectly related to the causes of collapse occurrence, such as distance from faults, slope angle and aspect, topographical elevation, distance from drainage, topographic wetness index (TWI), stream power index (SPI), Normalized Difference Vegetation Index (NDVI) by means of vegetation cover, distance from roads and settlements were used in the collapse susceptibility analyses. In the last stage of the analyses, collapse susceptibility maps were produced from the models, and they were then compared by means of their validations. However, Area Under Curve (AUC) values obtained from all three models showed that the map obtained from soft computing (ANN) model looks like more accurate than the other models, accuracies of all three models can be evaluated relatively similar. The results also showed that the conditional probability is an essential method in preparation of collapse susceptibility map and highly compatible with GIS operating features.
NASA Astrophysics Data System (ADS)
Tahavvor, Ali Reza
2017-03-01
In the present study artificial neural network and fractal geometry are used to predict frost thickness and density on a cold flat plate having constant surface temperature under forced convection for different ambient conditions. These methods are very applicable in this area because phase changes such as melting and solidification are simulated by conventional methods but frost formation is a most complicated phase change phenomenon consists of coupled heat and mass transfer. Therefore conventional mathematical techniques cannot capture the effects of all parameters on its growth and development because this process influenced by many factors and it is a time dependent process. Therefore, in this work soft computing method such as artificial neural network and fractal geometry are used to do this manner. The databases for modeling are generated from the experimental measurements. First, multilayer perceptron network is used and it is found that the back-propagation algorithm with Levenberg-Marquardt learning rule is the best choice to estimate frost growth properties due to accurate and faster training procedure. Second, fractal geometry based on the Von-Koch curve is used to model frost growth procedure especially in frost thickness and density. Comparison is performed between experimental measurements and soft computing methods. Results show that soft computing methods can be used more efficiently to determine frost properties over a flat plate. Based on the developed models, wide range of frost formation over flat plates can be determined for various conditions.
Soft Expansion of Double-Real-Virtual Corrections to Higgs Production at N$^3$LO
Anastasiou, Charalampos; Duhr, Claude; Dulat, Falko; ...
2015-05-15
We present methods to compute higher orders in the threshold expansion for the one-loop production of a Higgs boson in association with two partons at hadron colliders. This process contributes to the N 3LO Higgs production cross section beyond the soft-virtual approximation. We use reverse unitarity to expand the phase-space integrals in the small kinematic parameters and to reduce the coefficients of the expansion to a small set of master integrals. We describe two methods for the calculation of the master integrals. The first was introduced for the calculation of the soft triple-real radiation relevant to N 3LO Higgs production.more » The second uses a particular factorization of the three body phase-space measure and the knowledge of the scaling properties of the integral itself. Our result is presented as a Laurent expansion in the dimensional regulator, although some of the master integrals are computed to all orders in this parameter.« less
Nguyen, Vu-Hieu; Tran, Tho N H T; Sacchi, Mauricio D; Naili, Salah; Le, Lawrence H
2017-08-01
We present a semi-analytical finite element (SAFE) scheme for accurately computing the velocity dispersion and attenuation in a trilayered system consisting of a transversely-isotropic (TI) cortical bone plate sandwiched between the soft tissue and marrow layers. The soft tissue and marrow are mimicked by two fluid layers of finite thickness. A Kelvin-Voigt model accounts for the absorption of all three biological domains. The simulated dispersion curves are validated by the results from the commercial software DISPERSE and published literature. Finally, the algorithm is applied to a viscoelastic trilayered TI bone model to interpret the guided modes of an ex-vivo experimental data set from a bone phantom. Copyright © 2017 Elsevier Ltd. All rights reserved.
New-Sum: A Novel Online ABFT Scheme For General Iterative Methods
DOE Office of Scientific and Technical Information (OSTI.GOV)
Tao, Dingwen; Song, Shuaiwen; Krishnamoorthy, Sriram
Emerging high-performance computing platforms, with large component counts and lower power margins, are anticipated to be more susceptible to soft errors in both logic circuits and memory subsystems. We present an online algorithm-based fault tolerance (ABFT) approach to efficiently detect and recover soft errors for general iterative methods. We design a novel checksum-based encoding scheme for matrix-vector multiplication that is resilient to both arithmetic and memory errors. Our design decouples the checksum updating process from the actual computation, and allows adaptive checksum overhead control. Building on this new encoding mechanism, we propose two online ABFT designs that can effectively recovermore » from errors when combined with a checkpoint/rollback scheme.« less
Rough set soft computing cancer classification and network: one stone, two birds.
Zhang, Yue
2010-07-15
Gene expression profiling provides tremendous information to help unravel the complexity of cancer. The selection of the most informative genes from huge noise for cancer classification has taken centre stage, along with predicting the function of such identified genes and the construction of direct gene regulatory networks at different system levels with a tuneable parameter. A new study by Wang and Gotoh described a novel Variable Precision Rough Sets-rooted robust soft computing method to successfully address these problems and has yielded some new insights. The significance of this progress and its perspectives will be discussed in this article.
Gebremariam, Mekdes K.; Chinapaw, Mai J.; Bringolf-Isler, Bettina; Bere, Elling; Kovacs, Eva; Verloigne, Maïté; Stok, F. Marijn; Manios, Yannis; Brug, Johannes; Lien, Nanna
2017-01-01
Aim The aim of the present study was to explore if children who spend more time on screen-based sedentary behaviors (i.e.TV viewing and computer use) drink more sugar-sweetened soft drinks. The study also assessed whether these associations were independent of individual and home environmental correlates of soft drink consumption and whether they were moderated by parental education. Methods Data were collected from 7886 children participating in the EuropeaN Energy balance Research to prevent excessive weight Gain among Youth (ENERGY) survey conducted in eight European countries. Self-report questionnaires were used. Multilevel linear regression analyses with soft drink consumption as dependent variable, TV viewing and computer use as independent variables and age, gender, parental education, attitude towards soft drinks, self-efficacy, parental modelling, parental rules and home availability of soft drinks as covariates were conducted. Further interactions were tested to explore if these associations were moderated by parental education. Country-specific analyses were conducted. Results In six of the eight included countries, a significant positive association was observed between TV viewing (min/day) and soft drink consumption (ml/day), independent of individual and home environmental correlates of soft drink consumption (B = 0.46 (0.26–0.66) in Greece, B = 0.77 (0.36–1.17) in Norway, B = 0.82 (0.12–1.51) in Hungary, B = 1.06 (0.67–1.46) in Spain, B = 1.21 (0.67–1.74) in Belgium and B = 1.49 (0.72–2.27) in Switzerland). There was no significant association between computer use and soft drink consumption in six of the eight included countries in the final models. Moderation effects of parental education in the association between TV viewing and soft drink consumption were found in Norway and Hungary, the association being stronger among those with low parental education. Conclusions TV viewing appears to be independently associated with soft drink consumption and this association was moderated by parental education in two countries only. Reducing TV time might therefore favorably impact soft drink consumption. PMID:28182671
Support vector machine firefly algorithm based optimization of lens system.
Shamshirband, Shahaboddin; Petković, Dalibor; Pavlović, Nenad T; Ch, Sudheer; Altameem, Torki A; Gani, Abdullah
2015-01-01
Lens system design is an important factor in image quality. The main aspect of the lens system design methodology is the optimization procedure. Since optimization is a complex, nonlinear task, soft computing optimization algorithms can be used. There are many tools that can be employed to measure optical performance, but the spot diagram is the most useful. The spot diagram gives an indication of the image of a point object. In this paper, the spot size radius is considered an optimization criterion. Intelligent soft computing scheme support vector machines (SVMs) coupled with the firefly algorithm (FFA) are implemented. The performance of the proposed estimators is confirmed with the simulation results. The result of the proposed SVM-FFA model has been compared with support vector regression (SVR), artificial neural networks, and generic programming methods. The results show that the SVM-FFA model performs more accurately than the other methodologies. Therefore, SVM-FFA can be used as an efficient soft computing technique in the optimization of lens system designs.
Putzer, David; Klug, Sebastian; Moctezuma, Jose Luis; Nogler, Michael
2014-12-01
Time-of-flight (TOF) cameras can guide surgical robots or provide soft tissue information for augmented reality in the medical field. In this study, a method to automatically track the soft tissue envelope of a minimally invasive hip approach in a cadaver study is described. An algorithm for the TOF camera was developed and 30 measurements on 8 surgical situs (direct anterior approach) were carried out. The results were compared to a manual measurement of the soft tissue envelope. The TOF camera showed an overall recognition rate of the soft tissue envelope of 75%. On comparing the results from the algorithm with the manual measurements, a significant difference was found (P > .005). In this preliminary study, we have presented a method for automatically recognizing the soft tissue envelope of the surgical field in a real-time application. Further improvements could result in a robotic navigation device for minimally invasive hip surgery. © The Author(s) 2014.
A Stochastic-Variational Model for Soft Mumford-Shah Segmentation
2006-01-01
In contemporary image and vision analysis, stochastic approaches demonstrate great flexibility in representing and modeling complex phenomena, while variational-PDE methods gain enormous computational advantages over Monte Carlo or other stochastic algorithms. In combination, the two can lead to much more powerful novel models and efficient algorithms. In the current work, we propose a stochastic-variational model for soft (or fuzzy) Mumford-Shah segmentation of mixture image patterns. Unlike the classical hard Mumford-Shah segmentation, the new model allows each pixel to belong to each image pattern with some probability. Soft segmentation could lead to hard segmentation, and hence is more general. The modeling procedure, mathematical analysis on the existence of optimal solutions, and computational implementation of the new model are explored in detail, and numerical examples of both synthetic and natural images are presented. PMID:23165059
Estimation of the laser cutting operating cost by support vector regression methodology
NASA Astrophysics Data System (ADS)
Jović, Srđan; Radović, Aleksandar; Šarkoćević, Živče; Petković, Dalibor; Alizamir, Meysam
2016-09-01
Laser cutting is a popular manufacturing process utilized to cut various types of materials economically. The operating cost is affected by laser power, cutting speed, assist gas pressure, nozzle diameter and focus point position as well as the workpiece material. In this article, the process factors investigated were: laser power, cutting speed, air pressure and focal point position. The aim of this work is to relate the operating cost to the process parameters mentioned above. CO2 laser cutting of stainless steel of medical grade AISI316L has been investigated. The main goal was to analyze the operating cost through the laser power, cutting speed, air pressure, focal point position and material thickness. Since the laser operating cost is a complex, non-linear task, soft computing optimization algorithms can be used. Intelligent soft computing scheme support vector regression (SVR) was implemented. The performance of the proposed estimator was confirmed with the simulation results. The SVR results are then compared with artificial neural network and genetic programing. According to the results, a greater improvement in estimation accuracy can be achieved through the SVR compared to other soft computing methodologies. The new optimization methods benefit from the soft computing capabilities of global optimization and multiobjective optimization rather than choosing a starting point by trial and error and combining multiple criteria into a single criterion.
Random Weighting, Strong Tracking, and Unscented Kalman Filter for Soft Tissue Characterization.
Shin, Jaehyun; Zhong, Yongmin; Oetomo, Denny; Gu, Chengfan
2018-05-21
This paper presents a new nonlinear filtering method based on the Hunt-Crossley model for online nonlinear soft tissue characterization. This method overcomes the problem of performance degradation in the unscented Kalman filter due to contact model error. It adopts the concept of Mahalanobis distance to identify contact model error, and further incorporates a scaling factor in predicted state covariance to compensate identified model error. This scaling factor is determined according to the principle of innovation orthogonality to avoid the cumbersome computation of Jacobian matrix, where the random weighting concept is adopted to improve the estimation accuracy of innovation covariance. A master-slave robotic indentation system is developed to validate the performance of the proposed method. Simulation and experimental results as well as comparison analyses demonstrate that the efficacy of the proposed method for online characterization of soft tissue parameters in the presence of contact model error.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Li, Tong; Gu, YuanTong, E-mail: yuantong.gu@qut.edu.au
As all-atom molecular dynamics method is limited by its enormous computational cost, various coarse-grained strategies have been developed to extend the length scale of soft matters in the modeling of mechanical behaviors. However, the classical thermostat algorithm in highly coarse-grained molecular dynamics method would underestimate the thermodynamic behaviors of soft matters (e.g. microfilaments in cells), which can weaken the ability of materials to overcome local energy traps in granular modeling. Based on all-atom molecular dynamics modeling of microfilament fragments (G-actin clusters), a new stochastic thermostat algorithm is developed to retain the representation of thermodynamic properties of microfilaments at extra coarse-grainedmore » level. The accuracy of this stochastic thermostat algorithm is validated by all-atom MD simulation. This new stochastic thermostat algorithm provides an efficient way to investigate the thermomechanical properties of large-scale soft matters.« less
The Role of Anticipation in Intelligent Systems
NASA Astrophysics Data System (ADS)
Klir, George J.
2002-09-01
The paper explores the relationship between the area of anticipatory systems and the area of intelligent systems. After an overview of these areas, the role of anticipation in intelligent systems is discussed and it is argued that the area of intelligent systems can greatly benefit by importing the various results developed within the area of anticipatory systems. Distinctions between hard and soft systems and between hard and soft computing are then discussed. It is explained why intelligent systems are by necessity soft and why soft computing is essential for their construction. It is finally argued that the area of anticipatory systems can enlarge its scope by importing knowledge regarding soft systems and soft computing from the area of intelligent systems.
Rough Set Soft Computing Cancer Classification and Network: One Stone, Two Birds
Zhang, Yue
2010-01-01
Gene expression profiling provides tremendous information to help unravel the complexity of cancer. The selection of the most informative genes from huge noise for cancer classification has taken centre stage, along with predicting the function of such identified genes and the construction of direct gene regulatory networks at different system levels with a tuneable parameter. A new study by Wang and Gotoh described a novel Variable Precision Rough Sets-rooted robust soft computing method to successfully address these problems and has yielded some new insights. The significance of this progress and its perspectives will be discussed in this article. PMID:20706619
Printing soft matter in three dimensions.
Truby, Ryan L; Lewis, Jennifer A
2016-12-14
Light- and ink-based three-dimensional (3D) printing methods allow the rapid design and fabrication of materials without the need for expensive tooling, dies or lithographic masks. They have led to an era of manufacturing in which computers can control the fabrication of soft matter that has tunable mechanical, electrical and other functional properties. The expanding range of printable materials, coupled with the ability to programmably control their composition and architecture across various length scales, is driving innovation in myriad applications. This is illustrated by examples of biologically inspired composites, shape-morphing systems, soft sensors and robotics that only additive manufacturing can produce.
Printing soft matter in three dimensions
NASA Astrophysics Data System (ADS)
Truby, Ryan L.; Lewis, Jennifer A.
2016-12-01
Light- and ink-based three-dimensional (3D) printing methods allow the rapid design and fabrication of materials without the need for expensive tooling, dies or lithographic masks. They have led to an era of manufacturing in which computers can control the fabrication of soft matter that has tunable mechanical, electrical and other functional properties. The expanding range of printable materials, coupled with the ability to programmably control their composition and architecture across various length scales, is driving innovation in myriad applications. This is illustrated by examples of biologically inspired composites, shape-morphing systems, soft sensors and robotics that only additive manufacturing can produce.
Computational dynamics of soft machines
NASA Astrophysics Data System (ADS)
Hu, Haiyan; Tian, Qiang; Liu, Cheng
2017-06-01
Soft machine refers to a kind of mechanical system made of soft materials to complete sophisticated missions, such as handling a fragile object and crawling along a narrow tunnel corner, under low cost control and actuation. Hence, soft machines have raised great challenges to computational dynamics. In this review article, recent studies of the authors on the dynamic modeling, numerical simulation, and experimental validation of soft machines are summarized in the framework of multibody system dynamics. The dynamic modeling approaches are presented first for the geometric nonlinearities of coupled overall motions and large deformations of a soft component, the physical nonlinearities of a soft component made of hyperelastic or elastoplastic materials, and the frictional contacts/impacts of soft components, respectively. Then the computation approach is outlined for the dynamic simulation of soft machines governed by a set of differential-algebraic equations of very high dimensions, with an emphasis on the efficient computations of the nonlinear elastic force vector of finite elements. The validations of the proposed approaches are given via three case studies, including the locomotion of a soft quadrupedal robot, the spinning deployment of a solar sail of a spacecraft, and the deployment of a mesh reflector of a satellite antenna, as well as the corresponding experimental studies. Finally, some remarks are made for future studies.
Decomposition of Fuzzy Soft Sets with Finite Value Spaces
Jun, Young Bae
2014-01-01
The notion of fuzzy soft sets is a hybrid soft computing model that integrates both gradualness and parameterization methods in harmony to deal with uncertainty. The decomposition of fuzzy soft sets is of great importance in both theory and practical applications with regard to decision making under uncertainty. This study aims to explore decomposition of fuzzy soft sets with finite value spaces. Scalar uni-product and int-product operations of fuzzy soft sets are introduced and some related properties are investigated. Using t-level soft sets, we define level equivalent relations and show that the quotient structure of the unit interval induced by level equivalent relations is isomorphic to the lattice consisting of all t-level soft sets of a given fuzzy soft set. We also introduce the concepts of crucial threshold values and complete threshold sets. Finally, some decomposition theorems for fuzzy soft sets with finite value spaces are established, illustrated by an example concerning the classification and rating of multimedia cell phones. The obtained results extend some classical decomposition theorems of fuzzy sets, since every fuzzy set can be viewed as a fuzzy soft set with a single parameter. PMID:24558342
Decomposition of fuzzy soft sets with finite value spaces.
Feng, Feng; Fujita, Hamido; Jun, Young Bae; Khan, Madad
2014-01-01
The notion of fuzzy soft sets is a hybrid soft computing model that integrates both gradualness and parameterization methods in harmony to deal with uncertainty. The decomposition of fuzzy soft sets is of great importance in both theory and practical applications with regard to decision making under uncertainty. This study aims to explore decomposition of fuzzy soft sets with finite value spaces. Scalar uni-product and int-product operations of fuzzy soft sets are introduced and some related properties are investigated. Using t-level soft sets, we define level equivalent relations and show that the quotient structure of the unit interval induced by level equivalent relations is isomorphic to the lattice consisting of all t-level soft sets of a given fuzzy soft set. We also introduce the concepts of crucial threshold values and complete threshold sets. Finally, some decomposition theorems for fuzzy soft sets with finite value spaces are established, illustrated by an example concerning the classification and rating of multimedia cell phones. The obtained results extend some classical decomposition theorems of fuzzy sets, since every fuzzy set can be viewed as a fuzzy soft set with a single parameter.
Application of Soft Computing in Coherent Communications Phase Synchronization
NASA Technical Reports Server (NTRS)
Drake, Jeffrey T.; Prasad, Nadipuram R.
2000-01-01
The use of soft computing techniques in coherent communications phase synchronization provides an alternative to analytical or hard computing methods. This paper discusses a novel use of Adaptive Neuro-Fuzzy Inference Systems (ANFIS) for phase synchronization in coherent communications systems utilizing Multiple Phase Shift Keying (MPSK) modulation. A brief overview of the M-PSK digital communications bandpass modulation technique is presented and it's requisite need for phase synchronization is discussed. We briefly describe the hybrid platform developed by Jang that incorporates fuzzy/neural structures namely the, Adaptive Neuro-Fuzzy Interference Systems (ANFIS). We then discuss application of ANFIS to phase estimation for M-PSK. The modeling of both explicit, and implicit phase estimation schemes for M-PSK symbols with unknown structure are discussed. Performance results from simulation of the above scheme is presented.
Soft computing methods for geoidal height transformation
NASA Astrophysics Data System (ADS)
Akyilmaz, O.; Özlüdemir, M. T.; Ayan, T.; Çelik, R. N.
2009-07-01
Soft computing techniques, such as fuzzy logic and artificial neural network (ANN) approaches, have enabled researchers to create precise models for use in many scientific and engineering applications. Applications that can be employed in geodetic studies include the estimation of earth rotation parameters and the determination of mean sea level changes. Another important field of geodesy in which these computing techniques can be applied is geoidal height transformation. We report here our use of a conventional polynomial model, the Adaptive Network-based Fuzzy (or in some publications, Adaptive Neuro-Fuzzy) Inference System (ANFIS), an ANN and a modified ANN approach to approximate geoid heights. These approximation models have been tested on a number of test points. The results obtained through the transformation processes from ellipsoidal heights into local levelling heights have also been compared.
Exploiting short-term memory in soft body dynamics as a computational resource
Nakajima, K.; Li, T.; Hauser, H.; Pfeifer, R.
2014-01-01
Soft materials are not only highly deformable, but they also possess rich and diverse body dynamics. Soft body dynamics exhibit a variety of properties, including nonlinearity, elasticity and potentially infinitely many degrees of freedom. Here, we demonstrate that such soft body dynamics can be employed to conduct certain types of computation. Using body dynamics generated from a soft silicone arm, we show that they can be exploited to emulate functions that require memory and to embed robust closed-loop control into the arm. Our results suggest that soft body dynamics have a short-term memory and can serve as a computational resource. This finding paves the way towards exploiting passive body dynamics for control of a large class of underactuated systems. PMID:25185579
Data mining in soft computing framework: a survey.
Mitra, S; Pal, S K; Mitra, P
2002-01-01
The present article provides a survey of the available literature on data mining using soft computing. A categorization has been provided based on the different soft computing tools and their hybridizations used, the data mining function implemented, and the preference criterion selected by the model. The utility of the different soft computing methodologies is highlighted. Generally fuzzy sets are suitable for handling the issues related to understandability of patterns, incomplete/noisy data, mixed media information and human interaction, and can provide approximate solutions faster. Neural networks are nonparametric, robust, and exhibit good learning and generalization capabilities in data-rich environments. Genetic algorithms provide efficient search algorithms to select a model, from mixed media data, based on some preference criterion/objective function. Rough sets are suitable for handling different types of uncertainty in data. Some challenges to data mining and the application of soft computing methodologies are indicated. An extensive bibliography is also included.
Computation of stress on the surface of a soft homogeneous arbitrarily shaped particle.
Yang, Minglin; Ren, Kuan Fang; Wu, Yueqian; Sheng, Xinqing
2014-04-01
Prediction of the stress on the surface of an arbitrarily shaped particle of soft material is essential in the study of elastic properties of the particles with optical force. It is also necessary in the manipulation and sorting of small particles with optical tweezers, since a regular-shaped particle, such as a sphere, may be deformed under the nonuniform optical stress on its surface. The stress profile on a spherical or small spheroidal soft particle trapped by shaped beams has been studied, however little work on computing the surface stress of an irregular-shaped particle has been reported. We apply in this paper the surface integral equation with multilevel fast multipole algorithm to compute the surface stress on soft homogeneous arbitrarily shaped particles. The comparison of the computed stress profile with that predicted by the generalized Lorenz-Mie theory for a water droplet of diameter equal to 51 wavelengths in a focused Gaussian beam show that the precision of our method is very good. Then stress profiles on spheroids with different aspect ratios are computed. The particles are illuminated by a Gaussian beam of different waist radius at different incidences. Physical analysis on the mechanism of optical stress is given with help of our recently developed vectorial complex ray model. It is found that the maximum of the stress profile on the surface of prolate spheroids is not only determined by the reflected and refracted rays (orders p=0,1) but also the rays undergoing one or two internal reflections where they focus. Computational study of stress on surface of a biconcave cell-like particle, which is a typical application in life science, is also undertaken.
Soft functions for generic jet algorithms and observables at hadron colliders
Bertolini, Daniele; Kolodrubetz, Daniel; Neill, Duff Austin; ...
2017-07-20
Here, we introduce a method to compute one-loop soft functions for exclusive N - jet processes at hadron colliders, allowing for different definitions of the algorithm that determines the jet regions and of the measurements in those regions. In particular, we generalize the N -jettiness hemisphere decomposition of ref. [1] in a manner that separates the dependence on the jet boundary from the observables measured inside the jet and beam regions. Results are given for several factorizable jet definitions, including anti- kT , XCone, and other geometric partitionings. We calculate explicitly the soft functions for angularity measurements, including jet massmore » and jet broadening, in pp → L + 1 jet and explore the differences for various jet vetoes and algorithms. This includes a consistent treatment of rapidity divergences when applicable. We also compute analytic results for these soft functions in an expansion for a small jet radius R. We find that the small- R results, including corrections up to O(R 2), accurately capture the full behavior over a large range of R.« less
Zhou, Xiangmin; Zhang, Nan; Sha, Desong; Shen, Yunhe; Tamma, Kumar K; Sweet, Robert
2009-01-01
The inability to render realistic soft-tissue behavior in real time has remained a barrier to face and content aspects of validity for many virtual reality surgical training systems. Biophysically based models are not only suitable for training purposes but also for patient-specific clinical applications, physiological modeling and surgical planning. When considering the existing approaches for modeling soft tissue for virtual reality surgical simulation, the computer graphics-based approach lacks predictive capability; the mass-spring model (MSM) based approach lacks biophysically realistic soft-tissue dynamic behavior; and the finite element method (FEM) approaches fail to meet the real-time requirement. The present development stems from physics fundamental thermodynamic first law; for a space discrete dynamic system directly formulates the space discrete but time continuous governing equation with embedded material constitutive relation and results in a discrete mechanics framework which possesses a unique balance between the computational efforts and the physically realistic soft-tissue dynamic behavior. We describe the development of the discrete mechanics framework with focused attention towards a virtual laparoscopic nephrectomy application.
Soft functions for generic jet algorithms and observables at hadron colliders
DOE Office of Scientific and Technical Information (OSTI.GOV)
Bertolini, Daniele; Kolodrubetz, Daniel; Neill, Duff Austin
Here, we introduce a method to compute one-loop soft functions for exclusive N - jet processes at hadron colliders, allowing for different definitions of the algorithm that determines the jet regions and of the measurements in those regions. In particular, we generalize the N -jettiness hemisphere decomposition of ref. [1] in a manner that separates the dependence on the jet boundary from the observables measured inside the jet and beam regions. Results are given for several factorizable jet definitions, including anti- kT , XCone, and other geometric partitionings. We calculate explicitly the soft functions for angularity measurements, including jet massmore » and jet broadening, in pp → L + 1 jet and explore the differences for various jet vetoes and algorithms. This includes a consistent treatment of rapidity divergences when applicable. We also compute analytic results for these soft functions in an expansion for a small jet radius R. We find that the small- R results, including corrections up to O(R 2), accurately capture the full behavior over a large range of R.« less
Research Methodologies Explored for a Paradigm Shift in University Teaching.
ERIC Educational Resources Information Center
Venter, I. M.; Blignaut, R. J.; Stoltz, D.
2001-01-01
Innovative teaching methods such as collaborative learning, teamwork, and mind maps were introduced to teach computer science and statistics courses at a South African university. Soft systems methodology was adapted and used to manage the research process of evaluating the effectiveness of the teaching methods. This research method provided proof…
NASA Technical Reports Server (NTRS)
Drake, Jeffrey T.; Prasad, Nadipuram R.
1999-01-01
This paper surveys recent advances in communications that utilize soft computing approaches to phase synchronization. Soft computing, as opposed to hard computing, is a collection of complementary methodologies that act in producing the most desirable control, decision, or estimation strategies. Recently, the communications area has explored the use of the principal constituents of soft computing, namely, fuzzy logic, neural networks, and genetic algorithms, for modeling, control, and most recently for the estimation of phase in phase-coherent communications. If the receiver in a digital communications system is phase-coherent, as is often the case, phase synchronization is required. Synchronization thus requires estimation and/or control at the receiver of an unknown or random phase offset.
A resilient domain decomposition polynomial chaos solver for uncertain elliptic PDEs
NASA Astrophysics Data System (ADS)
Mycek, Paul; Contreras, Andres; Le Maître, Olivier; Sargsyan, Khachik; Rizzi, Francesco; Morris, Karla; Safta, Cosmin; Debusschere, Bert; Knio, Omar
2017-07-01
A resilient method is developed for the solution of uncertain elliptic PDEs on extreme scale platforms. The method is based on a hybrid domain decomposition, polynomial chaos (PC) framework that is designed to address soft faults. Specifically, parallel and independent solves of multiple deterministic local problems are used to define PC representations of local Dirichlet boundary-to-boundary maps that are used to reconstruct the global solution. A LAD-lasso type regression is developed for this purpose. The performance of the resulting algorithm is tested on an elliptic equation with an uncertain diffusivity field. Different test cases are considered in order to analyze the impacts of correlation structure of the uncertain diffusivity field, the stochastic resolution, as well as the probability of soft faults. In particular, the computations demonstrate that, provided sufficiently many samples are generated, the method effectively overcomes the occurrence of soft faults.
Pifferi, Massimo; Bush, Andrew; Pioggia, Giovanni; Di Cicco, Maria; Chinellato, Iolanda; Bodini, Alessandro; Macchia, Pierantonio; Boner, Attilio L
2011-02-01
Asthma control is emphasized by new guidelines but remains poor in many children. Evaluation of control relies on subjective patient recall and may be overestimated by health-care professionals. This study assessed the value of spirometry and fractional exhaled nitric oxide (FeNO) measurements, used alone or in combination, in models developed by a machine learning approach in the objective classification of asthma control according to Global Initiative for Asthma guidelines and tested the model in a second group of children with asthma. Fifty-three children with persistent atopic asthma underwent two to six evaluations of asthma control, including spirometry and FeNO. Soft computing evaluation was performed by means of artificial neural networks and principal component analysis. The model was then tested in a cross-sectional study in an additional 77 children with allergic asthma. The machine learning method was not able to distinguish different levels of control using either spirometry or FeNO values alone. However, their use in combination modeled by soft computing was able to discriminate levels of asthma control. In particular, the model is able to recognize all children with uncontrolled asthma and correctly identify 99.0% of children with totally controlled asthma. In the cross-sectional study, the model prospectively identified correctly all the uncontrolled children and 79.6% of the controlled children. Soft computing analysis of spirometry and FeNO allows objective categorization of asthma control status.
Multiple point statistical simulation using uncertain (soft) conditional data
NASA Astrophysics Data System (ADS)
Hansen, Thomas Mejer; Vu, Le Thanh; Mosegaard, Klaus; Cordua, Knud Skou
2018-05-01
Geostatistical simulation methods have been used to quantify spatial variability of reservoir models since the 80s. In the last two decades, state of the art simulation methods have changed from being based on covariance-based 2-point statistics to multiple-point statistics (MPS), that allow simulation of more realistic Earth-structures. In addition, increasing amounts of geo-information (geophysical, geological, etc.) from multiple sources are being collected. This pose the problem of integration of these different sources of information, such that decisions related to reservoir models can be taken on an as informed base as possible. In principle, though difficult in practice, this can be achieved using computationally expensive Monte Carlo methods. Here we investigate the use of sequential simulation based MPS simulation methods conditional to uncertain (soft) data, as a computational efficient alternative. First, it is demonstrated that current implementations of sequential simulation based on MPS (e.g. SNESIM, ENESIM and Direct Sampling) do not account properly for uncertain conditional information, due to a combination of using only co-located information, and a random simulation path. Then, we suggest two approaches that better account for the available uncertain information. The first make use of a preferential simulation path, where more informed model parameters are visited preferentially to less informed ones. The second approach involves using non co-located uncertain information. For different types of available data, these approaches are demonstrated to produce simulation results similar to those obtained by the general Monte Carlo based approach. These methods allow MPS simulation to condition properly to uncertain (soft) data, and hence provides a computationally attractive approach for integration of information about a reservoir model.
Shintake, Jun; Cacucciolo, Vito; Floreano, Dario; Shea, Herbert
2018-05-07
Advances in soft robotics, materials science, and stretchable electronics have enabled rapid progress in soft grippers. Here, a critical overview of soft robotic grippers is presented, covering different material sets, physical principles, and device architectures. Soft gripping can be categorized into three technologies, enabling grasping by: a) actuation, b) controlled stiffness, and c) controlled adhesion. A comprehensive review of each type is presented. Compared to rigid grippers, end-effectors fabricated from flexible and soft components can often grasp or manipulate a larger variety of objects. Such grippers are an example of morphological computation, where control complexity is greatly reduced by material softness and mechanical compliance. Advanced materials and soft components, in particular silicone elastomers, shape memory materials, and active polymers and gels, are increasingly investigated for the design of lighter, simpler, and more universal grippers, using the inherent functionality of the materials. Embedding stretchable distributed sensors in or on soft grippers greatly enhances the ways in which the grippers interact with objects. Challenges for soft grippers include miniaturization, robustness, speed, integration of sensing, and control. Improved materials, processing methods, and sensing play an important role in future research. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Delcamp, E.; Lagarde, B.; Polack, F.
Though optimization softwares are commonly used in visible optical design, none seems to exist for soft X-ray optics. It is shown here that optimization techniques can be applied with some advantages to X-UV monochromator design. A merit function, suitable for minimizing the aberrations is proposed, and the general method of computation is described. Samples of the software inputs and outputs are presented, and compared to reference data. As an example of application to soft X-ray monochromator design, the optimization of the soft X-ray monochromator of the ESRF microscopy beamline is presented. Good agreement between the predicted resolution of a modifiedmore » PGM monochromator and experimental measurements is reported.« less
Computation of mass-density images from x-ray refraction-angle images.
Wernick, Miles N; Yang, Yongyi; Mondal, Indrasis; Chapman, Dean; Hasnah, Moumen; Parham, Christopher; Pisano, Etta; Zhong, Zhong
2006-04-07
In this paper, we investigate the possibility of computing quantitatively accurate images of mass density variations in soft tissue. This is a challenging task, because density variations in soft tissue, such as the breast, can be very subtle. Beginning from an image of refraction angle created by either diffraction-enhanced imaging (DEI) or multiple-image radiography (MIR), we estimate the mass-density image using a constrained least squares (CLS) method. The CLS algorithm yields accurate density estimates while effectively suppressing noise. Our method improves on an analytical method proposed by Hasnah et al (2005 Med. Phys. 32 549-52), which can produce significant artefacts when even a modest level of noise is present. We present a quantitative evaluation study to determine the accuracy with which mass density can be determined in the presence of noise. Based on computer simulations, we find that the mass-density estimation error can be as low as a few per cent for typical density variations found in the breast. Example images computed from less-noisy real data are also shown to illustrate the feasibility of the technique. We anticipate that density imaging may have application in assessment of water content of cartilage resulting from osteoarthritis, in evaluation of bone density, and in mammographic interpretation.
Patel, S; Aldowaisan, A; Dawood, A
2017-08-01
This case report describes a new approach to isolation and soft tissue retraction during endodontic surgery using cone-beam computed tomography (CBCT), computer-aided design (CAD) and three-dimensional (3D) printing. A 53-year-old patient presented for endodontic treatment of her maxillary left central incisor. It was decided to treat this tooth with a microsurgical approach. The data from the diagnostic CBCT scan were also used to make a physical model of the operative site, and CAD software was used to design a soft tissue retractor to be used during the patient's surgery. A custom retractor was then fabricated using a 3D printer. The custom-made retractor enhanced visualization and soft tissue handling during the patient's surgery. The patient was asymptomatic at a 1-year review. No abnormalities were detected during her clinical examination, and radiographic examination revealed complete healing of the surgical site. The significance of proper soft tissue retraction in periapical microsurgery is underemphasized. Geometric data from CBCT scans may be harvested for a variety of uses, adding value to the examination. 3D printing is a promising technology that may potentially have many uses in endodontic surgery. © 2016 International Endodontic Journal. Published by John Wiley & Sons Ltd.
Toe, Kyaw Kyar; Huang, Weimin; Yang, Tao; Duan, Yuping; Zhou, Jiayin; Su, Yi; Teo, Soo-Kng; Kumar, Selvaraj Senthil; Lim, Calvin Chi-Wan; Chui, Chee Kong; Chang, Stephen
2015-08-01
This work presents a surgical training system that incorporates cutting operation of soft tissue simulated based on a modified pre-computed linear elastic model in the Simulation Open Framework Architecture (SOFA) environment. A precomputed linear elastic model used for the simulation of soft tissue deformation involves computing the compliance matrix a priori based on the topological information of the mesh. While this process may require a few minutes to several hours, based on the number of vertices in the mesh, it needs only to be computed once and allows real-time computation of the subsequent soft tissue deformation. However, as the compliance matrix is based on the initial topology of the mesh, it does not allow any topological changes during simulation, such as cutting or tearing of the mesh. This work proposes a way to modify the pre-computed data by correcting the topological connectivity in the compliance matrix, without re-computing the compliance matrix which is computationally expensive.
NASA Astrophysics Data System (ADS)
Fu, Y.; Yang, W.; Xu, O.; Zhou, L.; Wang, J.
2017-04-01
To investigate time-variant and nonlinear characteristics in industrial processes, a soft sensor modelling method based on time difference, moving-window recursive partial least square (PLS) and adaptive model updating is proposed. In this method, time difference values of input and output variables are used as training samples to construct the model, which can reduce the effects of the nonlinear characteristic on modelling accuracy and retain the advantages of recursive PLS algorithm. To solve the high updating frequency of the model, a confidence value is introduced, which can be updated adaptively according to the results of the model performance assessment. Once the confidence value is updated, the model can be updated. The proposed method has been used to predict the 4-carboxy-benz-aldehyde (CBA) content in the purified terephthalic acid (PTA) oxidation reaction process. The results show that the proposed soft sensor modelling method can reduce computation effectively, improve prediction accuracy by making use of process information and reflect the process characteristics accurately.
The role of soft computing in intelligent machines.
de Silva, Clarence W
2003-08-15
An intelligent machine relies on computational intelligence in generating its intelligent behaviour. This requires a knowledge system in which representation and processing of knowledge are central functions. Approximation is a 'soft' concept, and the capability to approximate for the purposes of comparison, pattern recognition, reasoning, and decision making is a manifestation of intelligence. This paper examines the use of soft computing in intelligent machines. Soft computing is an important branch of computational intelligence, where fuzzy logic, probability theory, neural networks, and genetic algorithms are synergistically used to mimic the reasoning and decision making of a human. This paper explores several important characteristics and capabilities of machines that exhibit intelligent behaviour. Approaches that are useful in the development of an intelligent machine are introduced. The paper presents a general structure for an intelligent machine, giving particular emphasis to its primary components, such as sensors, actuators, controllers, and the communication backbone, and their interaction. The role of soft computing within the overall system is discussed. Common techniques and approaches that will be useful in the development of an intelligent machine are introduced, and the main steps in the development of an intelligent machine for practical use are given. An industrial machine, which employs the concepts of soft computing in its operation, is presented, and one aspect of intelligent tuning, which is incorporated into the machine, is illustrated.
[Axial computer tomography of the neurocranium (author's transl)].
Stöppler, L
1977-05-27
Computer tomography (CT), a new radiographic examination technique, is very highly efficient, for it has high informative content with little stress for the patient. In contrast to the conventional X-ray technology, CT succeeds, by direct presentation of the structure of the soft parts, in obtaining information which comes close to that of macroscopic neuropathology. The capacity and limitations of the method at the present stage of development are reported. Computer tomography cannot displace conventional neuroradiological methods of investigation, although it is rightly presented as a screening method and helps towards selective use. Indications, technical integration and handling of CT are prerequisites for the exhaustive benefit of the excellent new technique.
Exploiting short-term memory in soft body dynamics as a computational resource.
Nakajima, K; Li, T; Hauser, H; Pfeifer, R
2014-11-06
Soft materials are not only highly deformable, but they also possess rich and diverse body dynamics. Soft body dynamics exhibit a variety of properties, including nonlinearity, elasticity and potentially infinitely many degrees of freedom. Here, we demonstrate that such soft body dynamics can be employed to conduct certain types of computation. Using body dynamics generated from a soft silicone arm, we show that they can be exploited to emulate functions that require memory and to embed robust closed-loop control into the arm. Our results suggest that soft body dynamics have a short-term memory and can serve as a computational resource. This finding paves the way towards exploiting passive body dynamics for control of a large class of underactuated systems. © 2014 The Author(s) Published by the Royal Society. All rights reserved.
Robust path planning for flexible needle insertion using Markov decision processes.
Tan, Xiaoyu; Yu, Pengqian; Lim, Kah-Bin; Chui, Chee-Kong
2018-05-11
Flexible needle has the potential to accurately navigate to a treatment region in the least invasive manner. We propose a new planning method using Markov decision processes (MDPs) for flexible needle navigation that can perform robust path planning and steering under the circumstance of complex tissue-needle interactions. This method enhances the robustness of flexible needle steering from three different perspectives. First, the method considers the problem caused by soft tissue deformation. The method then resolves the common needle penetration failure caused by patterns of targets, while the last solution addresses the uncertainty issues in flexible needle motion due to complex and unpredictable tissue-needle interaction. Computer simulation and phantom experimental results show that the proposed method can perform robust planning and generate a secure control policy for flexible needle steering. Compared with a traditional method using MDPs, the proposed method achieves higher accuracy and probability of success in avoiding obstacles under complicated and uncertain tissue-needle interactions. Future work will involve experiment with biological tissue in vivo. The proposed robust path planning method can securely steer flexible needle within soft phantom tissues and achieve high adaptability in computer simulation.
Microscope self-calibration based on micro laser line imaging and soft computing algorithms
NASA Astrophysics Data System (ADS)
Apolinar Muñoz Rodríguez, J.
2018-06-01
A technique to perform microscope self-calibration via micro laser line and soft computing algorithms is presented. In this technique, the microscope vision parameters are computed by means of soft computing algorithms based on laser line projection. To implement the self-calibration, a microscope vision system is constructed by means of a CCD camera and a 38 μm laser line. From this arrangement, the microscope vision parameters are represented via Bezier approximation networks, which are accomplished through the laser line position. In this procedure, a genetic algorithm determines the microscope vision parameters by means of laser line imaging. Also, the approximation networks compute the three-dimensional vision by means of the laser line position. Additionally, the soft computing algorithms re-calibrate the vision parameters when the microscope vision system is modified during the vision task. The proposed self-calibration improves accuracy of the traditional microscope calibration, which is accomplished via external references to the microscope system. The capability of the self-calibration based on soft computing algorithms is determined by means of the calibration accuracy and the micro-scale measurement error. This contribution is corroborated by an evaluation based on the accuracy of the traditional microscope calibration.
Finite element dynamic analysis of soft tissues using state-space model.
Iorga, Lucian N; Shan, Baoxiang; Pelegri, Assimina A
2009-04-01
A finite element (FE) model is employed to investigate the dynamic response of soft tissues under external excitations, particularly corresponding to the case of harmonic motion imaging. A solid 3D mixed 'u-p' element S8P0 is implemented to capture the near-incompressibility inherent in soft tissues. Two important aspects in structural modelling of these tissues are studied; these are the influence of viscous damping on the dynamic response and, following FE-modelling, a developed state-space formulation that valuates the efficiency of several order reduction methods. It is illustrated that the order of the mathematical model can be significantly reduced, while preserving the accuracy of the observed system dynamics. Thus, the reduced-order state-space representation of soft tissues for general dynamic analysis significantly reduces the computational cost and provides a unitary framework for the 'forward' simulation and 'inverse' estimation of soft tissues. Moreover, the results suggest that damping in soft-tissue is significant, effectively cancelling the contribution of all but the first few vibration modes.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Anastasiou, Charalampos; Duhr, Claude; Dulat, Falko
We present methods to compute higher orders in the threshold expansion for the one-loop production of a Higgs boson in association with two partons at hadron colliders. This process contributes to the N 3LO Higgs production cross section beyond the soft-virtual approximation. We use reverse unitarity to expand the phase-space integrals in the small kinematic parameters and to reduce the coefficients of the expansion to a small set of master integrals. We describe two methods for the calculation of the master integrals. The first was introduced for the calculation of the soft triple-real radiation relevant to N 3LO Higgs production.more » The second uses a particular factorization of the three body phase-space measure and the knowledge of the scaling properties of the integral itself. Our result is presented as a Laurent expansion in the dimensional regulator, although some of the master integrals are computed to all orders in this parameter.« less
Development and validation of real-time simulation of X-ray imaging with respiratory motion.
Vidal, Franck P; Villard, Pierre-Frédéric
2016-04-01
We present a framework that combines evolutionary optimisation, soft tissue modelling and ray tracing on GPU to simultaneously compute the respiratory motion and X-ray imaging in real-time. Our aim is to provide validated building blocks with high fidelity to closely match both the human physiology and the physics of X-rays. A CPU-based set of algorithms is presented to model organ behaviours during respiration. Soft tissue deformation is computed with an extension of the Chain Mail method. Rigid elements move according to kinematic laws. A GPU-based surface rendering method is proposed to compute the X-ray image using the Beer-Lambert law. It is provided as an open-source library. A quantitative validation study is provided to objectively assess the accuracy of both components: (i) the respiration against anatomical data, and (ii) the X-ray against the Beer-Lambert law and the results of Monte Carlo simulations. Our implementation can be used in various applications, such as interactive medical virtual environment to train percutaneous transhepatic cholangiography in interventional radiology, 2D/3D registration, computation of digitally reconstructed radiograph, simulation of 4D sinograms to test tomography reconstruction tools. Copyright © 2015 Elsevier Ltd. All rights reserved.
Hybrid soft computing systems for electromyographic signals analysis: a review.
Xie, Hong-Bo; Guo, Tianruo; Bai, Siwei; Dokos, Socrates
2014-02-03
Electromyographic (EMG) is a bio-signal collected on human skeletal muscle. Analysis of EMG signals has been widely used to detect human movement intent, control various human-machine interfaces, diagnose neuromuscular diseases, and model neuromusculoskeletal system. With the advances of artificial intelligence and soft computing, many sophisticated techniques have been proposed for such purpose. Hybrid soft computing system (HSCS), the integration of these different techniques, aims to further improve the effectiveness, efficiency, and accuracy of EMG analysis. This paper reviews and compares key combinations of neural network, support vector machine, fuzzy logic, evolutionary computing, and swarm intelligence for EMG analysis. Our suggestions on the possible future development of HSCS in EMG analysis are also given in terms of basic soft computing techniques, further combination of these techniques, and their other applications in EMG analysis.
Hybrid soft computing systems for electromyographic signals analysis: a review
2014-01-01
Electromyographic (EMG) is a bio-signal collected on human skeletal muscle. Analysis of EMG signals has been widely used to detect human movement intent, control various human-machine interfaces, diagnose neuromuscular diseases, and model neuromusculoskeletal system. With the advances of artificial intelligence and soft computing, many sophisticated techniques have been proposed for such purpose. Hybrid soft computing system (HSCS), the integration of these different techniques, aims to further improve the effectiveness, efficiency, and accuracy of EMG analysis. This paper reviews and compares key combinations of neural network, support vector machine, fuzzy logic, evolutionary computing, and swarm intelligence for EMG analysis. Our suggestions on the possible future development of HSCS in EMG analysis are also given in terms of basic soft computing techniques, further combination of these techniques, and their other applications in EMG analysis. PMID:24490979
NASA Astrophysics Data System (ADS)
Nooruddin, Hasan A.; Anifowose, Fatai; Abdulraheem, Abdulazeez
2014-03-01
Soft computing techniques are recently becoming very popular in the oil industry. A number of computational intelligence-based predictive methods have been widely applied in the industry with high prediction capabilities. Some of the popular methods include feed-forward neural networks, radial basis function network, generalized regression neural network, functional networks, support vector regression and adaptive network fuzzy inference system. A comparative study among most popular soft computing techniques is presented using a large dataset published in literature describing multimodal pore systems in the Arab D formation. The inputs to the models are air porosity, grain density, and Thomeer parameters obtained using mercury injection capillary pressure profiles. Corrected air permeability is the target variable. Applying developed permeability models in recent reservoir characterization workflow ensures consistency between micro and macro scale information represented mainly by Thomeer parameters and absolute permeability. The dataset was divided into two parts with 80% of data used for training and 20% for testing. The target permeability variable was transformed to the logarithmic scale as a pre-processing step and to show better correlations with the input variables. Statistical and graphical analysis of the results including permeability cross-plots and detailed error measures were created. In general, the comparative study showed very close results among the developed models. The feed-forward neural network permeability model showed the lowest average relative error, average absolute relative error, standard deviations of error and root means squares making it the best model for such problems. Adaptive network fuzzy inference system also showed very good results.
A fluid-structure interaction model of soft robotics using an active strain approach
NASA Astrophysics Data System (ADS)
Hess, Andrew; Lin, Zhaowu; Gao, Tong
2017-11-01
Soft robotic swimmers exhibit rich dynamics that stem from the non-linear interplay of the fluid and immersed soft elastic body. Due to the difficulty of handling the nonlinear two-way coupling of hydrodynamic flow and deforming elastic body, studies of flexible swimmers often employ either one-way coupling strategies with imposed motions of the solid body or some simplified elasticity models. To explore the nonlinear dynamics of soft robots powered by smart soft materials, we develop a computational model to deal with the two-way fluid/elastic structure interactions using the fictitious domain method. To mimic the dynamic response of the functional soft material under external actuations, we assume the solid phase to be neo-Hookean, and employ an active strain approach to incorporate actuation, which is based on the multiplicative decomposition of the deformation gradient tensor. We demonstrate the capability of our algorithm by performing a series of numerical explorations that manipulate an elastic structure with finite thickness, starting from simple rectangular or circular plates to soft robot prototypes such as stingrays and jellyfish.
A versatile model for soft patchy particles with various patch arrangements.
Li, Zhan-Wei; Zhu, You-Liang; Lu, Zhong-Yuan; Sun, Zhao-Yan
2016-01-21
We propose a simple and general mesoscale soft patchy particle model, which can felicitously describe the deformable and surface-anisotropic characteristics of soft patchy particles. This model can be used in dynamics simulations to investigate the aggregation behavior and mechanism of various types of soft patchy particles with tunable number, size, direction, and geometrical arrangement of the patches. To improve the computational efficiency of this mesoscale model in dynamics simulations, we give the simulation algorithm that fits the compute unified device architecture (CUDA) framework of NVIDIA graphics processing units (GPUs). The validation of the model and the performance of the simulations using GPUs are demonstrated by simulating several benchmark systems of soft patchy particles with 1 to 4 patches in a regular geometrical arrangement. Because of its simplicity and computational efficiency, the soft patchy particle model will provide a powerful tool to investigate the aggregation behavior of soft patchy particles, such as patchy micelles, patchy microgels, and patchy dendrimers, over larger spatial and temporal scales.
Real-time haptic cutting of high-resolution soft tissues.
Wu, Jun; Westermann, Rüdiger; Dick, Christian
2014-01-01
We present our systematic efforts in advancing the computational performance of physically accurate soft tissue cutting simulation, which is at the core of surgery simulators in general. We demonstrate a real-time performance of 15 simulation frames per second for haptic soft tissue cutting of a deformable body at an effective resolution of 170,000 finite elements. This is achieved by the following innovative components: (1) a linked octree discretization of the deformable body, which allows for fast and robust topological modifications of the simulation domain, (2) a composite finite element formulation, which thoroughly reduces the number of simulation degrees of freedom and thus enables to carefully balance simulation performance and accuracy, (3) a highly efficient geometric multigrid solver for solving the linear systems of equations arising from implicit time integration, (4) an efficient collision detection algorithm that effectively exploits the composition structure, and (5) a stable haptic rendering algorithm for computing the feedback forces. Considering that our method increases the finite element resolution for physically accurate real-time soft tissue cutting simulation by an order of magnitude, our technique has a high potential to significantly advance the realism of surgery simulators.
NASA Astrophysics Data System (ADS)
Li, Guo-Yang; He, Qiong; Qian, Lin-Xue; Geng, Huiying; Liu, Yanlin; Yang, Xue-Yi; Luo, Jianwen; Cao, Yanping
2016-09-01
In part I of this study, we investigated the elastic Cherenkov effect (ECE) in an incompressible transversely isotropic (TI) soft solid using a combined theoretical and computational approach, based on which an inverse method has been proposed to measure both the anisotropic and hyperelastic parameters of TI soft tissues. In this part, experiments were carried out to validate the inverse method and demonstrate its usefulness in practical measurements. We first performed ex vivo experiments on bovine skeletal muscles. Not only the shear moduli along and perpendicular to the direction of muscle fibers but also the elastic modulus EL and hyperelastic parameter c2 were determined. We next carried out tensile tests to determine EL, which was compared with the value obtained using the shear wave elastography method. Furthermore, we conducted in vivo experiments on the biceps brachii and gastrocnemius muscles of ten healthy volunteers. To the best of our knowledge, this study represents the first attempt to determine EL of human muscles using the dynamic elastography method and inverse analysis. The significance of our method and its potential for clinical use are discussed.
NASA Astrophysics Data System (ADS)
Nakashima, Yoshito; Komatsubara, Junko
Unconsolidated soft sediments deform and mix complexly by seismically induced fluidization. Such geological soft-sediment deformation structures (SSDSs) recorded in boring cores were imaged by X-ray computed tomography (CT), which enables visualization of the inhomogeneous spatial distribution of iron-bearing mineral grains as strong X-ray absorbers in the deformed strata. Multifractal analysis was applied to the two-dimensional (2D) CT images with various degrees of deformation and mixing. The results show that the distribution of the iron-bearing mineral grains is multifractal for less deformed/mixed strata and almost monofractal for fully mixed (i.e. almost homogenized) strata. Computer simulations of deformation of real and synthetic digital images were performed using the egg-beater flow model. The simulations successfully reproduced the transformation from the multifractal spectra into almost monofractal spectra (i.e. almost convergence on a single point) with an increase in deformation/mixing intensity. The present study demonstrates that multifractal analysis coupled with X-ray CT and the mixing flow model is useful to quantify the complexity of seismically induced SSDSs, standing as a novel method for the evaluation of cores for seismic risk assessment.
Postoperative ultrasonography of the musculoskeletal system.
Chun, Kyung Ah; Cho, Kil-Ho
2015-07-01
Ultrasonography of the postoperative musculoskeletal system plays an important role in the accurate diagnosis of abnormal lesions in the bone and soft tissues. Ultrasonography is a fast and reliable method with no harmful irradiation for the evaluation of postoperative musculoskeletal complications. In particular, it is not affected by the excessive metal artifacts that appear on computed tomography or magnetic resonance imaging. Another benefit of ultrasonography is its capability to dynamically assess the pathologic movement in joints, muscles, or tendons. This article discusses the frequent applications of musculoskeletal ultrasonography in various postoperative situations including those involving the soft tissues around the metal hardware, arthroplasty, postoperative tendons, recurrent soft tissue tumors, bone unions, and amputation surgery.
A methodology for modeling surface effects on stiff and soft solids
NASA Astrophysics Data System (ADS)
He, Jin; Park, Harold S.
2017-09-01
We present a computational method that can be applied to capture surface stress and surface tension-driven effects in both stiff, crystalline nanostructures, like size-dependent mechanical properties, and soft solids, like elastocapillary effects. We show that the method is equivalent to the classical Young-Laplace model. The method is based on converting surface tension and surface elasticity on a zero-thickness surface to an initial stress and corresponding elastic properties on a finite thickness shell, where the consideration of geometric nonlinearity enables capturing the out-of-plane component of the surface tension that results for curved surfaces through evaluation of the surface stress in the deformed configuration. In doing so, we are able to use commercially available finite element technology, and thus do not require consideration and implementation of the classical Young-Laplace equation. Several examples are presented to demonstrate the capability of the methodology for modeling surface stress in both soft solids and crystalline nanostructures.
A methodology for modeling surface effects on stiff and soft solids
NASA Astrophysics Data System (ADS)
He, Jin; Park, Harold S.
2018-06-01
We present a computational method that can be applied to capture surface stress and surface tension-driven effects in both stiff, crystalline nanostructures, like size-dependent mechanical properties, and soft solids, like elastocapillary effects. We show that the method is equivalent to the classical Young-Laplace model. The method is based on converting surface tension and surface elasticity on a zero-thickness surface to an initial stress and corresponding elastic properties on a finite thickness shell, where the consideration of geometric nonlinearity enables capturing the out-of-plane component of the surface tension that results for curved surfaces through evaluation of the surface stress in the deformed configuration. In doing so, we are able to use commercially available finite element technology, and thus do not require consideration and implementation of the classical Young-Laplace equation. Several examples are presented to demonstrate the capability of the methodology for modeling surface stress in both soft solids and crystalline nanostructures.
Practical method for appearance match between soft copy and hard copy
NASA Astrophysics Data System (ADS)
Katoh, Naoya
1994-04-01
CRT monitors are often used as a soft proofing device for the hard copy image output. However, what the user sees on the monitor does not match its output, even if the monitor and the output device are calibrated with CIE/XYZ or CIE/Lab. This is especially obvious when correlated color temperature (CCT) of CRT monitor's white point significantly differs from ambient light. In a typical office environment, one uses a computer graphic monitor having a CCT of 9300K in a room of white fluorescent light of 4150K CCT. In such a case, human visual system is partially adapted to the CRT monitor's white point and partially to the ambient light. The visual experiments were performed on the effect of the ambient lighting. Practical method for soft copy color reproduction that matches the hard copy image in appearance is presented in this paper. This method is fundamentally based on a simple von Kries' adaptation model and takes into account the human visual system's partial adaptation and contrast matching.
Extreme Mechanics in Soft Pneumatic Robots and Soft Microfluidic Electronics and Sensors
NASA Astrophysics Data System (ADS)
Majidi, Carmel
2012-02-01
In the near future, machines and robots will be completely soft, stretchable, impact resistance, and capable of adapting their shape and functionality to changes in mission and environment. Similar to biological tissue and soft-body organisms, these next-generation technologies will contain no rigid parts and instead be composed entirely of soft elastomers, gels, fluids, and other non-rigid matter. Using a combination of rapid prototyping tools, microfabrication methods, and emerging techniques in so-called ``soft lithography,'' scientists and engineers are currently introducing exciting new families of soft pneumatic robots, soft microfluidic sensors, and hyperelastic electronics that can be stretched to as much as 10x their natural length. Progress has been guided by an interdisciplinary collection of insights from chemistry, life sciences, robotics, microelectronics, and solid mechanics. In virtually every technology and application domain, mechanics and elasticity have a central role in governing functionality and design. Moreover, in contrast to conventional machines and electronics, soft pneumatic systems and microfluidics typically operate in the finite deformation regime, with materials stretching to several times their natural length. In this talk, I will review emerging paradigms in soft pneumatic robotics and soft microfluidic electronics and highlight modeling and design challenges that arise from the extreme mechanics of inflation, locomotion, sensor operation, and human interaction. I will also discuss perceived challenges and opportunities in a broad range of potential application, from medicine to wearable computing.
Chande, Ruchi D; Wayne, Jennifer S
2017-09-01
Computational models of diarthrodial joints serve to inform the biomechanical function of these structures, and as such, must be supplied appropriate inputs for performance that is representative of actual joint function. Inputs for these models are sourced from both imaging modalities as well as literature. The latter is often the source of mechanical properties for soft tissues, like ligament stiffnesses; however, such data are not always available for all the soft tissues nor is it known for patient-specific work. In the current research, a method to improve the ligament stiffness definition for a computational foot/ankle model was sought with the greater goal of improving the predictive ability of the computational model. Specifically, the stiffness values were optimized using artificial neural networks (ANNs); both feedforward and radial basis function networks (RBFNs) were considered. Optimal networks of each type were determined and subsequently used to predict stiffnesses for the foot/ankle model. Ultimately, the predicted stiffnesses were considered reasonable and resulted in enhanced performance of the computational model, suggesting that artificial neural networks can be used to optimize stiffness inputs.
Visual and haptic integration in the estimation of softness of deformable objects
Cellini, Cristiano; Kaim, Lukas; Drewing, Knut
2013-01-01
Softness perception intrinsically relies on haptic information. However, through everyday experiences we learn correspondences between felt softness and the visual effects of exploratory movements that are executed to feel softness. Here, we studied how visual and haptic information is integrated to assess the softness of deformable objects. Participants discriminated between the softness of two softer or two harder objects using only-visual, only-haptic or both visual and haptic information. We assessed the reliabilities of the softness judgments using the method of constant stimuli. In visuo-haptic trials, discrepancies between the two senses' information allowed us to measure the contribution of the individual senses to the judgments. Visual information (finger movement and object deformation) was simulated using computer graphics; input in visual trials was taken from previous visuo-haptic trials. Participants were able to infer softness from vision alone, and vision considerably contributed to bisensory judgments (∼35%). The visual contribution was higher than predicted from models of optimal integration (senses are weighted according to their reliabilities). Bisensory judgments were less reliable than predicted from optimal integration. We conclude that the visuo-haptic integration of softness information is biased toward vision, rather than being optimal, and might even be guided by a fixed weighting scheme. PMID:25165510
Zhang, Peng; Liu, Keping; Zhao, Bo; Li, Yuanchun
2015-01-01
Optimal guidance is essential for the soft landing task. However, due to its high computational complexities, it is hardly applied to the autonomous guidance. In this paper, a computationally inexpensive optimal guidance algorithm based on the radial basis function neural network (RBFNN) is proposed. The optimization problem of the trajectory for soft landing on asteroids is formulated and transformed into a two-point boundary value problem (TPBVP). Combining the database of initial states with the relative initial co-states, an RBFNN is trained offline. The optimal trajectory of the soft landing is determined rapidly by applying the trained network in the online guidance. The Monte Carlo simulations of soft landing on the Eros433 are performed to demonstrate the effectiveness of the proposed guidance algorithm. PMID:26367382
Borghi, Alessandro; Ruggiero, Federica; Badiali, Giovanni; Bianchi, Alberto; Marchetti, Claudio; Rodriguez-Florez, Naiara; Breakey, Richard W. F.; Jeelani, Owase; Dunaway, David J.; Schievano, Silvia
2018-01-01
Repositioning of the maxilla in orthognathic surgery is carried out for functional and aesthetic purposes. Pre-surgical planning tools can predict 3D facial appearance by computing the response of the soft tissue to the changes to the underlying skeleton. The clinical use of commercial prediction software remains controversial, likely due to the deterministic nature of these computational predictions. A novel probabilistic finite element model (FEM) for the prediction of postoperative facial soft tissues is proposed in this paper. A probabilistic FEM was developed and validated on a cohort of eight patients who underwent maxillary repositioning and had pre- and postoperative cone beam computed tomography (CBCT) scans taken. Firstly, a variables correlation assessed various modelling parameters. Secondly, a design of experiments (DOE) provided a range of potential outcomes based on uniformly distributed input parameters, followed by an optimisation. Lastly, the second DOE iteration provided optimised predictions with a probability range. A range of 3D predictions was obtained using the probabilistic FEM and validated using reconstructed soft tissue surfaces from the postoperative CBCT data. The predictions in the nose and upper lip areas accurately include the true postoperative position, whereas the prediction under-estimates the position of the cheeks and lower lip. A probabilistic FEM has been developed and validated for the prediction of the facial appearance following orthognathic surgery. This method shows how inaccuracies in the modelling and uncertainties in executing surgical planning influence the soft tissue prediction and it provides a range of predictions including a minimum and maximum, which may be helpful for patients in understanding the impact of surgery on the face. PMID:29742139
Knoops, Paul G M; Borghi, Alessandro; Ruggiero, Federica; Badiali, Giovanni; Bianchi, Alberto; Marchetti, Claudio; Rodriguez-Florez, Naiara; Breakey, Richard W F; Jeelani, Owase; Dunaway, David J; Schievano, Silvia
2018-01-01
Repositioning of the maxilla in orthognathic surgery is carried out for functional and aesthetic purposes. Pre-surgical planning tools can predict 3D facial appearance by computing the response of the soft tissue to the changes to the underlying skeleton. The clinical use of commercial prediction software remains controversial, likely due to the deterministic nature of these computational predictions. A novel probabilistic finite element model (FEM) for the prediction of postoperative facial soft tissues is proposed in this paper. A probabilistic FEM was developed and validated on a cohort of eight patients who underwent maxillary repositioning and had pre- and postoperative cone beam computed tomography (CBCT) scans taken. Firstly, a variables correlation assessed various modelling parameters. Secondly, a design of experiments (DOE) provided a range of potential outcomes based on uniformly distributed input parameters, followed by an optimisation. Lastly, the second DOE iteration provided optimised predictions with a probability range. A range of 3D predictions was obtained using the probabilistic FEM and validated using reconstructed soft tissue surfaces from the postoperative CBCT data. The predictions in the nose and upper lip areas accurately include the true postoperative position, whereas the prediction under-estimates the position of the cheeks and lower lip. A probabilistic FEM has been developed and validated for the prediction of the facial appearance following orthognathic surgery. This method shows how inaccuracies in the modelling and uncertainties in executing surgical planning influence the soft tissue prediction and it provides a range of predictions including a minimum and maximum, which may be helpful for patients in understanding the impact of surgery on the face.
NASA Astrophysics Data System (ADS)
Somogyi, Gábor
2013-04-01
We finish the definition of a subtraction scheme for computing NNLO corrections to QCD jet cross sections. In particular, we perform the integration of the soft-type contributions to the doubly unresolved counterterms via the method of Mellin-Barnes representations. With these final ingredients in place, the definition of the scheme is complete and the computation of fully differential rates for electron-positron annihilation into two and three jets at NNLO accuracy becomes feasible.
Heikkilä, Janne; Hynynen, Kullervo
2006-04-01
Many noninvasive ultrasound techniques have been developed to explore mechanical properties of soft tissues. One of these methods, Localized Harmonic Motion Imaging (LHMI), has been proposed to be used for ultrasound surgery monitoring. In LHMI, dynamic ultrasound radiation-force stimulation induces displacements in a target that can be measured using pulse-echo imaging and used to estimate the elastic properties of the target. In this initial, simulation study, the use of a one-dimensional phased array is explored for the induction of the tissue motion. The study compares three different dual-frequency and amplitude-modulated single-frequency methods for the inducing tissue motion. Simulations were computed in a homogeneous soft-tissue volume. The Rayleigh integral was used in the simulations of the ultrasound fields and the tissue displacements were computed using a finite-element method (FEM). The simulations showed that amplitude-modulated sonication using a single frequency produced the largest vibration amplitude of the target tissue. These simulations demonstrate that the properties of the tissue motion are highly dependent on the sonication method and that it is important to consider the full three-dimensional distribution of the ultrasound field for controlling the induction of tissue motion.
Gostian, Antoniu-Oreste; Schwarz, David; Mandt, Philipp; Anagiotos, Andreas; Ortmann, Magdalene; Pazen, David; Beutner, Dirk; Hüttenbrink, Karl-Bernd
2016-11-01
The round window vibroplasty is a feasible option for the treatment of conductive, sensorineural and mixed hearing loss. Although clinical data suggest a satisfying clinical outcome with various coupling methods, the most efficient coupling technique of the floating mass transducer to the round window is still a matter of debate. For this, a soft silicone-made coupler has been developed recently that aims to ease and optimize the stimulation of the round window membrane of this middle ear implant. We performed a temporal bone study evaluating the performance of the soft coupler compared to the coupling with individually shaped cartilage, perichondrium and the titanium round window coupler with loads up to 20 mN at the unaltered and fully exposed round window niche. The stimulation of the cochlea was measured by the volume velocities of the stapes footplate detected by a laser Doppler vibrometer. The coupling method was computed as significant factor with cartilage and perichondrium allowing for the highest volume velocities followed by the soft and titanium coupler. Exposure of the round window niche allowed for higher volume velocities while the applied load did not significantly affect the results. The soft coupler allows for a good contact to the round window membrane and an effective backward stimulation of the cochlea. Clinical data are mandatory to evaluate performance of this novel coupling method in vivo.
Micromechanics and constitutive models for soft active materials with phase evolution
NASA Astrophysics Data System (ADS)
Wang, Binglian
Soft active materials, such as shape memory polymers, liquid crystal elastomers, soft tissues, gels etc., are materials that can deform largely in response to external stimuli. Micromechanics analysis of heterogeneous materials based on finite element method is a typically numerical way to study the thermal-mechanical behaviors of soft active materials with phase evolution. While the constitutive models that can precisely describe the stress and strain fields of materials in the process of phase evolution can not be found in the databases of some commercial finite element analysis (FEA) tools such as ANSYS or Abaqus, even the specific constitutive behavior for each individual phase either the new formed one or the original one has already been well-known. So developing a computationally efficient and general three dimensional (3D) thermal-mechanical constitutive model for soft active materials with phase evolution which can be implemented into FEA is eagerly demanded. This paper first solved this problem theoretically by recording the deformation history of each individual phase in the phase evolution process, and adopted the idea of effectiveness by regarding all the new formed phase as an effective phase with an effective deformation to make this theory computationally efficient. A user material subroutine (UMAT) code based on this theoretical constitutive model has been finished in this work which can be added into the material database in Abaqus or ANSYS and can be easily used for most soft active materials with phase evolution. Model validation also has been done through comparison between micromechanical FEA and experiments on a particular composite material, shape memory elastomeric composite (SMEC) which consisted of an elastomeric matrix and the crystallizable fibre. Results show that the micromechanics and the constitutive models developed in this paper for soft active materials with phase evolution are completely relied on.
NASA Astrophysics Data System (ADS)
Mehdizadeh, Saeid; Behmanesh, Javad; Khalili, Keivan
2017-11-01
Precipitation plays an important role in determining the climate of a region. Precise estimation of precipitation is required to manage and plan water resources, as well as other related applications such as hydrology, climatology, meteorology and agriculture. Time series of hydrologic variables such as precipitation are composed of deterministic and stochastic parts. Despite this fact, the stochastic part of the precipitation data is not usually considered in modeling of precipitation process. As an innovation, the present study introduces three new hybrid models by integrating soft computing methods including multivariate adaptive regression splines (MARS), Bayesian networks (BN) and gene expression programming (GEP) with a time series model, namely generalized autoregressive conditional heteroscedasticity (GARCH) for modeling of the monthly precipitation. For this purpose, the deterministic (obtained by soft computing methods) and stochastic (obtained by GARCH time series model) parts are combined with each other. To carry out this research, monthly precipitation data of Babolsar, Bandar Anzali, Gorgan, Ramsar, Tehran and Urmia stations with different climates in Iran were used during the period of 1965-2014. Root mean square error (RMSE), relative root mean square error (RRMSE), mean absolute error (MAE) and determination coefficient (R2) were employed to evaluate the performance of conventional/single MARS, BN and GEP, as well as the proposed MARS-GARCH, BN-GARCH and GEP-GARCH hybrid models. It was found that the proposed novel models are more precise than single MARS, BN and GEP models. Overall, MARS-GARCH and BN-GARCH models yielded better accuracy than GEP-GARCH. The results of the present study confirmed the suitability of proposed methodology for precise modeling of precipitation.
Real-time simulation of biological soft tissues: a PGD approach.
Niroomandi, S; González, D; Alfaro, I; Bordeu, F; Leygue, A; Cueto, E; Chinesta, F
2013-05-01
We introduce here a novel approach for the numerical simulation of nonlinear, hyperelastic soft tissues at kilohertz feedback rates necessary for haptic rendering. This approach is based upon the use of proper generalized decomposition techniques, a generalization of PODs. Proper generalized decomposition techniques can be considered as a means of a priori model order reduction and provides a physics-based meta-model without the need for prior computer experiments. The suggested strategy is thus composed of an offline phase, in which a general meta-model is computed, and an online evaluation phase in which the results are obtained at real time. Results are provided that show the potential of the proposed technique, together with some benchmark test that shows the accuracy of the method. Copyright © 2013 John Wiley & Sons, Ltd.
Superimposition of 3-dimensional cone-beam computed tomography models of growing patients
Cevidanes, Lucia H. C.; Heymann, Gavin; Cornelis, Marie A.; DeClerck, Hugo J.; Tulloch, J. F. Camilla
2009-01-01
Introduction The objective of this study was to evaluate a new method for superimposition of 3-dimensional (3D) models of growing subjects. Methods Cone-beam computed tomography scans were taken before and after Class III malocclusion orthopedic treatment with miniplates. Three observers independently constructed 18 3D virtual surface models from cone-beam computed tomography scans of 3 patients. Separate 3D models were constructed for soft-tissue, cranial base, maxillary, and mandibular surfaces. The anterior cranial fossa was used to register the 3D models of before and after treatment (about 1 year of follow-up). Results Three-dimensional overlays of superimposed models and 3D color-coded displacement maps allowed visual and quantitative assessment of growth and treatment changes. The range of interobserver errors for each anatomic region was 0.4 mm for the zygomatic process of maxilla, chin, condyles, posterior border of the rami, and lower border of the mandible, and 0.5 mm for the anterior maxilla soft-tissue upper lip. Conclusions Our results suggest that this method is a valid and reproducible assessment of treatment outcomes for growing subjects. This technique can be used to identify maxillary and mandibular positional changes and bone remodeling relative to the anterior cranial fossa. PMID:19577154
Synthesizing cognition in neuromorphic electronic systems
Neftci, Emre; Binas, Jonathan; Rutishauser, Ueli; Chicca, Elisabetta; Indiveri, Giacomo; Douglas, Rodney J.
2013-01-01
The quest to implement intelligent processing in electronic neuromorphic systems lacks methods for achieving reliable behavioral dynamics on substrates of inherently imprecise and noisy neurons. Here we report a solution to this problem that involves first mapping an unreliable hardware layer of spiking silicon neurons into an abstract computational layer composed of generic reliable subnetworks of model neurons and then composing the target behavioral dynamics as a “soft state machine” running on these reliable subnets. In the first step, the neural networks of the abstract layer are realized on the hardware substrate by mapping the neuron circuit bias voltages to the model parameters. This mapping is obtained by an automatic method in which the electronic circuit biases are calibrated against the model parameters by a series of population activity measurements. The abstract computational layer is formed by configuring neural networks as generic soft winner-take-all subnetworks that provide reliable processing by virtue of their active gain, signal restoration, and multistability. The necessary states and transitions of the desired high-level behavior are then easily embedded in the computational layer by introducing only sparse connections between some neurons of the various subnets. We demonstrate this synthesis method for a neuromorphic sensory agent that performs real-time context-dependent classification of motion patterns observed by a silicon retina. PMID:23878215
Discrimination of Mixed Taste Solutions using Ultrasonic Wave and Soft Computing
NASA Astrophysics Data System (ADS)
Kojima, Yohichiro; Kimura, Futoshi; Mikami, Tsuyoshi; Kitama, Masataka
In this study, ultrasonic wave acoustic properties of mixed taste solutions were investigated, and the possibility of taste sensing based on the acoustical properties obtained was examined. In previous studies, properties of solutions were discriminated based on sound velocity, amplitude and frequency characteristics of ultrasonic waves propagating through the five basic taste solutions and marketed beverages. However, to make this method applicable to beverages that contain many taste substances, further studies are required. In this paper, the waveform of an ultrasonic wave with frequency of approximately 5 MHz propagating through mixed solutions composed of sweet and salty substance was measured. As a result, differences among solutions were clearly observed as differences in their properties. Furthermore, these mixed solutions were discriminated by a self-organizing neural network. The ratio of volume in their mixed solutions was estimated by a distance-type fuzzy reasoning method. Therefore, the possibility of taste sensing was shown by using ultrasonic wave acoustic properties and the soft computing, such as the self-organizing neural network and the distance-type fuzzy reasoning method.
Amadasi, Alberto; Borgonovo, Simone; Brandone, Alberto; Di Giancamillo, Mauro; Cattaneo, Cristina
2014-05-01
The radiological search for GSR is crucial in burnt material although it has been rarely tested. In this study, thirty-one bovine ribs were shot at near-contact range and burnt to calcination in an oven simulating a real combustion. Computed tomography (CT) and magnetic resonance (MR) were performed before and after carbonization and compared with former analyses with DR (digital radiography); thus comparing the assistance, the radiological methods can provide in the search for GSR in fresh and burnt bone. DR demonstrated the greatest ability in the detection of metallic residues, CT showed lower abilities, while MR showed a high sensitivity only in soft tissues. Thus, DR can be considered as the most sensitive method in the detection of GSR in charred bones, whereas CT and MR demonstrated much less reliability. Nonetheless, the MR ameliorates the analysis of gunshot wounds in other types of remains with large quantities of soft tissues. © 2013 American Academy of Forensic Sciences.
Improved Rubin-Bodner Model for the Prediction of Soft Tissue Deformations
Zhang, Guangming; Xia, James J.; Liebschner, Michael; Zhang, Xiaoyan; Kim, Daeseung; Zhou, Xiaobo
2016-01-01
In craniomaxillofacial (CMF) surgery, a reliable way of simulating the soft tissue deformation resulted from skeletal reconstruction is vitally important for preventing the risks of facial distortion postoperatively. However, it is difficult to simulate the soft tissue behaviors affected by different types of CMF surgery. This study presents an integrated bio-mechanical and statistical learning model to improve accuracy and reliability of predictions on soft facial tissue behavior. The Rubin-Bodner (RB) model is initially used to describe the biomechanical behavior of the soft facial tissue. Subsequently, a finite element model (FEM) computers the stress of each node in soft facial tissue mesh data resulted from bone displacement. Next, the Generalized Regression Neural Network (GRNN) method is implemented to obtain the relationship between the facial soft tissue deformation and the stress distribution corresponding to different CMF surgical types and to improve evaluation of elastic parameters included in the RB model. Therefore, the soft facial tissue deformation can be predicted by biomechanical properties and statistical model. Leave-one-out cross-validation is used on eleven patients. As a result, the average prediction error of our model (0.7035mm) is lower than those resulting from other approaches. It also demonstrates that the more accurate bio-mechanical information the model has, the better prediction performance it could achieve. PMID:27717593
Khaled Addas, Mohamed; Al Humaidi, Abdullah Saad Ali; Al Qahtani, Abdulrazaq Mohammed; Al Qahtani, Mubarak Daghash
2017-01-01
Aim To determine the prevalence of type of soft palate in targeted population. Materials and Methods Using computer technology in dentistry, intraoral digital scanner, and 3D analysis software tool, study was conducted. 100 patients selected from the outpatient clinics were divided into two groups based on the ages of 20–40 years and 41–60 years with equal ratio of males and females. Each selected patient's maxillary arch was scanned with intraoral scanner; images so obtained were sectioned in anteroposterior cross section and with the 3D analysis software; the angulation between hard and soft palate was determined. Results The prevalence of type II soft palate (angulation between hard and soft palate is between 10 and 45 degrees) was highest, 60% in group 1 and 44% in group 2. The difference between genders was statistically significant with p value <0.05 in both the groups, although females had higher angulation compared to the males in all classes of both groups. Conclusions In targeted population of Aseer Province, Saudi Arabia, the prevalence of type II soft palate was more common, with higher soft palate angulation among females. The advanced age had no effect in the type of soft palate in the region. PMID:28951740
A comparative analysis of soft computing techniques for gene prediction.
Goel, Neelam; Singh, Shailendra; Aseri, Trilok Chand
2013-07-01
The rapid growth of genomic sequence data for both human and nonhuman species has made analyzing these sequences, especially predicting genes in them, very important and is currently the focus of many research efforts. Beside its scientific interest in the molecular biology and genomics community, gene prediction is of considerable importance in human health and medicine. A variety of gene prediction techniques have been developed for eukaryotes over the past few years. This article reviews and analyzes the application of certain soft computing techniques in gene prediction. First, the problem of gene prediction and its challenges are described. These are followed by different soft computing techniques along with their application to gene prediction. In addition, a comparative analysis of different soft computing techniques for gene prediction is given. Finally some limitations of the current research activities and future research directions are provided. Copyright © 2013 Elsevier Inc. All rights reserved.
Information processing via physical soft body
Nakajima, Kohei; Hauser, Helmut; Li, Tao; Pfeifer, Rolf
2015-01-01
Soft machines have recently gained prominence due to their inherent softness and the resulting safety and resilience in applications. However, these machines also have disadvantages, as they respond with complex body dynamics when stimulated. These dynamics exhibit a variety of properties, including nonlinearity, memory, and potentially infinitely many degrees of freedom, which are often difficult to control. Here, we demonstrate that these seemingly undesirable properties can in fact be assets that can be exploited for real-time computation. Using body dynamics generated from a soft silicone arm, we show that they can be employed to emulate desired nonlinear dynamical systems. First, by using benchmark tasks, we demonstrate that the nonlinearity and memory within the body dynamics can increase the computational performance. Second, we characterize our system’s computational capability by comparing its task performance with a standard machine learning technique and identify its range of validity and limitation. Our results suggest that soft bodies are not only impressive in their deformability and flexibility but can also be potentially used as computational resources on top and for free. PMID:26014748
Luboz, Vincent; Chabanas, Matthieu; Swider, Pascal; Payan, Yohan
2005-08-01
This paper addresses an important issue raised for the clinical relevance of Computer-Assisted Surgical applications, namely the methodology used to automatically build patient-specific finite element (FE) models of anatomical structures. From this perspective, a method is proposed, based on a technique called the mesh-matching method, followed by a process that corrects mesh irregularities. The mesh-matching algorithm generates patient-specific volume meshes from an existing generic model. The mesh regularization process is based on the Jacobian matrix transform related to the FE reference element and the current element. This method for generating patient-specific FE models is first applied to computer-assisted maxillofacial surgery, and more precisely, to the FE elastic modelling of patient facial soft tissues. For each patient, the planned bone osteotomies (mandible, maxilla, chin) are used as boundary conditions to deform the FE face model, in order to predict the aesthetic outcome of the surgery. Seven FE patient-specific models were successfully generated by our method. For one patient, the prediction of the FE model is qualitatively compared with the patient's post-operative appearance, measured from a computer tomography scan. Then, our methodology is applied to computer-assisted orbital surgery. It is, therefore, evaluated for the generation of 11 patient-specific FE poroelastic models of the orbital soft tissues. These models are used to predict the consequences of the surgical decompression of the orbit. More precisely, an average law is extrapolated from the simulations carried out for each patient model. This law links the size of the osteotomy (i.e. the surgical gesture) and the backward displacement of the eyeball (the consequence of the surgical gesture).
Computer vision and soft computing for automatic skull-face overlay in craniofacial superimposition.
Campomanes-Álvarez, B Rosario; Ibáñez, O; Navarro, F; Alemán, I; Botella, M; Damas, S; Cordón, O
2014-12-01
Craniofacial superimposition can provide evidence to support that some human skeletal remains belong or not to a missing person. It involves the process of overlaying a skull with a number of ante mortem images of an individual and the analysis of their morphological correspondence. Within the craniofacial superimposition process, the skull-face overlay stage just focuses on achieving the best possible overlay of the skull and a single ante mortem image of the suspect. Although craniofacial superimposition has been in use for over a century, skull-face overlay is still applied by means of a trial-and-error approach without an automatic method. Practitioners finish the process once they consider that a good enough overlay has been attained. Hence, skull-face overlay is a very challenging, subjective, error prone, and time consuming part of the whole process. Though the numerical assessment of the method quality has not been achieved yet, computer vision and soft computing arise as powerful tools to automate it, dramatically reducing the time taken by the expert and obtaining an unbiased overlay result. In this manuscript, we justify and analyze the use of these techniques to properly model the skull-face overlay problem. We also present the automatic technical procedure we have developed using these computational methods and show the four overlays obtained in two craniofacial superimposition cases. This automatic procedure can be thus considered as a tool to aid forensic anthropologists to develop the skull-face overlay, automating and avoiding subjectivity of the most tedious task within craniofacial superimposition. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.
Differences in Train-induced Vibration between Hard Soil and Soft Soil
NASA Astrophysics Data System (ADS)
Noyori, M.; Yokoyama, H.
2017-12-01
Vibration and noise caused by running trains sometimes raises environmental issues. Train-induced vibration is caused by moving static and dynamic axle loads. To reduce the vibration, it is important to clarify the conditions under which the train-induced vibration increases. In this study, we clarified the differences in train-induced vibration between on hard soil and on soft soil using a numerical simulation method. The numerical simulation method we used is a combination of two analysis. The one is a coupled vibration analysis model of a running train, a track and a supporting structure. In the analysis, the excitation force of the viaduct slabs generated by a running train is computed. The other analysis is a three-dimensional vibration analysis model of a supporting structure and the ground into which the excitation force computed by the former analysis is input. As a result of the numerical simulation, the ground vibration in the area not more than 25m from the center of the viaduct is larger under the soft soil condition than that under the hard soil condition in almost all frequency ranges. On the other hand, the ground vibration of 40 and 50Hz at a point 50m from the center of the viaduct under the hard soil condition is larger than that under the soft soil condition. These are consistent with the result of the two-dimensional FEM based on a ground model alone. Thus, we concluded that these results are obtained from not the effects of the running train but the vibration characteristics of the ground.
Prediction of Software Reliability using Bio Inspired Soft Computing Techniques.
Diwaker, Chander; Tomar, Pradeep; Poonia, Ramesh C; Singh, Vijander
2018-04-10
A lot of models have been made for predicting software reliability. The reliability models are restricted to using particular types of methodologies and restricted number of parameters. There are a number of techniques and methodologies that may be used for reliability prediction. There is need to focus on parameters consideration while estimating reliability. The reliability of a system may increase or decreases depending on the selection of different parameters used. Thus there is need to identify factors that heavily affecting the reliability of the system. In present days, reusability is mostly used in the various area of research. Reusability is the basis of Component-Based System (CBS). The cost, time and human skill can be saved using Component-Based Software Engineering (CBSE) concepts. CBSE metrics may be used to assess those techniques which are more suitable for estimating system reliability. Soft computing is used for small as well as large-scale problems where it is difficult to find accurate results due to uncertainty or randomness. Several possibilities are available to apply soft computing techniques in medicine related problems. Clinical science of medicine using fuzzy-logic, neural network methodology significantly while basic science of medicine using neural-networks-genetic algorithm most frequently and preferably. There is unavoidable interest shown by medical scientists to use the various soft computing methodologies in genetics, physiology, radiology, cardiology and neurology discipline. CBSE boost users to reuse the past and existing software for making new products to provide quality with a saving of time, memory space, and money. This paper focused on assessment of commonly used soft computing technique like Genetic Algorithm (GA), Neural-Network (NN), Fuzzy Logic, Support Vector Machine (SVM), Ant Colony Optimization (ACO), Particle Swarm Optimization (PSO), and Artificial Bee Colony (ABC). This paper presents working of soft computing techniques and assessment of soft computing techniques to predict reliability. The parameter considered while estimating and prediction of reliability are also discussed. This study can be used in estimation and prediction of the reliability of various instruments used in the medical system, software engineering, computer engineering and mechanical engineering also. These concepts can be applied to both software and hardware, to predict the reliability using CBSE.
A Case for Soft Error Detection and Correction in Computational Chemistry.
van Dam, Hubertus J J; Vishnu, Abhinav; de Jong, Wibe A
2013-09-10
High performance computing platforms are expected to deliver 10(18) floating operations per second by the year 2022 through the deployment of millions of cores. Even if every core is highly reliable the sheer number of them will mean that the mean time between failures will become so short that most application runs will suffer at least one fault. In particular soft errors caused by intermittent incorrect behavior of the hardware are a concern as they lead to silent data corruption. In this paper we investigate the impact of soft errors on optimization algorithms using Hartree-Fock as a particular example. Optimization algorithms iteratively reduce the error in the initial guess to reach the intended solution. Therefore they may intuitively appear to be resilient to soft errors. Our results show that this is true for soft errors of small magnitudes but not for large errors. We suggest error detection and correction mechanisms for different classes of data structures. The results obtained with these mechanisms indicate that we can correct more than 95% of the soft errors at moderate increases in the computational cost.
Miga, Michael I
2016-01-01
With the recent advances in computing, the opportunities to translate computational models to more integrated roles in patient treatment are expanding at an exciting rate. One area of considerable development has been directed towards correcting soft tissue deformation within image guided neurosurgery applications. This review captures the efforts that have been undertaken towards enhancing neuronavigation by the integration of soft tissue biomechanical models, imaging and sensing technologies, and algorithmic developments. In addition, the review speaks to the evolving role of modeling frameworks within surgery and concludes with some future directions beyond neurosurgical applications.
Impact of view reduction in CT on radiation dose for patients
NASA Astrophysics Data System (ADS)
Parcero, E.; Flores, L.; Sánchez, M. G.; Vidal, V.; Verdú, G.
2017-08-01
Iterative methods have become a hot topic of research in computed tomography (CT) imaging because of their capacity to resolve the reconstruction problem from a limited number of projections. This allows the reduction of radiation exposure on patients during the data acquisition. The reconstruction time and the high radiation dose imposed on patients are the two major drawbacks in CT. To solve them effectively we adapted the method for sparse linear equations and sparse least squares (LSQR) with soft threshold filtering (STF) and the fast iterative shrinkage-thresholding algorithm (FISTA) to computed tomography reconstruction. The feasibility of the proposed methods is demonstrated numerically.
Rapid tooling method for soft customized removable oral appliances.
Salmi, Mika; Tuomi, Jukka; Sirkkanen, Rauno; Ingman, Tuula; Mäkitie, Antti
2012-01-01
Traditionally oral appliances i.e. removable orthodontic appliances, bite splints and snoring / sleep apnea appliances are made with alginate impressions and wax registrations. Our aim was to describe the process of manufacturing customized oral appliances with a new technique i.e. rapid tooling method. The appliance should ideally be custom made to match the teeth. An orthodontic patient, scheduled for conventional orthodontic treatment, served as a study subject. After a precise clinical and radiographic examination, the approach was to digitize the patient's dental arches and then to correct them virtually by computer. Additive manufacturing was then used to fabricate a mould for a soft customized appliance. The mould was manufactured using stereolithography from Somos ProtoGen O-XT 18420 material. Casting material for the mould to obtain the final appliance was silicone. As a result we managed to create a customized soft orthodontic appliance. Also, the accuracy of the method was found to be adequate. Two versions of the described device were manufactured: one with small and one with moderate orthodontic force. The study person also gave information on the subjective patient adaptation aspects of the oral appliance.
Vehicular traffic noise prediction using soft computing approach.
Singh, Daljeet; Nigam, S P; Agrawal, V P; Kumar, Maneek
2016-12-01
A new approach for the development of vehicular traffic noise prediction models is presented. Four different soft computing methods, namely, Generalized Linear Model, Decision Trees, Random Forests and Neural Networks, have been used to develop models to predict the hourly equivalent continuous sound pressure level, Leq, at different locations in the Patiala city in India. The input variables include the traffic volume per hour, percentage of heavy vehicles and average speed of vehicles. The performance of the four models is compared on the basis of performance criteria of coefficient of determination, mean square error and accuracy. 10-fold cross validation is done to check the stability of the Random Forest model, which gave the best results. A t-test is performed to check the fit of the model with the field data. Copyright © 2016 Elsevier Ltd. All rights reserved.
Modeling Soft Tissue Damage and Failure Using a Combined Particle/Continuum Approach.
Rausch, M K; Karniadakis, G E; Humphrey, J D
2017-02-01
Biological soft tissues experience damage and failure as a result of injury, disease, or simply age; examples include torn ligaments and arterial dissections. Given the complexity of tissue geometry and material behavior, computational models are often essential for studying both damage and failure. Yet, because of the need to account for discontinuous phenomena such as crazing, tearing, and rupturing, continuum methods are limited. Therefore, we model soft tissue damage and failure using a particle/continuum approach. Specifically, we combine continuum damage theory with Smoothed Particle Hydrodynamics (SPH). Because SPH is a meshless particle method, and particle connectivity is determined solely through a neighbor list, discontinuities can be readily modeled by modifying this list. We show, for the first time, that an anisotropic hyperelastic constitutive model commonly employed for modeling soft tissue can be conveniently implemented within a SPH framework and that SPH results show excellent agreement with analytical solutions for uniaxial and biaxial extension as well as finite element solutions for clamped uniaxial extension in 2D and 3D. We further develop a simple algorithm that automatically detects damaged particles and disconnects the spatial domain along rupture lines in 2D and rupture surfaces in 3D. We demonstrate the utility of this approach by simulating damage and failure under clamped uniaxial extension and in a peeling experiment of virtual soft tissue samples. In conclusion, SPH in combination with continuum damage theory may provide an accurate and efficient framework for modeling damage and failure in soft tissues.
Modeling Soft Tissue Damage and Failure Using a Combined Particle/Continuum Approach
Rausch, M. K.; Karniadakis, G. E.; Humphrey, J. D.
2016-01-01
Biological soft tissues experience damage and failure as a result of injury, disease, or simply age; examples include torn ligaments and arterial dissections. Given the complexity of tissue geometry and material behavior, computational models are often essential for studying both damage and failure. Yet, because of the need to account for discontinuous phenomena such as crazing, tearing, and rupturing, continuum methods are limited. Therefore, we model soft tissue damage and failure using a particle/continuum approach. Specifically, we combine continuum damage theory with Smoothed Particle Hydrodynamics (SPH). Because SPH is a meshless particle method, and particle connectivity is determined solely through a neighbor list, discontinuities can be readily modeled by modifying this list. We show, for the first time, that an anisotropic hyperelastic constitutive model commonly employed for modeling soft tissue can be conveniently implemented within a SPH framework and that SPH results show excellent agreement with analytical solutions for uniaxial and biaxial extension as well as finite element solutions for clamped uniaxial extension in 2D and 3D. We further develop a simple algorithm that automatically detects damaged particles and disconnects the spatial domain along rupture lines in 2D and rupture surfaces in 3D. We demonstrate the utility of this approach by simulating damage and failure under clamped uniaxial extension and in a peeling experiment of virtual soft tissue samples. In conclusion, SPH in combination with continuum damage theory may provide an accurate and efficient framework for modeling damage and failure in soft tissues. PMID:27538848
Cubical Mass-Spring Model design based on a tensile deformation test and nonlinear material model.
San-Vicente, Gaizka; Aguinaga, Iker; Tomás Celigüeta, Juan
2012-02-01
Mass-Spring Models (MSMs) are used to simulate the mechanical behavior of deformable bodies such as soft tissues in medical applications. Although they are fast to compute, they lack accuracy and their design remains still a great challenge. The major difficulties in building realistic MSMs lie on the spring stiffness estimation and the topology identification. In this work, the mechanical behavior of MSMs under tensile loads is analyzed before studying the spring stiffness estimation. In particular, the performed qualitative and quantitative analysis of the behavior of cubical MSMs shows that they have a nonlinear response similar to hyperelastic material models. According to this behavior, a new method for spring stiffness estimation valid for linear and nonlinear material models is proposed. This method adjusts the stress-strain and compressibility curves to a given reference behavior. The accuracy of the MSMs designed with this method is tested taking as reference some soft-tissue simulations based on nonlinear Finite Element Method (FEM). The obtained results show that MSMs can be designed to realistically model the behavior of hyperelastic materials such as soft tissues and can become an interesting alternative to other approaches such as nonlinear FEM.
Zheng, Meixun; Bender, Daniel
2018-03-13
Computer-based testing (CBT) has made progress in health sciences education. In 2015, the authors led implementation of a CBT system (ExamSoft) at a dental school in the U.S. Guided by the Technology Acceptance Model (TAM), the purposes of this study were to (a) examine dental students' acceptance of ExamSoft; (b) understand factors impacting acceptance; and (c) evaluate the impact of ExamSoft on students' learning and exam performance. Survey and focus group data revealed that ExamSoft was well accepted by students as a testing tool and acknowledged by most for its potential to support learning. Regression analyses showed that perceived ease of use and perceived usefulness of ExamSoft significantly predicted student acceptance. Prior CBT experience and computer skills did not significantly predict acceptance of ExamSoft. Students reported that ExamSoft promoted learning in the first program year, primarily through timely and rich feedback on examination performance. t-Tests yielded mixed results on whether students performed better on computerized or paper examinations. The study contributes to the literature on CBT and the application of the TAM model in health sciences education. Findings also suggest ways in which health sciences institutions can implement CBT to maximize its potential as an assessment and learning tool.
Uncertainty Modeling of Pollutant Transport in Atmosphere and Aquatic Route Using Soft Computing
NASA Astrophysics Data System (ADS)
Datta, D.
2010-10-01
Hazardous radionuclides are released as pollutants in the atmospheric and aquatic environment (ATAQE) during the normal operation of nuclear power plants. Atmospheric and aquatic dispersion models are routinely used to assess the impact of release of radionuclide from any nuclear facility or hazardous chemicals from any chemical plant on the ATAQE. Effect of the exposure from the hazardous nuclides or chemicals is measured in terms of risk. Uncertainty modeling is an integral part of the risk assessment. The paper focuses the uncertainty modeling of the pollutant transport in atmospheric and aquatic environment using soft computing. Soft computing is addressed due to the lack of information on the parameters that represent the corresponding models. Soft-computing in this domain basically addresses the usage of fuzzy set theory to explore the uncertainty of the model parameters and such type of uncertainty is called as epistemic uncertainty. Each uncertain input parameters of the model is described by a triangular membership function.
RNA secondary structure prediction using soft computing.
Ray, Shubhra Sankar; Pal, Sankar K
2013-01-01
Prediction of RNA structure is invaluable in creating new drugs and understanding genetic diseases. Several deterministic algorithms and soft computing-based techniques have been developed for more than a decade to determine the structure from a known RNA sequence. Soft computing gained importance with the need to get approximate solutions for RNA sequences by considering the issues related with kinetic effects, cotranscriptional folding, and estimation of certain energy parameters. A brief description of some of the soft computing-based techniques, developed for RNA secondary structure prediction, is presented along with their relevance. The basic concepts of RNA and its different structural elements like helix, bulge, hairpin loop, internal loop, and multiloop are described. These are followed by different methodologies, employing genetic algorithms, artificial neural networks, and fuzzy logic. The role of various metaheuristics, like simulated annealing, particle swarm optimization, ant colony optimization, and tabu search is also discussed. A relative comparison among different techniques, in predicting 12 known RNA secondary structures, is presented, as an example. Future challenging issues are then mentioned.
Dynamic and rheological properties of soft biological cell suspensions
Yazdani, Alireza; Li, Xuejin
2016-01-01
Quantifying dynamic and rheological properties of suspensions of soft biological particles such as vesicles, capsules, and red blood cells (RBCs) is fundamentally important in computational biology and biomedical engineering. In this review, recent studies on dynamic and rheological behavior of soft biological cell suspensions by computer simulations are presented, considering both unbounded and confined shear flow. Furthermore, the hemodynamic and hemorheological characteristics of RBCs in diseases such as malaria and sickle cell anemia are highlighted. PMID:27540271
NASA Astrophysics Data System (ADS)
Wilson, Katherine E.; Henke, E.-F. Markus; Slipher, Geoffrey A.; Anderson, Iain A.
2017-04-01
Electromechanically coupled dielectric elastomer actuators (DEAs) and dielectric elastomer switches (DESs) may form digital logic circuitry made entirely of soft and flexible materials. The expansion in planar area of a DEA exerts force across a DES, which is a soft electrode with strain-dependent resistivity. When compressed, the DES drops steeply in resistance and changes state from non-conducting to conducting. Logic operators may be achieved with different arrangements of interacting DE actuators and switches. We demonstrate combinatorial logic elements, including the fundamental Boolean logic gates, as well as sequential logic elements, including latches and flip-flops. With both data storage and signal processing abilities, the necessary calculating components of a soft computer are available. A noteworthy advantage of a soft computer with mechanosensitive DESs is the potential for responding to environmental strains while locally processing information and generating a reaction, like a muscle reflex.
Zhan, Yi; Fu, Guo; Zhou, Xiang; He, Bo; Yan, Li-Wei; Zhu, Qing-Tang; Gu, Li-Qiang; Liu, Xiao-Lin; Qi, Jian
2017-12-01
Complex extremity trauma commonly involves both soft tissue and vascular injuries. Traditional two-stage surgical repair may delay rehabilitation and functional recovery, as well as increase the risk of infections. We report a single-stage reconstructive surgical method that repairs soft tissue defects and vascular injuries with flow-through free flaps to improve functional outcomes. Between March 2010 and December 2016 in our hospital, 5 patients with severe upper extremity trauma received single-stage reconstructive surgery, in which a flow-through anterolateral thigh free flap was applied to repair soft tissue defects and vascular injuries simultaneously. Cases of injured artery were reconstructed with the distal trunk of the descending branch of the lateral circumflex femoral artery. A segment of adjacent vein was used if there was a second artery injury. Patients were followed to evaluate their functional recoveries, and received computed tomography angiography examinations to assess peripheral circulation. Two patients had post-operative thumb necrosis; one required amputation, and the other was healed after debridement and abdominal pedicle flap repair. The other 3 patients had no major complications (infection, necrosis) to the recipient or donor sites after surgery. All the patients had achieved satisfactory functional recovery by the end of the follow-up period. Computed tomography angiography showed adequate circulation in the peripheral vessels. The success of these cases shows that one-step reconstructive surgery with flow-through anterolateral thigh free flaps can be a safe and effective treatment option for patients with complex upper extremity trauma with soft tissue defects and vascular injuries. Copyright © 2017. Published by Elsevier Ltd.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Cui, Yutian; Yang, Fei; Tolbert, Leon M.
With the increased cloud computing and digital information storage, the energy requirement of data centers keeps increasing. A high-voltage point of load (HV POL) with an input series output parallel structure is proposed to convert 400 to 1 VDC within a single stage to increase the power conversion efficiency. The symmetrical controlled half-bridge current doubler is selected as the converter topology in the HV POL. A load-dependent soft-switching method has been proposed with an auxiliary circuit that includes inductor, diode, and MOSFETs so that the hard-switching issue of typical symmetrical controlled half-bridge converters is resolved. The operation principles of themore » proposed soft-switching half-bridge current doubler have been analyzed in detail. Then, the necessity of adjusting the timing with the loading in the proposed method is analyzed based on losses, and a controller is designed to realize the load-dependent operation. A lossless RCD current sensing method is used to sense the output inductor current value in the proposed load-dependent operation. In conclusion, experimental efficiency of a hardware prototype is provided to show that the proposed method can increase the converter's efficiency in both heavy- and light-load conditions.« less
Cui, Yutian; Yang, Fei; Tolbert, Leon M.; ...
2016-06-14
With the increased cloud computing and digital information storage, the energy requirement of data centers keeps increasing. A high-voltage point of load (HV POL) with an input series output parallel structure is proposed to convert 400 to 1 VDC within a single stage to increase the power conversion efficiency. The symmetrical controlled half-bridge current doubler is selected as the converter topology in the HV POL. A load-dependent soft-switching method has been proposed with an auxiliary circuit that includes inductor, diode, and MOSFETs so that the hard-switching issue of typical symmetrical controlled half-bridge converters is resolved. The operation principles of themore » proposed soft-switching half-bridge current doubler have been analyzed in detail. Then, the necessity of adjusting the timing with the loading in the proposed method is analyzed based on losses, and a controller is designed to realize the load-dependent operation. A lossless RCD current sensing method is used to sense the output inductor current value in the proposed load-dependent operation. In conclusion, experimental efficiency of a hardware prototype is provided to show that the proposed method can increase the converter's efficiency in both heavy- and light-load conditions.« less
Prevalence of Soft Tissue Calcifications in CBCT Images of Mandibular Region
Khojastepour, Leila; Haghnegahdar, Abdolaziz; Sayar, Hamed
2017-01-01
Statement of the Problem: Most of the soft tissue calcifications within the head and neck region might not be accompanied by clinical symptoms but may indicate some pathological conditions. Purpose: The aim of this research was to determine the prevalence of soft tissue calcifications in cone beam computed tomography (CBCT) images of mandibular region. Materials and Method: In this cross sectional study the CBCT images of 602 patients including 294 men and 308 women with mean age 41.38±15.18 years were evaluated regarding the presence, anatomical location; type (single or multiple) and size of soft tissue calcification in mandibular region. All CBCT images were acquired by NewTom VGi scanner. Odds ratio and chi-square tests were used for data analysis and p< 0.05 was considered to be statistically significant. Results: 156 out of 602 patients had at least one soft tissue calcification in their mandibular region (25.9%. of studied population with mean age 51.7±18.03 years). Men showed significantly higher rate of soft tissue calcification than women (30.3% vs. 21.8%). Soft tissue calcification was predominantly seen at posterior region of the mandible (88%) and most of them were single (60.7%). The prevalence of soft tissue calcification increased with age. Most of the detected soft tissue calcifications were smaller than 3mm (90%). Conclusion: Soft tissue calcifications in mandibular area were a relatively common finding especially in posterior region and more likely to happen in men and in older age group. PMID:28620632
Khozani, Zohreh Sheikh; Bonakdari, Hossein; Zaji, Amir Hossein
2016-01-01
Two new soft computing models, namely genetic programming (GP) and genetic artificial algorithm (GAA) neural network (a combination of modified genetic algorithm and artificial neural network methods) were developed in order to predict the percentage of shear force in a rectangular channel with non-homogeneous roughness. The ability of these methods to estimate the percentage of shear force was investigated. Moreover, the independent parameters' effectiveness in predicting the percentage of shear force was determined using sensitivity analysis. According to the results, the GP model demonstrated superior performance to the GAA model. A comparison was also made between the GP program determined as the best model and five equations obtained in prior research. The GP model with the lowest error values (root mean square error ((RMSE) of 0.0515) had the best function compared with the other equations presented for rough and smooth channels as well as smooth ducts. The equation proposed for rectangular channels with rough boundaries (RMSE of 0.0642) outperformed the prior equations for smooth boundaries.
Ultrasoft Electronics for Hyperelastic Strain, Pressure, and Direct Curvature Sensing
NASA Astrophysics Data System (ADS)
Majidi, Carmel; Kramer, Rebecca; Wood, Robert
2011-03-01
Progress in soft robotics, wearable computing, and programmable matter demands a new class of ultrasoft electronics for tactile control, contact detection, and deformation mapping. This next generation of sensors will remain electrically functional under extreme deformation without influencing the natural mechanics of the host system. Ultrasoft strain and pressure sensing has previously been demonstrated with elastomer sheets (eg. PDMS, silicone rubber) embedded with microchannels of conductive liquid (mercury, eGaIn). Building on these efforts, we introduce a novel method for direct curvature sensing that registers the location and intensity of surface curvature. An elastomer sheet is embedded with micropatterned cavities and microchannels of conductive liquid. Bending the elastomer or placing it on a curved surface leads to a change in channel cross-section and a corresponding change in its electrical resistance. In contrast to conventional methods of curvature sensing, this approach does not depend on semi-rigid components or differential strain measurement. Direct curvature sensing completes the portfolio of sensing elements required to completely map hyperelastic deformation for future soft robotics and computing. NSF MRSEC DMR-0820484.
NASA Astrophysics Data System (ADS)
Kisi, Ozgur; Shiri, Jalal
2012-06-01
Estimating sediment volume carried by a river is an important issue in water resources engineering. This paper compares the accuracy of three different soft computing methods, Artificial Neural Networks (ANNs), Adaptive Neuro-Fuzzy Inference System (ANFIS), and Gene Expression Programming (GEP), in estimating daily suspended sediment concentration on rivers by using hydro-meteorological data. The daily rainfall, streamflow and suspended sediment concentration data from Eel River near Dos Rios, at California, USA are used as a case study. The comparison results indicate that the GEP model performs better than the other models in daily suspended sediment concentration estimation for the particular data sets used in this study. Levenberg-Marquardt, conjugate gradient and gradient descent training algorithms were used for the ANN models. Out of three algorithms, the Conjugate gradient algorithm was found to be better than the others.
Embedded Empiricisms in Soft Soil Technology
NASA Astrophysics Data System (ADS)
Wijeyesekera, D. C.; John, L. M. S. Alvin; Adnan, Z.
2016-07-01
Civil engineers of today are continuously challenged by innovative projects that push further the knowledge boundaries with conceptual and/or ingenious solutions leading to the realization of that once was considered impossible in the realms of geotechnology. Some of the forward developments rely on empirical methods embedded within soft soil technology and the spectral realms of engineering in its entirety. Empiricisms unlike folklore are not always shrouded in mysticism but can find scientific reasoning to justify them being adopted in design and tangible construction projects. This lecture therefore is an outline exposition of how empiricism has been integrally embedded in total empirical beginnings in the evolution of soft soil technology from the Renaissance time, through the developments of soil mechanics in the 19th century which in turn has paved the way to the rise of computational soil mechanics. Developments in computational soil mechanics has always embraced and are founded on a wide backdrop of empirical geoenvironment simulations. However, it is imperative that a competent geotechnical engineer needs postgraduate training combined with empiricism that is based on years of well- winnowed practical experience to fathom the diverseness and complexity of nature. However, experience being regarded more highly than expertise can, perhaps inadvertently, inhibit development and innovation.
Kaminaka, Akihiro; Nakano, Tamaki; Ono, Shinji; Kato, Tokinori; Yatani, Hirofumi
2015-10-01
This study evaluated changes in the horizontal and vertical dimensions of the buccal alveolar bone and soft tissue over a 1-year period following implant prosthesis. Thirty-three participants with no history of guided bone regeneration or soft tissue augmentation underwent dental implant placement with different types of connections. The dimensions of the buccal alveolar bone and soft tissue were evaluated immediately and at 1 year after prosthesis from reconstructions of cross-sectional cone-beam computed tomography images. The vertical and horizontal loss of buccal bone and soft tissue around implants with conical connections were lower than around those with external or internal connections. Statistically significant negative correlations were observed between initial horizontal bone thickness and changes in vertical bone and soft tissue height (p < .05), and between initial horizontal soft tissue thickness and the change in vertical soft tissue height (p < .05). Implants with a conical connection preserve peri-implant alveolar bone and soft tissue more effectively than other connection types. Furthermore, the initial buccal alveolar bone and soft tissue thickness around the implant platform may influence their vertical dimensional changes at 1 year after implant prosthesis. © 2014 Wiley Periodicals, Inc.
GPU-based acceleration of computations in nonlinear finite element deformation analysis.
Mafi, Ramin; Sirouspour, Shahin
2014-03-01
The physics of deformation for biological soft-tissue is best described by nonlinear continuum mechanics-based models, which then can be discretized by the FEM for a numerical solution. However, computational complexity of such models have limited their use in applications requiring real-time or fast response. In this work, we propose a graphic processing unit-based implementation of the FEM using implicit time integration for dynamic nonlinear deformation analysis. This is the most general formulation of the deformation analysis. It is valid for large deformations and strains and can account for material nonlinearities. The data-parallel nature and the intense arithmetic computations of nonlinear FEM equations make it particularly suitable for implementation on a parallel computing platform such as graphic processing unit. In this work, we present and compare two different designs based on the matrix-free and conventional preconditioned conjugate gradients algorithms for solving the FEM equations arising in deformation analysis. The speedup achieved with the proposed parallel implementations of the algorithms will be instrumental in the development of advanced surgical simulators and medical image registration methods involving soft-tissue deformation. Copyright © 2013 John Wiley & Sons, Ltd.
NASA Technical Reports Server (NTRS)
Hancock, Thomas
1993-01-01
This experiment investigated the integrity of static computer memory (floppy disk media) when exposed to the environment of low earth orbit. The experiment attempted to record soft-event upsets (bit-flips) in static computer memory. Typical conditions that exist in low earth orbit that may cause soft-event upsets include: cosmic rays, low level background radiation, charged fields, static charges, and the earth's magnetic field. Over the years several spacecraft have been affected by soft-event upsets (bit-flips), and these events have caused a loss of data or affected spacecraft guidance and control. This paper describes a commercial spin-off that is being developed from the experiment.
Song, Kyung-Jin; Kim, Gyu-Hyung; Lee, Kwang-Bok
2008-07-01
To classify comprehensively the severity of soft tissue injury for extension injuries of the lower cervical spine by magnetic resonance imaging (MRI). To investigate severity of extension injuries using a modified classification system for soft tissue injury by MRI, and to determine the possibility of predicting cord injury by determining the severity of soft tissue injury. It is difficult to diagnose extension injuries by plain radiography and computed tomography. MRI is considered to be the best method of diagnosing soft tissue injuries. The authors examined whether an MRI based diagnostic standard could be devised for extension injuries of the cervical spine. MRI was performed before surgery in 81 patients that had experienced a distractive-extension injury during the past 5 years. Severities of soft tissue injury were subdivided into 5 stages. The retropharyngeal space and the retrotracheal space were measured, and their correlations with the severity of soft tissue injury were examined, as was the relation between canal stenosis and cord injury. Cord injury developed in injuries greater than Grade III (according to our devised system) accompanied by posterior longitudinal ligament rupture (P < 0.01). As the severity of soft tissue injury increased, the cord signal change increased (P < 0.01), the retropharyngeal space and the retrotracheal space increased, and swelling severity in each stage were statistically significant (P < 0.01). In canal stenosis patients, soft tissue damage and cord injury were not found to be associated (P = 0.45). In cases of distractive-extension injury, levels of soft tissue injury were determined accurately by MRI. Moreover, the severity of soft tissue injury was found to be closely associated with the development of cord injury.
Coarse-Grained Models for Protein-Cell Membrane Interactions
Bradley, Ryan; Radhakrishnan, Ravi
2015-01-01
The physiological properties of biological soft matter are the product of collective interactions, which span many time and length scales. Recent computational modeling efforts have helped illuminate experiments that characterize the ways in which proteins modulate membrane physics. Linking these models across time and length scales in a multiscale model explains how atomistic information propagates to larger scales. This paper reviews continuum modeling and coarse-grained molecular dynamics methods, which connect atomistic simulations and single-molecule experiments with the observed microscopic or mesoscale properties of soft-matter systems essential to our understanding of cells, particularly those involved in sculpting and remodeling cell membranes. PMID:26613047
Modification of Hazen's equation in coarse grained soils by soft computing techniques
NASA Astrophysics Data System (ADS)
Kaynar, Oguz; Yilmaz, Isik; Marschalko, Marian; Bednarik, Martin; Fojtova, Lucie
2013-04-01
Hazen first proposed a Relationship between coefficient of permeability (k) and effective grain size (d10) was first proposed by Hazen, and it was then extended by some other researchers. However many attempts were done for estimation of k, correlation coefficients (R2) of the models were generally lower than ~0.80 and whole grain size distribution curves were not included in the assessments. Soft computing techniques such as; artificial neural networks, fuzzy inference systems, genetic algorithms, etc. and their hybrids are now being successfully used as an alternative tool. In this study, use of some soft computing techniques such as Artificial Neural Networks (ANNs) (MLP, RBF, etc.) and Adaptive Neuro-Fuzzy Inference System (ANFIS) for prediction of permeability of coarse grained soils was described, and Hazen's equation was then modificated. It was found that the soft computing models exhibited high performance in prediction of permeability coefficient. However four different kinds of ANN algorithms showed similar prediction performance, results of MLP was found to be relatively more accurate than RBF models. The most reliable prediction was obtained from ANFIS model.
Regularization of soft-X-ray imaging in the DIII-D tokamak
Wingen, A.; Shafer, M. W.; Unterberg, E. A.; ...
2015-03-02
We developed an image inversion scheme for the soft X-ray imaging system (SXRIS) diagnostic at the DIII-D tokamak in order to obtain the local soft X-ray emission at a poloidal cross-section from the spatially line-integrated image taken by the SXRIS camera. The scheme uses the Tikhonov regularization method since the inversion problem is generally ill-posed. The regularization technique uses the generalized singular value decomposition to determine a solution that depends on a free regularization parameter. The latter has to be chosen carefully, and the so called {\\it L-curve} method to find the optimum regularization parameter is outlined. A representative testmore » image is used to study the properties of the inversion scheme with respect to inversion accuracy, amount/strength of regularization, image noise and image resolution. Moreover, the optimum inversion parameters are identified, while the L-curve method successfully computes the optimum regularization parameter. Noise is found to be the most limiting issue, but sufficient regularization is still possible at noise to signal ratios up to 10%-15%. Finally, the inversion scheme is applied to measured SXRIS data and the line-integrated SXRIS image is successfully inverted.« less
Darwinian Spacecraft: Soft Computing Strategies Breeding Better, Faster Cheaper
NASA Technical Reports Server (NTRS)
Noever, David A.; Baskaran, Subbiah
1999-01-01
Computers can create infinite lists of combinations to try to solve a particular problem, a process called "soft-computing." This process uses statistical comparables, neural networks, genetic algorithms, fuzzy variables in uncertain environments, and flexible machine learning to create a system which will allow spacecraft to increase robustness, and metric evaluation. These concepts will allow for the development of a spacecraft which will allow missions to be performed at lower costs.
Dental MRI using wireless intraoral coils
NASA Astrophysics Data System (ADS)
Ludwig, Ute; Eisenbeiss, Anne-Katrin; Scheifele, Christian; Nelson, Katja; Bock, Michael; Hennig, Jürgen; von Elverfeldt, Dominik; Herdt, Olga; Flügge, Tabea; Hövener, Jan-Bernd
2016-03-01
Currently, the gold standard for dental imaging is projection radiography or cone-beam computed tomography (CBCT). These methods are fast and cost-efficient, but exhibit poor soft tissue contrast and expose the patient to ionizing radiation (X-rays). The need for an alternative imaging modality e.g. for soft tissue management has stimulated a rising interest in dental magnetic resonance imaging (MRI) which provides superior soft tissue contrast. Compared to X-ray imaging, however, so far the spatial resolution of MRI is lower and the scan time is longer. In this contribution, we describe wireless, inductively-coupled intraoral coils whose local sensitivity enables high resolution MRI of dental soft tissue. In comparison to CBCT, a similar image quality with complementary contrast was obtained ex vivo. In-vivo, a voxel size of the order of 250•250•500 μm3 was achieved in 4 min only. Compared to dental MRI acquired with clinical equipment, the quality of the images was superior in the sensitive volume of the coils and is expected to improve the planning of interventions and monitoring thereafter. This method may enable a more accurate dental diagnosis and avoid unnecessary interventions, improving patient welfare and bringing MRI a step closer to becoming a radiation-free alternative for dental imaging.
Sommer, Gerhard; Eder, Maximilian; Kovacs, Laszlo; Pathak, Heramb; Bonitz, Lars; Mueller, Christoph; Regitnig, Peter; Holzapfel, Gerhard A
2013-11-01
A preoperative simulation of soft tissue deformations during plastic and reconstructive surgery is desirable to support the surgeon's planning and to improve surgical outcomes. The current development of constitutive adipose tissue models, for the implementation in multilayer computational frameworks for the simulation of human soft tissue deformations, has proved difficult because knowledge of the required mechanical parameters of fat tissue is limited. Therefore, for the first time, human abdominal adipose tissues were mechanically investigated by biaxial tensile and triaxial shear tests. The results of this study suggest that human abdominal adipose tissues under quasi-static and dynamic multiaxial loadings can be characterized as a nonlinear, anisotropic and viscoelastic soft biological material. The nonlinear and anisotropic features are consequences of the material's collagenous microstructure. The aligned collagenous septa observed in histological investigations causes the anisotropy of the tissue. A hyperelastic model used in this study was appropriate to represent the quasi-static multiaxial mechanical behavior of fat tissue. The constitutive parameters are intended to serve as a basis for soft tissue simulations using the finite element method, which is an apparent method for obtaining promising results in the field of plastic and reconstructive surgery. Copyright © 2013 Acta Materialia Inc. Published by Elsevier Ltd. All rights reserved.
USDA-ARS?s Scientific Manuscript database
One of the most important and least understood properties of carbohydrates is their conformational profile in solution. The study of carbohydrates in solution is a most difficult computational problem, a result of the many soft conformational variables (hydroxyl groups) inherent in the structures of...
Experimental investigation of halogen-bond hard-soft acid-base complementarity.
Riel, Asia Marie S; Jessop, Morly J; Decato, Daniel A; Massena, Casey J; Nascimento, Vinicius R; Berryman, Orion B
2017-04-01
The halogen bond (XB) is a topical noncovalent interaction of rapidly increasing importance. The XB employs a `soft' donor atom in comparison to the `hard' proton of the hydrogen bond (HB). This difference has led to the hypothesis that XBs can form more favorable interactions with `soft' bases than HBs. While computational studies have supported this suggestion, solution and solid-state data are lacking. Here, XB soft-soft complementarity is investigated with a bidentate receptor that shows similar associations with neutral carbonyls and heavy chalcogen analogs. The solution speciation and XB soft-soft complementarity is supported by four crystal structures containing neutral and anionic soft Lewis bases.
Martín, Andrés; Barrientos, Antonio; Del Cerro, Jaime
2018-03-22
This article presents a new method to solve the inverse kinematics problem of hyper-redundant and soft manipulators. From an engineering perspective, this kind of robots are underdetermined systems. Therefore, they exhibit an infinite number of solutions for the inverse kinematics problem, and to choose the best one can be a great challenge. A new algorithm based on the cyclic coordinate descent (CCD) and named as natural-CCD is proposed to solve this issue. It takes its name as a result of generating very harmonious robot movements and trajectories that also appear in nature, such as the golden spiral. In addition, it has been applied to perform continuous trajectories, to develop whole-body movements, to analyze motion planning in complex environments, and to study fault tolerance, even for both prismatic and rotational joints. The proposed algorithm is very simple, precise, and computationally efficient. It works for robots either in two or three spatial dimensions and handles a large amount of degrees-of-freedom. Because of this, it is aimed to break down barriers between discrete hyper-redundant and continuum soft robots.
Learning the inverse kinetics of an octopus-like manipulator in three-dimensional space.
Giorelli, M; Renda, F; Calisti, M; Arienti, A; Ferri, G; Laschi, C
2015-05-13
This work addresses the inverse kinematics problem of a bioinspired octopus-like manipulator moving in three-dimensional space. The bioinspired manipulator has a conical soft structure that confers the ability of twirling around objects as a real octopus arm does. Despite the simple design, the soft conical shape manipulator driven by cables is described by nonlinear differential equations, which are difficult to solve analytically. Since exact solutions of the equations are not available, the Jacobian matrix cannot be calculated analytically and the classical iterative methods cannot be used. To overcome the intrinsic problems of methods based on the Jacobian matrix, this paper proposes a neural network learning the inverse kinematics of a soft octopus-like manipulator driven by cables. After the learning phase, a feed-forward neural network is able to represent the relation between manipulator tip positions and forces applied to the cables. Experimental results show that a desired tip position can be achieved in a short time, since heavy computations are avoided, with a degree of accuracy of 8% relative average error with respect to the total arm length.
Ichikawa, Kazunori; Kashio, Akinori; Mori, Harushi; Ochi, Atushi; Karino, Shotaro; Sakamoto, Takashi; Kakigi, Akinobu; Yamasoba, Tatsuya
2014-04-01
To develop a new method to determine the presence of intracochlear ossification and/or fibrosis in cochlear implantation candidates with bilateral profound deafness following meningitis. Diagnostic test assessment. A university hospital. This study involved 15 ears from 13 patients with profound deafness following meningitis who underwent cochlear implantation. These ears showed normal structures, soft tissue, partial bony occlusion, and complete bony occlusion in 4, 3, 2, and 6 ears, respectively. We measured radiodensity in Hounsfield units (HU) using 0.5-mm-thick axial high-resolution computed tomography image slices at 3 different levels in the basal turn, the fenestration, and inferior and ascending segment sites, located along the electrode-insertion path. Pixel-level analysis on the DICOM viewer yielded actual computed tomography values of intracochlear soft tissues by eliminating the partial volume effect. The values were compared with the intraoperative findings. Values for ossification (n = 12) ranged from +547 HU to +1137 HU; for fibrosis (n = 11), from +154 HU to +574 HU; and for fluid (n = 22), from -49 HU to +255 HU. From these values, we developed 2 presets of window width (WW) and window level (WL): (1) WW: 1800, WL: 1100 (200 HU to 2000 HU) and (2) WW: 1500, WL: 1250 (500 HU to 2000 HU). The results using these 2 presets corresponded well to the intraoperative findings. Our new method is easy and feasible for preoperative determination of the presence of cochlear ossification and/or fibrosis that develops following meningitis.
Soft-tissue facial characteristics of attractive Chinese men compared to normal men
Wu, Feng; Li, Junfang; He, Hong; Huang, Na; Tang, Youchao; Wang, Yuanqing
2015-01-01
Objective: To compare the facial characteristics of attractive Chinese men with those of reference men. Materials and Methods: The three-dimensional coordinates of 50 facial landmarks were collected in 40 healthy reference men and in 40 “attractive” men, soft tissue facial angles, distances, areas, and volumes were computed and compared using analysis of variance. Results: When compared with reference men, attractive men shared several similar facial characteristics: relatively large forehead, reduced mandible, and rounded face. They had a more acute soft tissue profile, an increased upper facial width and middle facial depth, larger mouth, and more voluminous lips than reference men. Conclusions: Attractive men had several facial characteristics suggesting babyness. Nonetheless, each group of men was characterized by a different development of these features. Esthetic reference values can be a useful tool for clinicians, but should always consider the characteristics of individual faces. PMID:26221357
Buytaert, Jan A N; Salih, Wasil H M; Dierick, Manual; Jacobs, Patric; Dirckx, Joris J J
2011-12-01
In order to improve realism in middle ear (ME) finite-element modeling (FEM), comprehensive and precise morphological data are needed. To date, micro-scale X-ray computed tomography (μCT) recordings have been used as geometric input data for FEM models of the ME ossicles. Previously, attempts were made to obtain these data on ME soft tissue structures as well. However, due to low X-ray absorption of soft tissue, quality of these images is limited. Another popular approach is using histological sections as data for 3D models, delivering high in-plane resolution for the sections, but the technique is destructive in nature and registration of the sections is difficult. We combine data from high-resolution μCT recordings with data from high-resolution orthogonal-plane fluorescence optical-sectioning microscopy (OPFOS), both obtained on the same gerbil specimen. State-of-the-art μCT delivers high-resolution data on the 3D shape of ossicles and other ME bony structures, while the OPFOS setup generates data of unprecedented quality both on bone and soft tissue ME structures. Each of these techniques is tomographic and non-destructive and delivers sets of automatically aligned virtual sections. The datasets coming from different techniques need to be registered with respect to each other. By combining both datasets, we obtain a complete high-resolution morphological model of all functional components in the gerbil ME. The resulting 3D model can be readily imported in FEM software and is made freely available to the research community. In this paper, we discuss the methods used, present the resulting merged model, and discuss the morphological properties of the soft tissue structures, such as muscles and ligaments.
A k-space method for large-scale models of wave propagation in tissue.
Mast, T D; Souriau, L P; Liu, D L; Tabei, M; Nachman, A I; Waag, R C
2001-03-01
Large-scale simulation of ultrasonic pulse propagation in inhomogeneous tissue is important for the study of ultrasound-tissue interaction as well as for development of new imaging methods. Typical scales of interest span hundreds of wavelengths; most current two-dimensional methods, such as finite-difference and finite-element methods, are unable to compute propagation on this scale with the efficiency needed for imaging studies. Furthermore, for most available methods of simulating ultrasonic propagation, large-scale, three-dimensional computations of ultrasonic scattering are infeasible. Some of these difficulties have been overcome by previous pseudospectral and k-space methods, which allow substantial portions of the necessary computations to be executed using fast Fourier transforms. This paper presents a simplified derivation of the k-space method for a medium of variable sound speed and density; the derivation clearly shows the relationship of this k-space method to both past k-space methods and pseudospectral methods. In the present method, the spatial differential equations are solved by a simple Fourier transform method, and temporal iteration is performed using a k-t space propagator. The temporal iteration procedure is shown to be exact for homogeneous media, unconditionally stable for "slow" (c(x) < or = c0) media, and highly accurate for general weakly scattering media. The applicability of the k-space method to large-scale soft tissue modeling is shown by simulating two-dimensional propagation of an incident plane wave through several tissue-mimicking cylinders as well as a model chest wall cross section. A three-dimensional implementation of the k-space method is also employed for the example problem of propagation through a tissue-mimicking sphere. Numerical results indicate that the k-space method is accurate for large-scale soft tissue computations with much greater efficiency than that of an analogous leapfrog pseudospectral method or a 2-4 finite difference time-domain method. However, numerical results also indicate that the k-space method is less accurate than the finite-difference method for a high contrast scatterer with bone-like properties, although qualitative results can still be obtained by the k-space method with high efficiency. Possible extensions to the method, including representation of absorption effects, absorbing boundary conditions, elastic-wave propagation, and acoustic nonlinearity, are discussed.
A New Soft Computing Method for K-Harmonic Means Clustering.
Yeh, Wei-Chang; Jiang, Yunzhi; Chen, Yee-Fen; Chen, Zhe
2016-01-01
The K-harmonic means clustering algorithm (KHM) is a new clustering method used to group data such that the sum of the harmonic averages of the distances between each entity and all cluster centroids is minimized. Because it is less sensitive to initialization than K-means (KM), many researchers have recently been attracted to studying KHM. In this study, the proposed iSSO-KHM is based on an improved simplified swarm optimization (iSSO) and integrates a variable neighborhood search (VNS) for KHM clustering. As evidence of the utility of the proposed iSSO-KHM, we present extensive computational results on eight benchmark problems. From the computational results, the comparison appears to support the superiority of the proposed iSSO-KHM over previously developed algorithms for all experiments in the literature.
Gebremariam, Mekdes K; Chinapaw, Mai J; Bringolf-Isler, Bettina; Bere, Elling; Kovacs, Eva; Verloigne, Maïté; Stok, F Marijn; Manios, Yannis; Brug, Johannes; Lien, Nanna
2017-01-01
The aim of the present study was to explore if children who spend more time on screen-based sedentary behaviors (i.e.TV viewing and computer use) drink more sugar-sweetened soft drinks. The study also assessed whether these associations were independent of individual and home environmental correlates of soft drink consumption and whether they were moderated by parental education. Data were collected from 7886 children participating in the EuropeaN Energy balance Research to prevent excessive weight Gain among Youth (ENERGY) survey conducted in eight European countries. Self-report questionnaires were used. Multilevel linear regression analyses with soft drink consumption as dependent variable, TV viewing and computer use as independent variables and age, gender, parental education, attitude towards soft drinks, self-efficacy, parental modelling, parental rules and home availability of soft drinks as covariates were conducted. Further interactions were tested to explore if these associations were moderated by parental education. Country-specific analyses were conducted. In six of the eight included countries, a significant positive association was observed between TV viewing (min/day) and soft drink consumption (ml/day), independent of individual and home environmental correlates of soft drink consumption (B = 0.46 (0.26-0.66) in Greece, B = 0.77 (0.36-1.17) in Norway, B = 0.82 (0.12-1.51) in Hungary, B = 1.06 (0.67-1.46) in Spain, B = 1.21 (0.67-1.74) in Belgium and B = 1.49 (0.72-2.27) in Switzerland). There was no significant association between computer use and soft drink consumption in six of the eight included countries in the final models. Moderation effects of parental education in the association between TV viewing and soft drink consumption were found in Norway and Hungary, the association being stronger among those with low parental education. TV viewing appears to be independently associated with soft drink consumption and this association was moderated by parental education in two countries only. Reducing TV time might therefore favorably impact soft drink consumption.
Autocorrelation techniques for soft photogrammetry
NASA Astrophysics Data System (ADS)
Yao, Wu
In this thesis research is carried out on image processing, image matching searching strategies, feature type and image matching, and optimal window size in image matching. To make comparisons, the soft photogrammetry package SoftPlotter is used. Two aerial photographs from the Iowa State University campus high flight 94 are scanned into digital format. In order to create a stereo model from them, interior orientation, single photograph rectification and stereo rectification are done. Two new image matching methods, multi-method image matching (MMIM) and unsquare window image matching are developed and compared. MMIM is used to determine the optimal window size in image matching. Twenty four check points from four different types of ground features are used for checking the results from image matching. Comparison between these four types of ground feature shows that the methods developed here improve the speed and the precision of image matching. A process called direct transformation is described and compared with the multiple steps in image processing. The results from image processing are consistent with those from SoftPlotter. A modified LAN image header is developed and used to store the information about the stereo model and image matching. A comparison is also made between cross correlation image matching (CCIM), least difference image matching (LDIM) and least square image matching (LSIM). The quality of image matching in relation to ground features are compared using two methods developed in this study, the coefficient surface for CCIM and the difference surface for LDIM. To reduce the amount of computation in image matching, the best-track searching algorithm, developed in this research, is used instead of the whole range searching algorithm.
The hierarchical expert tuning of PID controllers using tools of soft computing.
Karray, F; Gueaieb, W; Al-Sharhan, S
2002-01-01
We present soft computing-based results pertaining to the hierarchical tuning process of PID controllers located within the control loop of a class of nonlinear systems. The results are compared with PID controllers implemented either in a stand alone scheme or as a part of conventional gain scheduling structure. This work is motivated by the increasing need in the industry to design highly reliable and efficient controllers for dealing with regulation and tracking capabilities of complex processes characterized by nonlinearities and possibly time varying parameters. The soft computing-based controllers proposed are hybrid in nature in that they integrate within a well-defined hierarchical structure the benefits of hard algorithmic controllers with those having supervisory capabilities. The controllers proposed also have the distinct features of learning and auto-tuning without the need for tedious and computationally extensive online systems identification schemes.
Estimators of The Magnitude-Squared Spectrum and Methods for Incorporating SNR Uncertainty
Lu, Yang; Loizou, Philipos C.
2011-01-01
Statistical estimators of the magnitude-squared spectrum are derived based on the assumption that the magnitude-squared spectrum of the noisy speech signal can be computed as the sum of the (clean) signal and noise magnitude-squared spectra. Maximum a posterior (MAP) and minimum mean square error (MMSE) estimators are derived based on a Gaussian statistical model. The gain function of the MAP estimator was found to be identical to the gain function used in the ideal binary mask (IdBM) that is widely used in computational auditory scene analysis (CASA). As such, it was binary and assumed the value of 1 if the local SNR exceeded 0 dB, and assumed the value of 0 otherwise. By modeling the local instantaneous SNR as an F-distributed random variable, soft masking methods were derived incorporating SNR uncertainty. The soft masking method, in particular, which weighted the noisy magnitude-squared spectrum by the a priori probability that the local SNR exceeds 0 dB was shown to be identical to the Wiener gain function. Results indicated that the proposed estimators yielded significantly better speech quality than the conventional MMSE spectral power estimators, in terms of yielding lower residual noise and lower speech distortion. PMID:21886543
Souris, Kevin; Lee, John Aldo; Sterpin, Edmond
2016-04-01
Accuracy in proton therapy treatment planning can be improved using Monte Carlo (MC) simulations. However the long computation time of such methods hinders their use in clinical routine. This work aims to develop a fast multipurpose Monte Carlo simulation tool for proton therapy using massively parallel central processing unit (CPU) architectures. A new Monte Carlo, called MCsquare (many-core Monte Carlo), has been designed and optimized for the last generation of Intel Xeon processors and Intel Xeon Phi coprocessors. These massively parallel architectures offer the flexibility and the computational power suitable to MC methods. The class-II condensed history algorithm of MCsquare provides a fast and yet accurate method of simulating heavy charged particles such as protons, deuterons, and alphas inside voxelized geometries. Hard ionizations, with energy losses above a user-specified threshold, are simulated individually while soft events are regrouped in a multiple scattering theory. Elastic and inelastic nuclear interactions are sampled from ICRU 63 differential cross sections, thereby allowing for the computation of prompt gamma emission profiles. MCsquare has been benchmarked with the gate/geant4 Monte Carlo application for homogeneous and heterogeneous geometries. Comparisons with gate/geant4 for various geometries show deviations within 2%-1 mm. In spite of the limited memory bandwidth of the coprocessor simulation time is below 25 s for 10(7) primary 200 MeV protons in average soft tissues using all Xeon Phi and CPU resources embedded in a single desktop unit. MCsquare exploits the flexibility of CPU architectures to provide a multipurpose MC simulation tool. Optimized code enables the use of accurate MC calculation within a reasonable computation time, adequate for clinical practice. MCsquare also simulates prompt gamma emission and can thus be used also for in vivo range verification.
Classical and all-floating FETI methods for the simulation of arterial tissues
Augustin, Christoph M.; Holzapfel, Gerhard A.; Steinbach, Olaf
2015-01-01
High-resolution and anatomically realistic computer models of biological soft tissues play a significant role in the understanding of the function of cardiovascular components in health and disease. However, the computational effort to handle fine grids to resolve the geometries as well as sophisticated tissue models is very challenging. One possibility to derive a strongly scalable parallel solution algorithm is to consider finite element tearing and interconnecting (FETI) methods. In this study we propose and investigate the application of FETI methods to simulate the elastic behavior of biological soft tissues. As one particular example we choose the artery which is – as most other biological tissues – characterized by anisotropic and nonlinear material properties. We compare two specific approaches of FETI methods, classical and all-floating, and investigate the numerical behavior of different preconditioning techniques. In comparison to classical FETI, the all-floating approach has not only advantages concerning the implementation but in many cases also concerning the convergence of the global iterative solution method. This behavior is illustrated with numerical examples. We present results of linear elastic simulations to show convergence rates, as expected from the theory, and results from the more sophisticated nonlinear case where we apply a well-known anisotropic model to the realistic geometry of an artery. Although the FETI methods have a great applicability on artery simulations we will also discuss some limitations concerning the dependence on material parameters. PMID:26751957
Active Surfaces and Interfaces of Soft Materials
NASA Astrophysics Data System (ADS)
Wang, Qiming
A variety of intriguing surface patterns have been observed on developing natural systems, ranging from corrugated surface of white blood cells at nanometer scales to wrinkled dog skins at millimeter scales. To mimetically harness functionalities of natural morphologies, artificial transformative skin systems by using soft active materials have been rationally designed to generate versatile patterns for a variety of engineering applications. The study of the mechanics and design of these dynamic surface patterns on soft active materials are both physically interesting and technologically important. This dissertation starts with studying abundant surface patterns in Nature by constructing a unified phase diagram of surface instabilities on soft materials with minimum numbers of physical parameters. Guided by this integrated phase diagram, an electroactive system is designed to investigate a variety of electrically-induced surface instabilities of elastomers, including electro-creasing, electro-cratering, electro-wrinkling and electro-cavitation. Combing experimental, theoretical and computational methods, the initiation, evolution and transition of these instabilities are analyzed. To apply these dynamic surface instabilities to serving engineering and biology, new techniques of Dynamic Electrostatic Lithography and electroactive anti-biofouling are demonstrated.
Mutual capacitance of liquid conductors in deformable tactile sensing arrays
NASA Astrophysics Data System (ADS)
Li, Bin; Fontecchio, Adam K.; Visell, Yon
2016-01-01
Advances in highly deformable electronics are needed in order to enable emerging categories of soft computing devices ranging from wearable electronics, to medical devices, and soft robotic components. The combination of highly elastic substrates with intrinsically stretchable conductors holds the promise of enabling electronic sensors that can conform to curved objects, reconfigurable displays, or soft biological tissues, including the skin. Here, we contribute sensing principles for tactile (mechanical image) sensors based on very low modulus polymer substrates with embedded liquid metal microfluidic arrays. The sensors are fabricated using a single-step casting method that utilizes fine nylon filaments to produce arrays of cylindrical channels on two layers. The liquid metal (gallium indium alloy) conductors that fill these channels readily adopt the shape of the embedding membrane, yielding levels of deformability greater than 400%, due to the use of soft polymer substrates. We modeled the sensor performance using electrostatic theory and continuum mechanics, yielding excellent agreement with experiments. Using a matrix-addressed capacitance measurement technique, we are able to resolve strain distributions with millimeter resolution over areas of several square centimeters.
Mutual capacitance of liquid conductors in deformable tactile sensing arrays
DOE Office of Scientific and Technical Information (OSTI.GOV)
Li, Bin; Fontecchio, Adam K.; Visell, Yon
2016-01-04
Advances in highly deformable electronics are needed in order to enable emerging categories of soft computing devices ranging from wearable electronics, to medical devices, and soft robotic components. The combination of highly elastic substrates with intrinsically stretchable conductors holds the promise of enabling electronic sensors that can conform to curved objects, reconfigurable displays, or soft biological tissues, including the skin. Here, we contribute sensing principles for tactile (mechanical image) sensors based on very low modulus polymer substrates with embedded liquid metal microfluidic arrays. The sensors are fabricated using a single-step casting method that utilizes fine nylon filaments to produce arraysmore » of cylindrical channels on two layers. The liquid metal (gallium indium alloy) conductors that fill these channels readily adopt the shape of the embedding membrane, yielding levels of deformability greater than 400%, due to the use of soft polymer substrates. We modeled the sensor performance using electrostatic theory and continuum mechanics, yielding excellent agreement with experiments. Using a matrix-addressed capacitance measurement technique, we are able to resolve strain distributions with millimeter resolution over areas of several square centimeters.« less
The interaction between a solid body and viscous fluid by marker-and-cell method
NASA Technical Reports Server (NTRS)
Cheng, R. Y. K.
1976-01-01
A computational method for solving nonlinear problems relating to impact and penetration of a rigid body into a fluid type medium is presented. The numerical techniques, based on the Marker-and-Cell method, gives the pressure and velocity of the flow field. An important feature in this method is that the force and displacement of the rigid body interacting with the fluid during the impact and sinking phases are evaluated from the boundary stresses imposed by the fluid on the rigid body. A sample problem of low velocity penetration of a rigid block into still water is solved by this method. The computed time histories of the acceleration, pressure, and displacement of the block show food agreement with experimental measurements. A sample problem of high velocity impact of a rigid block into soft clay is also presented.
Dimensionality and noise in energy selective x-ray imaging
Alvarez, Robert E.
2013-01-01
Purpose: To develop and test a method to quantify the effect of dimensionality on the noise in energy selective x-ray imaging. Methods: The Cramèr-Rao lower bound (CRLB), a universal lower limit of the covariance of any unbiased estimator, is used to quantify the noise. It is shown that increasing dimensionality always increases, or at best leaves the same, the variance. An analytic formula for the increase in variance in an energy selective x-ray system is derived. The formula is used to gain insight into the dependence of the increase in variance on the properties of the additional basis functions, the measurement noise covariance, and the source spectrum. The formula is also used with computer simulations to quantify the dependence of the additional variance on these factors. Simulated images of an object with three materials are used to demonstrate the trade-off of increased information with dimensionality and noise. The images are computed from energy selective data with a maximum likelihood estimator. Results: The increase in variance depends most importantly on the dimension and on the properties of the additional basis functions. With the attenuation coefficients of cortical bone, soft tissue, and adipose tissue as the basis functions, the increase in variance of the bone component from two to three dimensions is 1.4 × 103. With the soft tissue component, it is 2.7 × 104. If the attenuation coefficient of a high atomic number contrast agent is used as the third basis function, there is only a slight increase in the variance from two to three basis functions, 1.03 and 7.4 for the bone and soft tissue components, respectively. The changes in spectrum shape with beam hardening also have a substantial effect. They increase the variance by a factor of approximately 200 for the bone component and 220 for the soft tissue component as the soft tissue object thickness increases from 1 to 30 cm. Decreasing the energy resolution of the detectors increases the variance of the bone component markedly with three dimension processing, approximately a factor of 25 as the resolution decreases from 100 to 3 bins. The increase with two dimension processing for adipose tissue is a factor of two and with the contrast agent as the third material for two or three dimensions is also a factor of two for both components. The simulated images show that a maximum likelihood estimator can be used to process energy selective x-ray data to produce images with noise close to the CRLB. Conclusions: The method presented can be used to compute the effects of the object attenuation coefficients and the x-ray system properties on the relationship of dimensionality and noise in energy selective x-ray imaging systems. PMID:24320442
Deegan, Timothy; Owen, Rebecca; Holt, Tanya; Fielding, Andrew; Biggs, Jennifer; Parfitt, Matthew; Coates, Alicia; Roberts, Lisa
2015-02-01
This investigation aimed to assess the consistency and accuracy of radiation therapists (RTs) performing cone beam computed tomography (CBCT) alignment to fiducial markers (FMs) (CBCTFM ) and the soft tissue prostate (CBCTST ). Six patients receiving prostate radiation therapy underwent daily CBCTs. Manual alignment of CBCTFM and CBCTST was performed by three RTs. Inter-observer agreement was assessed using a modified Bland-Altman analysis for each alignment method. Clinically acceptable 95% limits of agreement with the mean (LoAmean ) were defined as ±2.0 mm for CBCTFM and ±3.0 mm for CBCTST . Differences between CBCTST alignment and the observer-averaged CBCTFM (AvCBCTFM ) alignment were analysed. Clinically acceptable 95% LoA were defined as ±3.0 mm for the comparison of CBCTST and AvCBCTFM . CBCTFM and CBCTST alignments were performed for 185 images. The CBCTFM 95% LoAmean were within ±2.0 mm in all planes. CBCTST 95% LoAmean were within ±3.0 mm in all planes. Comparison of CBCTST with AvCBCTFM resulted in 95% LoA of -4.9 to 2.6, -1.6 to 2.5 and -4.7 to 1.9 mm in the superior-inferior, left-right and anterior-posterior planes, respectively. Significant differences were found between soft tissue alignment and the predicted FM position. FMs are useful in reducing inter-observer variability compared with soft tissue alignment. Consideration needs to be given to margin design when using soft tissue matching due to increased inter-observer variability. This study highlights some of the complexities of soft tissue guidance for prostate radiation therapy. © 2014 The Royal Australian and New Zealand College of Radiologists.
Mukherjee, Anirban; Bal, Chandrasekhar; Tripathi, Madhavi; Das, Chandan Jyoti; Shamim, Shamim Ahmed
2017-01-01
A 44-year-old female with known primary myelofibrosis presented with shortness of breath. High Resolution Computed Tomography thorax revealed large heterogeneously enhancing extraparenchymal soft tissue density mass involving bilateral lung fields. F-18-fluorodeoxyglucose (FDG) positron emission tomography/computed tomography revealed mildly FDG avid soft tissue density mass with specks of calcification involving bilateral lung fields, liver, and spleen. Subsequent histopathologic evaluation from the right lung mass was suggestive of extramedullary hematopoesis. PMID:28533647
Compact "diode-based" multi-energy soft x-ray diagnostic for NSTX.
Tritz, K; Clayton, D J; Stutman, D; Finkenthal, M
2012-10-01
A novel and compact, diode-based, multi-energy soft x-ray (ME-SXR) diagnostic has been developed for the National Spherical Tokamak Experiment. The new edge ME-SXR system tested on NSTX consists of a set of vertically stacked diode arrays, each viewing the plasma tangentially through independent pinholes and filters providing an overlapping view of the plasma midplane which allows simultaneous SXR measurements with coarse sub-sampling of the x-ray spectrum. Using computed x-ray spectral emission data, combinations of filters can provide fast (>10 kHz) measurements of changes in the electron temperature and density profiles providing a method to "fill-in" the gaps of the multi-point Thomson scattering system.
Enhanced performance of microfluidic soft pressure sensors with embedded solid microspheres
NASA Astrophysics Data System (ADS)
Shin, Hee-Sup; Ryu, Jaiyoung; Majidi, Carmel; Park, Yong-Lae
2016-02-01
The cross-sectional geometry of an embedded microchannel influences the electromechanical response of a soft microfluidic sensor to applied surface pressure. When a pressure is exerted on the surface of the sensor deforming the soft structure, the cross-sectional area of the embedded channel filled with a conductive fluid decreases, increasing the channel’s electrical resistance. This electromechanical coupling can be tuned by adding solid microspheres into the channel. In order to determine the influence of microspheres, we use both analytic and computational methods to predict the pressure responses of soft microfluidic sensors with two different channel cross-sections: a square and an equilateral triangular. The analytical models were derived from contact mechanics in which microspheres were regarded as spherical indenters, and finite element analysis (FEA) was used for simulation. For experimental validation, sensor samples with the two different channel cross-sections were prepared and tested. For comparison, the sensor samples were tested both with and without microspheres. All three results from the analytical models, the FEA simulations, and the experiments showed reasonable agreement confirming that the multi-material soft structure significantly improved its pressure response in terms of both linearity and sensitivity. The embedded solid particles enhanced the performance of soft sensors while maintaining their flexible and stretchable mechanical characteristic. We also provide analytical and experimental analyses of hysteresis of microfluidic soft sensors considering a resistive force to the shape recovery of the polymer structure by the embedded viscous fluid.
High energy x-ray phase contrast CT using glancing-angle grating interferometers
DOE Office of Scientific and Technical Information (OSTI.GOV)
Sarapata, A., E-mail: adrian.sarapata@tum.de; Stayman, J. W.; Siewerdsen, J. H.
Purpose: The authors present initial progress toward a clinically compatible x-ray phase contrast CT system, using glancing-angle x-ray grating interferometry to provide high contrast soft tissue images at estimated by computer simulation dose levels comparable to conventional absorption based CT. Methods: DPC-CT scans of a joint phantom and of soft tissues were performed in order to answer several important questions from a clinical setup point of view. A comparison between high and low fringe visibility systems is presented. The standard phase stepping method was compared with sliding window interlaced scanning. Using estimated dose values obtained with a Monte-Carlo code themore » authors studied the dependence of the phase image contrast on exposure time and dose. Results: Using a glancing angle interferometer at high x-ray energy (∼45 keV mean value) in combination with a conventional x-ray tube the authors achieved fringe visibility values of nearly 50%, never reported before. High fringe visibility is shown to be an indispensable parameter for a potential clinical scanner. Sliding window interlaced scanning proved to have higher SNRs and CNRs in a region of interest and to also be a crucial part of a low dose CT system. DPC-CT images of a soft tissue phantom at exposures in the range typical for absorption based CT of musculoskeletal extremities were obtained. Assuming a human knee as the CT target, good soft tissue phase contrast could be obtained at an estimated absorbed dose level around 8 mGy, similar to conventional CT. Conclusions: DPC-CT with glancing-angle interferometers provides improved soft tissue contrast over absorption CT even at clinically compatible dose levels (estimated by a Monte-Carlo computer simulation). Further steps in image processing, data reconstruction, and spectral matching could make the technique fully clinically compatible. Nevertheless, due to its increased scan time and complexity the technique should be thought of not as replacing, but as complimentary to conventional CT, to be used in specific applications.« less
Modeling Human Behavior with Fuzzy and Soft Computing Methods
2017-12-13
REPORT DOCUMENTATION PAGE Form Approved OMB No. 0704-0188 The public reporting burden for this collection of information is estimated to average 1...completing and reviewing the collection of information . Send comments regarding this burden estimate or any other aspect of this collection of... information , including suggestions for reducing the burden, to Department of Defense, Washington Headquarters Services, Directorate for Information
Economics of cutting hardwood dimension parts with an automated system
Henry A. Huber; Steve Ruddell; Kalinath Mukherjee; Charles W. McMillin
1989-01-01
A financial analysis using discounted cash-flow decision methods was completed to determine the economic feasibility of replacing a conventional roughmill crosscut and rip operation with a proposed automated computer vision and laser cutting system. Red oak and soft maple lumber were cut at production levels of 30 thousand board feet (MBF)/day and 5 MBF/day to produce...
Real-time simulation of contact and cutting of heterogeneous soft-tissues.
Courtecuisse, Hadrien; Allard, Jérémie; Kerfriden, Pierre; Bordas, Stéphane P A; Cotin, Stéphane; Duriez, Christian
2014-02-01
This paper presents a numerical method for interactive (real-time) simulations, which considerably improves the accuracy of the response of heterogeneous soft-tissue models undergoing contact, cutting and other topological changes. We provide an integrated methodology able to deal both with the ill-conditioning issues associated with material heterogeneities, contact boundary conditions which are one of the main sources of inaccuracies, and cutting which is one of the most challenging issues in interactive simulations. Our approach is based on an implicit time integration of a non-linear finite element model. To enable real-time computations, we propose a new preconditioning technique, based on an asynchronous update at low frequency. The preconditioner is not only used to improve the computation of the deformation of the tissues, but also to simulate the contact response of homogeneous and heterogeneous bodies with the same accuracy. We also address the problem of cutting the heterogeneous structures and propose a method to update the preconditioner according to the topological modifications. Finally, we apply our approach to three challenging demonstrators: (i) a simulation of cataract surgery (ii) a simulation of laparoscopic hepatectomy (iii) a brain tumor surgery. Copyright © 2013 Elsevier B.V. All rights reserved.
NASA Astrophysics Data System (ADS)
Zhang, Jingqiong; Zhang, Wenbiao; He, Yuting; Yan, Yong
2016-11-01
The amount of coke deposition on catalyst pellets is one of the most important indexes of catalytic property and service life. As a result, it is essential to measure this and analyze the active state of the catalysts during a continuous production process. This paper proposes a new method to predict the amount of coke deposition on catalyst pellets based on image analysis and soft computing. An image acquisition system consisting of a flatbed scanner and an opaque cover is used to obtain catalyst images. After imaging processing and feature extraction, twelve effective features are selected and two best feature sets are determined by the prediction tests. A neural network optimized by a particle swarm optimization algorithm is used to establish the prediction model of the coke amount based on various datasets. The root mean square error of the prediction values are all below 0.021 and the coefficient of determination R 2, for the model, are all above 78.71%. Therefore, a feasible, effective and precise method is demonstrated, which may be applied to realize the real-time measurement of coke deposition based on on-line sampling and fast image analysis.
Computed tomographic images using tube source of x rays: interior properties of the material
NASA Astrophysics Data System (ADS)
Rao, Donepudi V.; Takeda, Tohoru; Itai, Yuji; Seltzer, S. M.; Hubbell, John H.; Zeniya, Tsutomu; Akatsuka, Takao; Cesareo, Roberto; Brunetti, Antonio; Gigante, Giovanni E.
2002-01-01
An image intensifier based computed tomography scanner and a tube source of x-rays are used to obtain the images of small objects, plastics, wood and soft materials in order to know the interior properties of the material. A new method is developed to estimate the degree of monochromacy, total solid angle, efficiency and geometrical effects of the measuring system and the way to produce monoenergetic radiation. The flux emitted by the x-ray tube is filtered using the appropriate filters at the chosen optimum energy and reasonable monochromacy is achieved and the images are acceptably distinct. Much attention has been focused on the imaging of small objects of weakly attenuating materials at optimum value. At optimum value it is possible to calculate the three-dimensional representation of inner and outer surfaces of the object. The image contrast between soft materials could be significantly enhanced by optimal selection of the energy of the x-rays by Monte Carlo methods. The imaging system is compact, reasonably economic, has a good contrast resolution, simple operation and routine availability and explores the use of optimizing tomography for various applications.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Wu, Vincent W.C., E-mail: htvinwu@polyu.edu.hk; Tse, Teddy K.H.; Ho, Cola L.M.
2013-07-01
Monte Carlo (MC) simulation is currently the most accurate dose calculation algorithm in radiotherapy planning but requires relatively long processing time. Faster model-based algorithms such as the anisotropic analytical algorithm (AAA) by the Eclipse treatment planning system and multigrid superposition (MGS) by the XiO treatment planning system are 2 commonly used algorithms. This study compared AAA and MGS against MC, as the gold standard, on brain, nasopharynx, lung, and prostate cancer patients. Computed tomography of 6 patients of each cancer type was used. The same hypothetical treatment plan using the same machine and treatment prescription was computed for each casemore » by each planning system using their respective dose calculation algorithm. The doses at reference points including (1) soft tissues only, (2) bones only, (3) air cavities only, (4) soft tissue-bone boundary (Soft/Bone), (5) soft tissue-air boundary (Soft/Air), and (6) bone-air boundary (Bone/Air), were measured and compared using the mean absolute percentage error (MAPE), which was a function of the percentage dose deviations from MC. Besides, the computation time of each treatment plan was recorded and compared. The MAPEs of MGS were significantly lower than AAA in all types of cancers (p<0.001). With regards to body density combinations, the MAPE of AAA ranged from 1.8% (soft tissue) to 4.9% (Bone/Air), whereas that of MGS from 1.6% (air cavities) to 2.9% (Soft/Bone). The MAPEs of MGS (2.6%±2.1) were significantly lower than that of AAA (3.7%±2.5) in all tissue density combinations (p<0.001). The mean computation time of AAA for all treatment plans was significantly lower than that of the MGS (p<0.001). Both AAA and MGS algorithms demonstrated dose deviations of less than 4.0% in most clinical cases and their performance was better in homogeneous tissues than at tissue boundaries. In general, MGS demonstrated relatively smaller dose deviations than AAA but required longer computation time.« less
DOE Office of Scientific and Technical Information (OSTI.GOV)
Qi, X; Yang, Y; Jack, N
Purpose: On-board MRI provides superior soft-tissue contrast, allowing patient alignment using tumor or nearby critical structures. This study aims to study H&N MRI-guided IGRT to analyze inter-fraction patient setup variations using soft-tissue targets and design appropriate CTV-to-PTV margin and clinical implication. Methods: 282 MR images for 10 H&N IMRT patients treated on a ViewRay system were retrospectively analyzed. Patients were immobilized using a thermoplastic mask on a customized headrest fitted in a radiofrequency coil and positioned to soft-tissue targets. The inter-fraction patient displacements were recorded to compute the PTV margins using the recipe: 2.5∑+0.7σ. New IMRT plans optimized on themore » revised PTVs were generated to evaluate the delivered dose distributions. An in-house dose deformation registration tool was used to assess the resulting dosimetric consequences when margin adaption is performed based on weekly MR images. The cumulative doses were compared to the reduced margin plans for targets and critical structures. Results: The inter-fraction displacements (and standard deviations), ∑ and σ were tabulated for MRI and compared to kVCBCT. The computed CTV-to-PTV margin was 3.5mm for soft-tissue based registration. There were minimal differences between the planned and delivered doses when comparing clinical and the PTV reduced margin plans: the paired t-tests yielded p=0.38 and 0.66 between the planned and delivered doses for the adapted margin plans for the maximum cord and mean parotid dose, respectively. Target V95 received comparable doses as planned for the reduced margin plans. Conclusion: The 0.35T MRI offers acceptable soft-tissue contrast and good spatial resolution for patient alignment and target visualization. Better tumor conspicuity from MRI allows soft-tissue based alignments with potentially improved accuracy, suggesting a benefit of margin reduction for H&N radiotherapy. The reduced margin plans (i.e., 2 mm) resulted in improved normal structure sparing and accurate dose delivery to achieve intended treatment goal under MR guidance.« less
The application of artificial intelligence in the optimal design of mechanical systems
NASA Astrophysics Data System (ADS)
Poteralski, A.; Szczepanik, M.
2016-11-01
The paper is devoted to new computational techniques in mechanical optimization where one tries to study, model, analyze and optimize very complex phenomena, for which more precise scientific tools of the past were incapable of giving low cost and complete solution. Soft computing methods differ from conventional (hard) computing in that, unlike hard computing, they are tolerant of imprecision, uncertainty, partial truth and approximation. The paper deals with an application of the bio-inspired methods, like the evolutionary algorithms (EA), the artificial immune systems (AIS) and the particle swarm optimizers (PSO) to optimization problems. Structures considered in this work are analyzed by the finite element method (FEM), the boundary element method (BEM) and by the method of fundamental solutions (MFS). The bio-inspired methods are applied to optimize shape, topology and material properties of 2D, 3D and coupled 2D/3D structures, to optimize the termomechanical structures, to optimize parameters of composites structures modeled by the FEM, to optimize the elastic vibrating systems to identify the material constants for piezoelectric materials modeled by the BEM and to identify parameters in acoustics problem modeled by the MFS.
Inference of cancer-specific gene regulatory networks using soft computing rules.
Wang, Xiaosheng; Gotoh, Osamu
2010-03-24
Perturbations of gene regulatory networks are essentially responsible for oncogenesis. Therefore, inferring the gene regulatory networks is a key step to overcoming cancer. In this work, we propose a method for inferring directed gene regulatory networks based on soft computing rules, which can identify important cause-effect regulatory relations of gene expression. First, we identify important genes associated with a specific cancer (colon cancer) using a supervised learning approach. Next, we reconstruct the gene regulatory networks by inferring the regulatory relations among the identified genes, and their regulated relations by other genes within the genome. We obtain two meaningful findings. One is that upregulated genes are regulated by more genes than downregulated ones, while downregulated genes regulate more genes than upregulated ones. The other one is that tumor suppressors suppress tumor activators and activate other tumor suppressors strongly, while tumor activators activate other tumor activators and suppress tumor suppressors weakly, indicating the robustness of biological systems. These findings provide valuable insights into the pathogenesis of cancer.
Klein–Gordon equation in curved space-time
NASA Astrophysics Data System (ADS)
Lehn, R. D.; Chabysheva, S. S.; Hiller, J. R.
2018-07-01
We report the methods and results of a computational physics project on the solution of the relativistic Klein–Gordon equation for a light particle gravitationally bound to a heavy central mass. The gravitational interaction is prescribed by the metric of a spherically symmetric space-time. Metrics are considered for an impenetrable sphere, a soft sphere of uniform density, and a soft sphere with a linear transition from constant to zero density; in each case the radius of the central mass is chosen to be sufficient to avoid any event horizon. The solutions are obtained numerically and compared with nonrelativistic Coulomb-type solutions, both directly and in perturbation theory, to study the general-relativistic corrections to the quantum solutions for a 1/r potential. The density profile with a linear transition is chosen to avoid singularities in the wave equation that can be caused by a discontinuous derivative of the density. This project should be of interest to instructors and students of computational physics at the graduate and advanced undergraduate levels.
Development of Semi-Automatic Lathe by using Intelligent Soft Computing Technique
NASA Astrophysics Data System (ADS)
Sakthi, S.; Niresh, J.; Vignesh, K.; Anand Raj, G.
2018-03-01
This paper discusses the enhancement of conventional lathe machine to semi-automated lathe machine by implementing a soft computing method. In the present scenario, lathe machine plays a vital role in the engineering division of manufacturing industry. While the manual lathe machines are economical, the accuracy and efficiency are not up to the mark. On the other hand, CNC machine provide the desired accuracy and efficiency, but requires a huge capital. In order to over come this situation, a semi-automated approach towards the conventional lathe machine is developed by employing stepper motors to the horizontal and vertical drive, that can be controlled by Arduino UNO -microcontroller. Based on the input parameters of the lathe operation the arduino coding is been generated and transferred to the UNO board. Thus upgrading from manual to semi-automatic lathe machines can significantly increase the accuracy and efficiency while, at the same time, keeping a check on investment cost and consequently provide a much needed escalation to the manufacturing industry.
On the possibility of non-invasive multilayer temperature estimation using soft-computing methods.
Teixeira, C A; Pereira, W C A; Ruano, A E; Ruano, M Graça
2010-01-01
This work reports original results on the possibility of non-invasive temperature estimation (NITE) in a multilayered phantom by applying soft-computing methods. The existence of reliable non-invasive temperature estimator models would improve the security and efficacy of thermal therapies. These points would lead to a broader acceptance of this kind of therapies. Several approaches based on medical imaging technologies were proposed, magnetic resonance imaging (MRI) being appointed as the only one to achieve the acceptable temperature resolutions for hyperthermia purposes. However, MRI intrinsic characteristics (e.g., high instrumentation cost) lead us to use backscattered ultrasound (BSU). Among the different BSU features, temporal echo-shifts have received a major attention. These shifts are due to changes of speed-of-sound and expansion of the medium. The originality of this work involves two aspects: the estimator model itself is original (based on soft-computing methods) and the application to temperature estimation in a three-layer phantom is also not reported in literature. In this work a three-layer (non-homogeneous) phantom was developed. The two external layers were composed of (in % of weight): 86.5% degassed water, 11% glycerin and 2.5% agar-agar. The intermediate layer was obtained by adding graphite powder in the amount of 2% of the water weight to the above composition. The phantom was developed to have attenuation and speed-of-sound similar to in vivo muscle, according to the literature. BSU signals were collected and cumulative temporal echo-shifts computed. These shifts and the past temperature values were then considered as possible estimators inputs. A soft-computing methodology was applied to look for appropriate multilayered temperature estimators. The methodology involves radial-basis functions neural networks (RBFNN) with structure optimized by the multi-objective genetic algorithm (MOGA). In this work 40 operating conditions were considered, i.e. five 5-mm spaced spatial points and eight therapeutic intensities (I(SATA)): 0.3, 0.5, 0.7, 1.0, 1.3, 1.5, 1.7 and 2.0W/cm(2). Models were trained and selected to estimate temperature at only four intensities, then during the validation phase, the best-fitted models were analyzed in data collected at the eight intensities. This procedure leads to a more realistic evaluation of the generalisation level of the best-obtained structures. At the end of the identification phase, 82 (preferable) estimator models were achieved. The majority of them present an average maximum absolute error (MAE) inferior to 0.5 degrees C. The best-fitted estimator presents a MAE of only 0.4 degrees C for both the 40 operating conditions. This means that the gold-standard maximum error (0.5 degrees C) pointed for hyperthermia was fulfilled independently of the intensity and spatial position considered, showing the improved generalisation capacity of the identified estimator models. As the majority of the preferable estimator models, the best one presents 6 inputs and 11 neurons. In addition to the appropriate error performance, the estimator models present also a reduced computational complexity and then the possibility to be applied in real-time. A non-invasive temperature estimation model, based on soft-computing technique, was proposed for a three-layered phantom. The best-achieved estimator models presented an appropriate error performance regardless of the spatial point considered (inside or at the interface of the layers) and of the intensity applied. Other methodologies published so far, estimate temperature only in homogeneous media. The main drawback of the proposed methodology is the necessity of a-priory knowledge of the temperature behavior. Data used for training and optimisation should be representative, i.e., they should cover all possible physical situations of the estimation environment.
van der List, Jelle P; Chawla, Harshvardhan; Joskowicz, Leo; Pearle, Andrew D
2016-11-01
Recently, there is a growing interest in surgical variables that are intraoperatively controlled by orthopaedic surgeons, including lower leg alignment, component positioning and soft tissues balancing. Since more tight control over these factors is associated with improved outcomes of unicompartmental knee arthroplasty and total knee arthroplasty (TKA), several computer navigation and robotic-assisted systems have been developed. Although mechanical axis accuracy and component positioning have been shown to improve with computer navigation, no superiority in functional outcomes has yet been shown. This could be explained by the fact that many differences exist between the number and type of surgical variables these systems control. Most systems control lower leg alignment and component positioning, while some in addition control soft tissue balancing. Finally, robotic-assisted systems have the additional advantage of improving surgical precision. A systematic search in PubMed, Embase and Cochrane Library resulted in 40 comparative studies and three registries on computer navigation reporting outcomes of 474,197 patients, and 21 basic science and clinical studies on robotic-assisted knee arthroplasty. Twenty-eight of these comparative computer navigation studies reported Knee Society Total scores in 3504 patients. Stratifying by type of surgical variables, no significant differences were noted in outcomes between surgery with computer-navigated TKA controlling for alignment and component positioning versus conventional TKA (p = 0.63). However, significantly better outcomes were noted following computer-navigated TKA that also controlled for soft tissue balancing versus conventional TKA (mean difference 4.84, 95 % Confidence Interval 1.61, 8.07, p = 0.003). A literature review of robotic systems showed that these systems can, similarly to computer navigation, reliably improve lower leg alignment, component positioning and soft tissues balancing. Furthermore, two studies comparing robotic-assisted with computer-navigated surgery reported superiority of robotic-assisted surgery in controlling these factors. Manually controlling all these surgical variables can be difficult for the orthopaedic surgeon. Findings in this study suggest that computer navigation or robotic assistance may help managing these multiple variables and could improve outcomes. Future studies assessing the role of soft tissue balancing in knee arthroplasty and long-term follow-up studies assessing the role of computer-navigated and robotic-assisted knee arthroplasty are needed.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Reuter, K.; Raptopoulos, V.; Reale, F.
1983-06-01
The diagnosis of peritoneal mesothelioma was made prospectively and noninvasively in four patients with the use of sonography, computed tomography, and sonographically guided fine-needle aspiration biopsy. The imaging methods revealed information similar to the operative findings, with clear superiority of computed tomography over sonography. These noninvasive methods may be used as screening tools, especially among groups or in regional areas with a high risk for asbestos exposure. The findings included soft-tissue masses with invariable involvement of the omentum; small intraperitoneal nodules; thickened peritoneum, mesentery, and bowel wall; pleural plaques; and usually minimal, if any, ascites. Since the differential diagnosis frommore » peritoneal carcinomatosis may be difficult, sonographically (or CT) guided aspiration biopsy is needed to produce diagnostic cytologic specimens. The use of this type of biopsy should obviate surgical exploration.« less
Sommerfeld, Thomas; Ehara, Masahiro
2015-01-21
The energy of a temporary anion can be computed by adding a stabilizing potential to the molecular Hamiltonian, increasing the stabilization until the temporary state is turned into a bound state, and then further increasing the stabilization until enough bound state energies have been collected so that these can be extrapolated back to vanishing stabilization. The lifetime can be obtained from the same data, but only if the extrapolation is done through analytic continuation of the momentum as a function of the square root of a shifted stabilizing parameter. This method is known as analytic continuation of the coupling constant, and it requires--at least in principle--that the bound-state input data are computed with a short-range stabilizing potential. In the context of molecules and ab initio packages, long-range Coulomb stabilizing potentials are, however, far more convenient and have been used in the past with some success, although the error introduced by the long-rang nature of the stabilizing potential remains unknown. Here, we introduce a soft-Voronoi box potential that can serve as a short-range stabilizing potential. The difference between a Coulomb and the new stabilization is analyzed in detail for a one-dimensional model system as well as for the (2)Πu resonance of CO2(-), and in both cases, the extrapolation results are compared to independently computed resonance parameters, from complex scaling for the model, and from complex absorbing potential calculations for CO2(-). It is important to emphasize that for both the model and for CO2(-), all three sets of results have, respectively, been obtained with the same electronic structure method and basis set so that the theoretical description of the continuum can be directly compared. The new soft-Voronoi-box-based extrapolation is then used to study the influence of the size of diffuse and the valence basis sets on the computed resonance parameters.
Vendemia, Nicholas; Chao, Jerry; Ivanidze, Jana; Sanelli, Pina; Spinelli, Henry M
2011-01-01
Medpor (Porex Surgical, Inc, Newnan, GA) is composed of porous polyethylene and is commonly used in craniofacial reconstruction. When complications such as seroma or abscess formation arise, diagnostic modalities are limited because Medpor is radiolucent on conventional radiologic studies. This poses a problem in situations where imaging is necessary to distinguish the implant from surrounding tissues. To present a clinically useful method for imaging Medpor with conventional computed tomographic (CT) scanning. Eleven patients (12 total implants) who have undergone reconstructive surgery with Medpor were included in the study. A retrospective review of CT scans done between 1 and 16 months postoperatively was performed using 3 distinct CT window settings. Measurements of implant dimensions and Hounsfield units were recorded and qualitatively assessed. Of the 3 distinct window settings studied, namely, "bone" (W1100/L450), "soft tissue"; (W500/L50), and "implant" (W800/L200), the implant window proved the most ideal, allowing the investigators to visualize and evaluate Medpor in all cases. Qualitative analysis revealed that Medpor implants were able to be distinguished from surrounding tissue in both the implant and soft tissue windows, with a density falling between that of fat and fluid. In 1 case, Medpor could not be visualized in the soft tissue window, although it could be visualized in the implant window. Quantitative analysis demonstrated a mean (SD) density of -38.7 (7.4) Hounsfield units. Medpor may be optimally visualized on conventional CT scans using the implant window settings W800/L200, which can aid in imaging Medpor and diagnosing implant-related complications.
Wittig, Holger; Zesch, Stephanie; Rosendahl, Wilfried; Blache, Sandra; Müller-Gerbl, Magdalena; Hotz, Gerhard
2017-01-01
Objective In this study, an Inca bundle was examined using computed tomography (CT). The primary aim was to determine the preservation status of bony and soft tissues, the sex, the age at the time of death, possible indicators for disease or even the cause of death, as well as the kind of mummification. A secondary aim was to obtain a brief overview of the wrapping in order to gain additional information on the cultural background. Materials and methods The bundle belongs to the Museum of Cultures in Basel, Switzerland, and was bought in Munich, Germany, in 1921. Radiocarbon dating of the superficial textile yielded a calibrated age between 1480 and 1650 AD. The mummy was investigated using multi-slice CT with slice thickness of 0.75 mm and 110 kilovolt. For standardized assessment of soft tissue preservation, a recently developed checklist was applied. Results CT revealed the mummy of a seven to nine year old boy with superior preservation of bony and soft tissues allowing detailed assessment. Indicators of neurofibromatosis type 1 (paravertebral and cutaneous neurofibromas, a breast neurofibroma, sphenoid wing dysplasia), Chagas disease (dilatation of the esophagus, stomach, rectum, and large amounts of feces), and lung infection (pleural adherence, calcifications), probably due to tuberculosis, were found. Furthermore, signs of peri-mortem violence (transection of the chest and a defect in the abdominal wall) were detected. CT images revealed a carefully performed wrapping. Conclusion CT examination of the Inca bundle proved to be an important non-destructive examination method. Standardized assessment, especially of the soft tissue structures, allowed for diagnoses of several diseases, indicating a multi-morbid child at the time of death. The careful wrapping pointed to a ceremonial burial. Within the cultural background, the signs of fatal violence were discussed as a possible result of war, murder, accident, or human sacrifice. PMID:28403237
NASA Astrophysics Data System (ADS)
Wang, Lunche; Kisi, Ozgur; Zounemat-Kermani, Mohammad; Li, Hui
2017-01-01
Pan evaporation (Ep) plays important roles in agricultural water resources management. One of the basic challenges is modeling Ep using limited climatic parameters because there are a number of factors affecting the evaporation rate. This study investigated the abilities of six different soft computing methods, multi-layer perceptron (MLP), generalized regression neural network (GRNN), fuzzy genetic (FG), least square support vector machine (LSSVM), multivariate adaptive regression spline (MARS), adaptive neuro-fuzzy inference systems with grid partition (ANFIS-GP), and two regression methods, multiple linear regression (MLR) and Stephens and Stewart model (SS) in predicting monthly Ep. Long-term climatic data at various sites crossing a wide range of climates during 1961-2000 are used for model development and validation. The results showed that the models have different accuracies in different climates and the MLP model performed superior to the other models in predicting monthly Ep at most stations using local input combinations (for example, the MAE (mean absolute errors), RMSE (root mean square errors), and determination coefficient (R2) are 0.314 mm/day, 0.405 mm/day and 0.988, respectively for HEB station), while GRNN model performed better in Tibetan Plateau (MAE, RMSE and R2 are 0.459 mm/day, 0.592 mm/day and 0.932, respectively). The accuracies of above models ranked as: MLP, GRNN, LSSVM, FG, ANFIS-GP, MARS and MLR. The overall results indicated that the soft computing techniques generally performed better than the regression methods, but MLR and SS models can be more preferred at some climatic zones instead of complex nonlinear models, for example, the BJ (Beijing), CQ (Chongqing) and HK (Haikou) stations. Therefore, it can be concluded that Ep could be successfully predicted using above models in hydrological modeling studies.
Explosion safety in industrial electrostatics
NASA Astrophysics Data System (ADS)
Szabó, S. V.; Kiss, I.; Berta, I.
2011-01-01
Complicated industrial systems are often endangered by electrostatic hazards, both from atmospheric (lightning phenomenon, primary and secondary lightning protection) and industrial (technological problems caused by static charging and fire and explosion hazards.) According to the classical approach protective methods have to be used in order to remove electrostatic charging and to avoid damages, however no attempt to compute the risk before and after applying the protective method is made, relying instead on well-educated and practiced expertise. The Budapest School of Electrostatics - in close cooperation with industrial partners - develops new suitable solutions for probability based decision support (Static Control Up-to-date Technology, SCOUT) using soft computing methods. This new approach can be used to assess and audit existing systems and - using the predictive power of the models - to design and plan activities in industrial electrostatics.
Spectral Regularization Algorithms for Learning Large Incomplete Matrices.
Mazumder, Rahul; Hastie, Trevor; Tibshirani, Robert
2010-03-01
We use convex relaxation techniques to provide a sequence of regularized low-rank solutions for large-scale matrix completion problems. Using the nuclear norm as a regularizer, we provide a simple and very efficient convex algorithm for minimizing the reconstruction error subject to a bound on the nuclear norm. Our algorithm Soft-Impute iteratively replaces the missing elements with those obtained from a soft-thresholded SVD. With warm starts this allows us to efficiently compute an entire regularization path of solutions on a grid of values of the regularization parameter. The computationally intensive part of our algorithm is in computing a low-rank SVD of a dense matrix. Exploiting the problem structure, we show that the task can be performed with a complexity linear in the matrix dimensions. Our semidefinite-programming algorithm is readily scalable to large matrices: for example it can obtain a rank-80 approximation of a 10(6) × 10(6) incomplete matrix with 10(5) observed entries in 2.5 hours, and can fit a rank 40 approximation to the full Netflix training set in 6.6 hours. Our methods show very good performance both in training and test error when compared to other competitive state-of-the art techniques.
Spectral Regularization Algorithms for Learning Large Incomplete Matrices
Mazumder, Rahul; Hastie, Trevor; Tibshirani, Robert
2010-01-01
We use convex relaxation techniques to provide a sequence of regularized low-rank solutions for large-scale matrix completion problems. Using the nuclear norm as a regularizer, we provide a simple and very efficient convex algorithm for minimizing the reconstruction error subject to a bound on the nuclear norm. Our algorithm Soft-Impute iteratively replaces the missing elements with those obtained from a soft-thresholded SVD. With warm starts this allows us to efficiently compute an entire regularization path of solutions on a grid of values of the regularization parameter. The computationally intensive part of our algorithm is in computing a low-rank SVD of a dense matrix. Exploiting the problem structure, we show that the task can be performed with a complexity linear in the matrix dimensions. Our semidefinite-programming algorithm is readily scalable to large matrices: for example it can obtain a rank-80 approximation of a 106 × 106 incomplete matrix with 105 observed entries in 2.5 hours, and can fit a rank 40 approximation to the full Netflix training set in 6.6 hours. Our methods show very good performance both in training and test error when compared to other competitive state-of-the art techniques. PMID:21552465
Weber, R; Knaup, P; Knietitg, R; Haux, R; Merzweiler, A; Mludek, V; Schilling, F H; Wiedemann, T
2001-01-01
The German Society for Paediatric Oncology and Haematology (GPOH) runs nation-wide multicentre clinical trials to improve the treatment of children suffering from malignant diseases. We want to provide methods and tools to support the centres of these trials in developing trial specific modules for the computer-based DOcumentation System for Paediatric Oncology (DOSPO). For this we carried out an object-oriented business process analysis for the Cooperative Soft Tissue Sarcoma Trial at the Olgahospital Stuttgart for Child and Adolescent Medicine. The result is a comprehensive business process model consisting of UML-diagrams and use case specifications. We recommend the object-oriented business process analysis as a method for the definition of requirements in information processing projects in the field of clinical trials in general. For this our model can serve as basis because it slightly can be adjusted to each type of clinical trial.
Optimization and real-time control for laser treatment of heterogeneous soft tissues.
Feng, Yusheng; Fuentes, David; Hawkins, Andrea; Bass, Jon M; Rylander, Marissa Nichole
2009-01-01
Predicting the outcome of thermotherapies in cancer treatment requires an accurate characterization of the bioheat transfer processes in soft tissues. Due to the biological and structural complexity of tumor (soft tissue) composition and vasculature, it is often very difficult to obtain reliable tissue properties that is one of the key factors for the accurate treatment outcome prediction. Efficient algorithms employing in vivo thermal measurements to determine heterogeneous thermal tissues properties in conjunction with a detailed sensitivity analysis can produce essential information for model development and optimal control. The goals of this paper are to present a general formulation of the bioheat transfer equation for heterogeneous soft tissues, review models and algorithms developed for cell damage, heat shock proteins, and soft tissues with nanoparticle inclusion, and demonstrate an overall computational strategy for developing a laser treatment framework with the ability to perform real-time robust calibrations and optimal control. This computational strategy can be applied to other thermotherapies using the heat source such as radio frequency or high intensity focused ultrasound.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Souris, Kevin, E-mail: kevin.souris@uclouvain.be; Lee, John Aldo; Sterpin, Edmond
2016-04-15
Purpose: Accuracy in proton therapy treatment planning can be improved using Monte Carlo (MC) simulations. However the long computation time of such methods hinders their use in clinical routine. This work aims to develop a fast multipurpose Monte Carlo simulation tool for proton therapy using massively parallel central processing unit (CPU) architectures. Methods: A new Monte Carlo, called MCsquare (many-core Monte Carlo), has been designed and optimized for the last generation of Intel Xeon processors and Intel Xeon Phi coprocessors. These massively parallel architectures offer the flexibility and the computational power suitable to MC methods. The class-II condensed history algorithmmore » of MCsquare provides a fast and yet accurate method of simulating heavy charged particles such as protons, deuterons, and alphas inside voxelized geometries. Hard ionizations, with energy losses above a user-specified threshold, are simulated individually while soft events are regrouped in a multiple scattering theory. Elastic and inelastic nuclear interactions are sampled from ICRU 63 differential cross sections, thereby allowing for the computation of prompt gamma emission profiles. MCsquare has been benchmarked with the GATE/GEANT4 Monte Carlo application for homogeneous and heterogeneous geometries. Results: Comparisons with GATE/GEANT4 for various geometries show deviations within 2%–1 mm. In spite of the limited memory bandwidth of the coprocessor simulation time is below 25 s for 10{sup 7} primary 200 MeV protons in average soft tissues using all Xeon Phi and CPU resources embedded in a single desktop unit. Conclusions: MCsquare exploits the flexibility of CPU architectures to provide a multipurpose MC simulation tool. Optimized code enables the use of accurate MC calculation within a reasonable computation time, adequate for clinical practice. MCsquare also simulates prompt gamma emission and can thus be used also for in vivo range verification.« less
NASA Astrophysics Data System (ADS)
Vennila, P.; Govindaraju, M.; Venkatesh, G.; Kamal, C.
2016-05-01
Fourier transform - Infra red (FT-IR) and Fourier transform - Raman (FT-Raman) spectroscopic techniques have been carried out to analyze O-methoxy benzaldehyde (OMB) molecule. The fundamental vibrational frequencies and intensity of vibrational bands were evaluated using density functional theory (DFT). The vibrational analysis of stable isomer of OMB has been carried out by FT-IR and FT-Raman in combination with theoretical method simultaneously. The first-order hyperpolarizability and the anisotropy polarizability invariant were computed by DFT method. The atomic charges, hardness, softness, ionization potential, electronegativity, HOMO-LUMO energies, and electrophilicity index have been calculated. The 13C and 1H Nuclear magnetic resonance (NMR) have also been obtained by GIAO method. Molecular electronic potential (MEP) has been calculated by the DFT calculation method. Electronic excitation energies, oscillator strength and excited states characteristics were computed by the closed-shell singlet calculation method.
Penza, Veronica; Ortiz, Jesús; Mattos, Leonardo S; Forgione, Antonello; De Momi, Elena
2016-02-01
Single-incision laparoscopic surgery decreases postoperative infections, but introduces limitations in the surgeon's maneuverability and in the surgical field of view. This work aims at enhancing intra-operative surgical visualization by exploiting the 3D information about the surgical site. An interactive guidance system is proposed wherein the pose of preoperative tissue models is updated online. A critical process involves the intra-operative acquisition of tissue surfaces. It can be achieved using stereoscopic imaging and 3D reconstruction techniques. This work contributes to this process by proposing new methods for improved dense 3D reconstruction of soft tissues, which allows a more accurate deformation identification and facilitates the registration process. Two methods for soft tissue 3D reconstruction are proposed: Method 1 follows the traditional approach of the block matching algorithm. Method 2 performs a nonparametric modified census transform to be more robust to illumination variation. The simple linear iterative clustering (SLIC) super-pixel algorithm is exploited for disparity refinement by filling holes in the disparity images. The methods were validated using two video datasets from the Hamlyn Centre, achieving an accuracy of 2.95 and 1.66 mm, respectively. A comparison with ground-truth data demonstrated the disparity refinement procedure: (1) increases the number of reconstructed points by up to 43 % and (2) does not affect the accuracy of the 3D reconstructions significantly. Both methods give results that compare favorably with the state-of-the-art methods. The computational time constraints their applicability in real time, but can be greatly improved by using a GPU implementation.
Patient-specific polyetheretherketone facial implants in a computer-aided planning workflow.
Guevara-Rojas, Godoberto; Figl, Michael; Schicho, Kurt; Seemann, Rudolf; Traxler, Hannes; Vacariu, Apostolos; Carbon, Claus-Christian; Ewers, Rolf; Watzinger, Franz
2014-09-01
In the present study, we report an innovative workflow using polyetheretherketone (PEEK) patient-specific implants for esthetic corrections in the facial region through onlay grafting. The planning includes implant design according to virtual osteotomy and generation of a subtraction volume. The implant design was refined by stepwise changing the implant geometry according to soft tissue simulations. One patient was scanned using computed tomography. PEEK implants were interactively designed and manufactured using rapid prototyping techniques. Positioning intraoperatively was assisted by computer-aided navigation. Two months after surgery, a 3-dimensional surface model of the patient's face was generated using photogrammetry. Finally, the Hausdorff distance calculation was used to quantify the overall error, encompassing the failures in soft tissue simulation and implantation. The implant positioning process during surgery was satisfactory. The simulated soft tissue surface and the photogrammetry scan of the patient showed a high correspondence, especially where the skin covered the implants. The mean total error (Hausdorff distance) was 0.81 ± 1.00 mm (median 0.48, interquartile range 1.11). The spatial deviation remained less than 0.7 mm for the vast majority of points. The proposed workflow provides a complete computer-aided design, computer-aided manufacturing, and computer-aided surgery chain for implant design, allowing for soft tissue simulation, fabrication of patient-specific implants, and image-guided surgery to position the implants. Much of the surgical complexity resulting from osteotomies of the zygoma, chin, or mandibular angle might be transferred into the planning phase of patient-specific implants. Copyright © 2014 American Association of Oral and Maxillofacial Surgeons. Published by Elsevier Inc. All rights reserved.
Comparison of computed tomography and complex motion tomography in the evaluation of cholesteatoma
DOE Office of Scientific and Technical Information (OSTI.GOV)
Shaffer, K.A.
1984-08-01
High-resolution axial and coronal computed tomographic (CT) scans were compared with coronal and sagittal complex motion tomograms in patients with suspected middle ear cholesteatomas. Information on CT scans equaled or exceeded that on conventional complex motion tomograms in 16 of 17 patients, and in 11 it provided additional information. Soft-tissue resolution was superior with CT. In 14 patients who underwent surgery, CT provided information that was valuable to the surgeon. On the basis of this study, high-resolution CT is recommended as the preferred method for evaluating most patients with cholesteatomas of the temporal bone.
A Real-Time Marker-Based Visual Sensor Based on a FPGA and a Soft Core Processor
Tayara, Hilal; Ham, Woonchul; Chong, Kil To
2016-01-01
This paper introduces a real-time marker-based visual sensor architecture for mobile robot localization and navigation. A hardware acceleration architecture for post video processing system was implemented on a field-programmable gate array (FPGA). The pose calculation algorithm was implemented in a System on Chip (SoC) with an Altera Nios II soft-core processor. For every frame, single pass image segmentation and Feature Accelerated Segment Test (FAST) corner detection were used for extracting the predefined markers with known geometries in FPGA. Coplanar PosIT algorithm was implemented on the Nios II soft-core processor supplied with floating point hardware for accelerating floating point operations. Trigonometric functions have been approximated using Taylor series and cubic approximation using Lagrange polynomials. Inverse square root method has been implemented for approximating square root computations. Real time results have been achieved and pixel streams have been processed on the fly without any need to buffer the input frame for further implementation. PMID:27983714
New Platforms for Characterization of Biological Material Failure and Resilience Properties
NASA Astrophysics Data System (ADS)
Brown, Katherine; Butler, Benjamin J.; Nguyen, Thuy-Tien N.; Sorry, David; Williams, Alun; Proud, William G.
2017-06-01
Obtaining information about the material responses of viscoelastic soft matter, such as polymers and foams has, required adaptation of techniques traditionally used with hard condensed matter. More recently it has been recognized that understanding the strain-rate behavior of natural and synthetic soft biological materials poses even greater challenges for materials research due their heterogeneous composition and structural complexity. Expanding fundamental knowledge about how these classes of biomaterials function under different loading regimes is of considerable interest in both fundamental and applied research. A comparative overview of methods, developed in our laboratory or elsewhere, for determining material responses of cells and soft tissues over a wide range of strain rates (quasi-static to blast loading) will be presented. Examples will illustrate how data are obtained for studying material responses of cells and tissues. Strengths and weaknesses of current approaches will be discussed, with particular emphasis on challenges associated with the development of realistic experimental and computational models for trauma and other disease indications.
A Real-Time Marker-Based Visual Sensor Based on a FPGA and a Soft Core Processor.
Tayara, Hilal; Ham, Woonchul; Chong, Kil To
2016-12-15
This paper introduces a real-time marker-based visual sensor architecture for mobile robot localization and navigation. A hardware acceleration architecture for post video processing system was implemented on a field-programmable gate array (FPGA). The pose calculation algorithm was implemented in a System on Chip (SoC) with an Altera Nios II soft-core processor. For every frame, single pass image segmentation and Feature Accelerated Segment Test (FAST) corner detection were used for extracting the predefined markers with known geometries in FPGA. Coplanar PosIT algorithm was implemented on the Nios II soft-core processor supplied with floating point hardware for accelerating floating point operations. Trigonometric functions have been approximated using Taylor series and cubic approximation using Lagrange polynomials. Inverse square root method has been implemented for approximating square root computations. Real time results have been achieved and pixel streams have been processed on the fly without any need to buffer the input frame for further implementation.
Non Lipomatous Benign Lesions Mimicking Soft-tissue Sarcomas: A Pictorial Essay
CORAN, ALESSANDRO; ORSATTI, GIOVANNA; CRIMÌ, FILIPPO; RASTRELLI, MARCO; DI MAGGIO, ANTONIO; PONZONI, ALBERTO; ATTAR, SHADY; STRAMARE, ROBERTO
2018-01-01
The incidental finding of soft tissue masses is a challenge for the radiologist. Benign and malignant lesions can be differentiated relying on patient history, symptoms and mostly with the help of imaging. Ultrasound (US), computed tomography (CT) and magnetic resonance imaging (MRI) become fundamental in order to distinguish these lesions but the radiologist needs to know the main characteristics of benign soft tissue masses and sarcomas. Herein, we present a pictorial review of lesions mimicking soft tissue sarcomas features. PMID:29475903
Automated segmentations of skin, soft-tissue, and skeleton, from torso CT images
NASA Astrophysics Data System (ADS)
Zhou, Xiangrong; Hara, Takeshi; Fujita, Hiroshi; Yokoyama, Ryujiro; Kiryu, Takuji; Hoshi, Hiroaki
2004-05-01
We have been developing a computer-aided diagnosis (CAD) scheme for automatically recognizing human tissue and organ regions from high-resolution torso CT images. We show some initial results for extracting skin, soft-tissue and skeleton regions. 139 patient cases of torso CT images (male 92, female 47; age: 12-88) were used in this study. Each case was imaged with a common protocol (120kV/320mA) and covered the whole torso with isotopic spatial resolution of about 0.63 mm and density resolution of 12 bits. A gray-level thresholding based procedure was applied to separate the human body from background. The density and distance features to body surface were used to determine the skin, and separate soft-tissue from the others. A 3-D region growing based method was used to extract the skeleton. We applied this system to the 139 cases and found that the skin, soft-tissue and skeleton regions were recognized correctly for 93% of the patient cases. The accuracy of segmentation results was acceptable by evaluating the results slice by slice. This scheme will be included in CAD systems for detecting and diagnosing the abnormal lesions in multi-slice torso CT images.
NASA Astrophysics Data System (ADS)
Bourke, Jason Michael
This study seeks to restore the internal anatomy within the nasal passages of dinosaurs via the use of comparative anatomical methods along with computational fluid dynamic simulations. Nasal airway descriptions and airflow simulations are described for extant birds, crocodylians, and lizards. These descriptions served as a baseline for airflow within the nasal passages of diapsids. The presence of shared airflow and soft-tissue properties found in the nasal passages of extant diapsids, were used to restore soft tissues within the airways of dinosaurs under the assumption that biologically unfeasible airflow patterns (e.g., lack of air movement in olfactory recess) can serve as signals for missing soft tissues. This methodology was tested on several dinosaur taxa. Restored airways in some taxa revealed the potential presence and likely shape of nasal turbinates. Heat transfer efficiency was tested in two dinosaur species with elaborated nasal passages. Results of that analysis revealed that dinosaur noses were efficient heat exchangers that likely played an integral role in maintaining cephalic thermoregulation. Brain cooling via nasal expansion appears to have been necessary for dinosaurs to have achieved their immense body sizes without overheating their brains.
Soft computing techniques toward modeling the water supplies of Cyprus.
Iliadis, L; Maris, F; Tachos, S
2011-10-01
This research effort aims in the application of soft computing techniques toward water resources management. More specifically, the target is the development of reliable soft computing models capable of estimating the water supply for the case of "Germasogeia" mountainous watersheds in Cyprus. Initially, ε-Regression Support Vector Machines (ε-RSVM) and fuzzy weighted ε-RSVMR models have been developed that accept five input parameters. At the same time, reliable artificial neural networks have been developed to perform the same job. The 5-fold cross validation approach has been employed in order to eliminate bad local behaviors and to produce a more representative training data set. Thus, the fuzzy weighted Support Vector Regression (SVR) combined with the fuzzy partition has been employed in an effort to enhance the quality of the results. Several rational and reliable models have been produced that can enhance the efficiency of water policy designers. Copyright © 2011 Elsevier Ltd. All rights reserved.
Mundahl, John; Jianjun Meng; He, Jeffrey; Bin He
2016-08-01
Brain-computer interface (BCI) systems allow users to directly control computers and other machines by modulating their brain waves. In the present study, we investigated the effect of soft drinks on resting state (RS) EEG signals and BCI control. Eight healthy human volunteers each participated in three sessions of BCI cursor tasks and resting state EEG. During each session, the subjects drank an unlabeled soft drink with either sugar, caffeine, or neither ingredient. A comparison of resting state spectral power shows a substantial decrease in alpha and beta power after caffeine consumption relative to control. Despite attenuation of the frequency range used for the control signal, caffeine average BCI performance was the same as control. Our work provides a useful characterization of caffeine, the world's most popular stimulant, on brain signal frequencies and their effect on BCI performance.
GPU-based real-time soft tissue deformation with cutting and haptic feedback.
Courtecuisse, Hadrien; Jung, Hoeryong; Allard, Jérémie; Duriez, Christian; Lee, Doo Yong; Cotin, Stéphane
2010-12-01
This article describes a series of contributions in the field of real-time simulation of soft tissue biomechanics. These contributions address various requirements for interactive simulation of complex surgical procedures. In particular, this article presents results in the areas of soft tissue deformation, contact modelling, simulation of cutting, and haptic rendering, which are all relevant to a variety of medical interventions. The contributions described in this article share a common underlying model of deformation and rely on GPU implementations to significantly improve computation times. This consistency in the modelling technique and computational approach ensures coherent results as well as efficient, robust and flexible solutions. Copyright © 2010 Elsevier Ltd. All rights reserved.
The rotation-powered nature of some soft gamma-ray repeaters and anomalous X-ray pulsars
NASA Astrophysics Data System (ADS)
Coelho, Jaziel G.; Cáceres, D. L.; de Lima, R. C. R.; Malheiro, M.; Rueda, J. A.; Ruffini, R.
2017-03-01
Context. Soft gamma-ray repeaters (SGRs) and anomalous X-ray pulsars (AXPs) are slow rotating isolated pulsars whose energy reservoir is still matter of debate. Adopting neutron star (NS) fiducial parameters; mass M = 1.4 M⊙, radius R = 10 km, and moment of inertia, I = 1045 g cm2, the rotational energy loss, Ėrot, is lower than the observed luminosity (dominated by the X-rays) LX for many of the sources. Aims: We investigate the possibility that some members of this family could be canonical rotation-powered pulsars using realistic NS structure parameters instead of fiducial values. Methods: We compute the NS mass, radius, moment of inertia and angular momentum from numerical integration of the axisymmetric general relativistic equations of equilibrium. We then compute the entire range of allowed values of the rotational energy loss, Ėrot, for the observed values of rotation period P and spin-down rate Ṗ. We also estimate the surface magnetic field using a general relativistic model of a rotating magnetic dipole. Results: We show that realistic NS parameters lowers the estimated value of the magnetic field and radiation efficiency, LX/Ėrot, with respect to estimates based on fiducial NS parameters. We show that nine SGRs/AXPs can be described as canonical pulsars driven by the NS rotational energy, for LX computed in the soft (2-10 keV) X-ray band. We compute the range of NS masses for which LX/Ėrot< 1. We discuss the observed hard X-ray emission in three sources of the group of nine potentially rotation-powered NSs. This additional hard X-ray component dominates over the soft one leading to LX/Ėrot > 1 in two of them. Conclusions: We show that 9 SGRs/AXPs can be rotation-powered NSs if we analyze their X-ray luminosity in the soft 2-10 keV band. Interestingly, four of them show radio emission and six have been associated with supernova remnants (including Swift J1834.9-0846 the first SGR observed with a surrounding wind nebula). These observations give additional support to our results of a natural explanation of these sources in terms of ordinary pulsars. Including the hard X-ray emission observed in three sources of the group of potential rotation-powered NSs, this number of sources with LX/Ėrot< 1 becomes seven. It remains open to verification 1) the accuracy of the estimated distances and 2) the possible contribution of the associated supernova remnants to the hard X-ray emission.
A comparative approach to computer aided design model of a dog femur.
Turamanlar, O; Verim, O; Karabulut, A
2016-01-01
Computer assisted technologies offer new opportunities in medical imaging and rapid prototyping in biomechanical engineering. Three dimensional (3D) modelling of soft tissues and bones are becoming more important. The accuracy of the analysis in modelling processes depends on the outline of the tissues derived from medical images. The aim of this study is the evaluation of the accuracy of 3D models of a dog femur derived from computed tomography data by using point cloud method and boundary line method on several modelling software. Solidworks, Rapidform and 3DSMax software were used to create 3D models and outcomes were evaluated statistically. The most accurate 3D prototype of the dog femur was created with stereolithography method using rapid prototype device. Furthermore, the linearity of the volumes of models was investigated between software and the constructed models. The difference between the software and real models manifests the sensitivity of the software and the devices used in this manner.
Dimensionality and noise in energy selective x-ray imaging
DOE Office of Scientific and Technical Information (OSTI.GOV)
Alvarez, Robert E.
Purpose: To develop and test a method to quantify the effect of dimensionality on the noise in energy selective x-ray imaging.Methods: The Cramèr-Rao lower bound (CRLB), a universal lower limit of the covariance of any unbiased estimator, is used to quantify the noise. It is shown that increasing dimensionality always increases, or at best leaves the same, the variance. An analytic formula for the increase in variance in an energy selective x-ray system is derived. The formula is used to gain insight into the dependence of the increase in variance on the properties of the additional basis functions, the measurementmore » noise covariance, and the source spectrum. The formula is also used with computer simulations to quantify the dependence of the additional variance on these factors. Simulated images of an object with three materials are used to demonstrate the trade-off of increased information with dimensionality and noise. The images are computed from energy selective data with a maximum likelihood estimator.Results: The increase in variance depends most importantly on the dimension and on the properties of the additional basis functions. With the attenuation coefficients of cortical bone, soft tissue, and adipose tissue as the basis functions, the increase in variance of the bone component from two to three dimensions is 1.4 × 10{sup 3}. With the soft tissue component, it is 2.7 × 10{sup 4}. If the attenuation coefficient of a high atomic number contrast agent is used as the third basis function, there is only a slight increase in the variance from two to three basis functions, 1.03 and 7.4 for the bone and soft tissue components, respectively. The changes in spectrum shape with beam hardening also have a substantial effect. They increase the variance by a factor of approximately 200 for the bone component and 220 for the soft tissue component as the soft tissue object thickness increases from 1 to 30 cm. Decreasing the energy resolution of the detectors increases the variance of the bone component markedly with three dimension processing, approximately a factor of 25 as the resolution decreases from 100 to 3 bins. The increase with two dimension processing for adipose tissue is a factor of two and with the contrast agent as the third material for two or three dimensions is also a factor of two for both components. The simulated images show that a maximum likelihood estimator can be used to process energy selective x-ray data to produce images with noise close to the CRLB.Conclusions: The method presented can be used to compute the effects of the object attenuation coefficients and the x-ray system properties on the relationship of dimensionality and noise in energy selective x-ray imaging systems.« less
On Some Nonclassical Algebraic Properties of Interval-Valued Fuzzy Soft Sets
2014-01-01
Interval-valued fuzzy soft sets realize a hybrid soft computing model in a general framework. Both Molodtsov's soft sets and interval-valued fuzzy sets can be seen as special cases of interval-valued fuzzy soft sets. In this study, we first compare four different types of interval-valued fuzzy soft subsets and reveal the relations among them. Then we concentrate on investigating some nonclassical algebraic properties of interval-valued fuzzy soft sets under the soft product operations. We show that some fundamental algebraic properties including the commutative and associative laws do not hold in the conventional sense, but hold in weaker forms characterized in terms of the relation =L. We obtain a number of algebraic inequalities of interval-valued fuzzy soft sets characterized by interval-valued fuzzy soft inclusions. We also establish the weak idempotent law and the weak absorptive law of interval-valued fuzzy soft sets using interval-valued fuzzy soft J-equal relations. It is revealed that the soft product operations ∧ and ∨ of interval-valued fuzzy soft sets do not always have similar algebraic properties. Moreover, we find that only distributive inequalities described by the interval-valued fuzzy soft L-inclusions hold for interval-valued fuzzy soft sets. PMID:25143964
On some nonclassical algebraic properties of interval-valued fuzzy soft sets.
Liu, Xiaoyan; Feng, Feng; Zhang, Hui
2014-01-01
Interval-valued fuzzy soft sets realize a hybrid soft computing model in a general framework. Both Molodtsov's soft sets and interval-valued fuzzy sets can be seen as special cases of interval-valued fuzzy soft sets. In this study, we first compare four different types of interval-valued fuzzy soft subsets and reveal the relations among them. Then we concentrate on investigating some nonclassical algebraic properties of interval-valued fuzzy soft sets under the soft product operations. We show that some fundamental algebraic properties including the commutative and associative laws do not hold in the conventional sense, but hold in weaker forms characterized in terms of the relation = L . We obtain a number of algebraic inequalities of interval-valued fuzzy soft sets characterized by interval-valued fuzzy soft inclusions. We also establish the weak idempotent law and the weak absorptive law of interval-valued fuzzy soft sets using interval-valued fuzzy soft J-equal relations. It is revealed that the soft product operations ∧ and ∨ of interval-valued fuzzy soft sets do not always have similar algebraic properties. Moreover, we find that only distributive inequalities described by the interval-valued fuzzy soft L-inclusions hold for interval-valued fuzzy soft sets.
[Soft- and hardware support for the setup for computer tracking of radiation teletherapy].
Tarutin, I G; Piliavets, V I; Strakh, A G; Minenko, V F; Golubovskiĭ, A I
1983-06-01
A hard and soft ware computer assisted complex has been worked out for gamma-beam therapy. The complex included all radiotherapeutic units, including a Siemens program controlled betatron with an energy of 42 MEV computer ES-1022, a Medigraf system of the processing of graphic information, a Mars-256 system for control over the homogeneity of distribution of dose rate on the field of irradiation and a package of mathematical programs to select a plan of irradiation of various tumor sites. The prospects of the utilization of such complexes in the dosimetric support of radiation therapy are discussed.
EUV/soft x-ray spectra for low B neutron stars
NASA Technical Reports Server (NTRS)
Romani, Roger W.; Rajagopal, Mohan; Rogers, Forrest J.; Iglesias, Carlos A.
1995-01-01
Recent ROSAT and EUVE detections of spin-powered neutron stars suggest that many emit 'thermal' radiation, peaking in the EUV/soft X-ray band. These data constrain the neutron stars' thermal history, but interpretation requires comparison with model atmosphere computations, since emergent spectra depend strongly on the surface composition and magnetic field. As recent opacity computations show substantial change to absorption cross sections at neutron star photospheric conditions, we report here on new model atmosphere computations employing such data. The results are compared with magnetic atmosphere models and applied to PSR J0437-4715, a low field neutron star.
NASA Astrophysics Data System (ADS)
De Lorenzo, Danilo; De Momi, Elena; Beretta, Elisa; Cerveri, Pietro; Perona, Franco; Ferrigno, Giancarlo
2009-02-01
Computer Assisted Orthopaedic Surgery (CAOS) systems improve the results and the standardization of surgical interventions. Anatomical landmarks and bone surface detection is straightforward to either register the surgical space with the pre-operative imaging space and to compute biomechanical parameters for prosthesis alignment. Surface points acquisition increases the intervention invasiveness and can be influenced by the soft tissue layer interposition (7-15mm localization errors). This study is aimed at evaluating the accuracy of a custom-made A-mode ultrasound (US) system for non invasive detection of anatomical landmarks and surfaces. A-mode solutions eliminate the necessity of US images segmentation, offers real-time signal processing and requires less invasive equipment. The system consists in a single transducer US probe optically tracked, a pulser/receiver and an FPGA-based board, which is responsible for logic control command generation and for real-time signal processing and three custom-made board (signal acquisition, blanking and synchronization). We propose a new calibration method of the US system. The experimental validation was then performed measuring the length of known-shape polymethylmethacrylate boxes filled with pure water and acquiring bone surface points on a bovine bone phantom covered with soft-tissue mimicking materials. Measurement errors were computed through MR and CT images acquisitions of the phantom. Points acquisition on bone surface with the US system demonstrated lower errors (1.2mm) than standard pointer acquisition (4.2mm).
NASA Astrophysics Data System (ADS)
Tripathi, Anurag; Khakhar, D. V.
2010-04-01
We study smooth, slightly inelastic particles flowing under gravity on a bumpy inclined plane using event-driven and discrete-element simulations. Shallow layers (ten particle diameters) are used to enable simulation using the event-driven method within reasonable computational times. Steady flows are obtained in a narrow range of angles (13°-14.5°) ; lower angles result in stopping of the flow and higher angles in continuous acceleration. The flow is relatively dense with the solid volume fraction, ν≈0.5 , and significant layering of particles is observed. We derive expressions for the stress, heat flux, and dissipation for the hard and soft particle models from first principles. The computed mean velocity, temperature, stress, dissipation, and heat flux profiles of hard particles are compared to soft particle results for different values of stiffness constant (k) . The value of stiffness constant for which results for hard and soft particles are identical is found to be k≥2×106mg/d , where m is the mass of a particle, g is the acceleration due to gravity, and d is the particle diameter. We compare the simulation results to constitutive relations obtained from the kinetic theory of Jenkins and Richman [J. T. Jenkins and M. W. Richman, Arch. Ration. Mech. Anal. 87, 355 (1985)] for pressure, dissipation, viscosity, and thermal conductivity. We find that all the quantities are very well predicted by kinetic theory for volume fractions ν<0.5 . At higher densities, obtained for thicker layers ( H=15d and H=20d ), the kinetic theory does not give accurate prediction. Deviations of the kinetic theory predictions from simulation results are relatively small for dissipation and heat flux and most significant deviations are observed for shear viscosity and pressure. The results indicate the range of applicability of soft particle simulations and kinetic theory for dense flows.
Nelson, Todd G.; Zimmerman, Trent K.; Fernelius, Janette D.; Magleby, Spencer P.; Howell, Larry L.
2016-01-01
Packing soft-sheet materials of approximately zero bending stiffness using Soft Origami (origami patterns applied to soft-sheet materials) into cylindrical volumes and their deployment via mechanisms or internal pressure (inflation) is of interest in fields including automobile airbags, deployable heart stents, inflatable space habitats, and dirigible and parachute packing. This paper explores twofold patterns, the ‘flasher’ and the ‘inverted-cone fold’, for packing soft-sheet materials into cylindrical volumes. Two initial packing methods and mechanisms are examined for each of the flasher and inverted-cone fold patterns. An application to driver’s side automobile airbags is performed, and deployment tests are completed to compare the influence of packing method and origami pattern on deployment performance. Following deployment tests, two additional packing methods for the inverted-cone fold pattern are explored and applied to automobile airbags. It is shown that modifying the packing method (using different methods to impose the same base pattern on the soft-sheet material) can lead to different deployment performance. In total, two origami patterns and six packing methods are examined, and the benefits of using Soft Origami patterns and packing methods are discussed. Soft Origami is presented as a viable method for efficiently packing soft-sheet materials into cylindrical volumes. PMID:27703707
NASA Astrophysics Data System (ADS)
Bruton, Jared T.; Nelson, Todd G.; Zimmerman, Trent K.; Fernelius, Janette D.; Magleby, Spencer P.; Howell, Larry L.
2016-09-01
Packing soft-sheet materials of approximately zero bending stiffness using Soft Origami (origami patterns applied to soft-sheet materials) into cylindrical volumes and their deployment via mechanisms or internal pressure (inflation) is of interest in fields including automobile airbags, deployable heart stents, inflatable space habitats, and dirigible and parachute packing. This paper explores twofold patterns, the `flasher' and the `inverted-cone fold', for packing soft-sheet materials into cylindrical volumes. Two initial packing methods and mechanisms are examined for each of the flasher and inverted-cone fold patterns. An application to driver's side automobile airbags is performed, and deployment tests are completed to compare the influence of packing method and origami pattern on deployment performance. Following deployment tests, two additional packing methods for the inverted-cone fold pattern are explored and applied to automobile airbags. It is shown that modifying the packing method (using different methods to impose the same base pattern on the soft-sheet material) can lead to different deployment performance. In total, two origami patterns and six packing methods are examined, and the benefits of using Soft Origami patterns and packing methods are discussed. Soft Origami is presented as a viable method for efficiently packing soft-sheet materials into cylindrical volumes.
Bruton, Jared T; Nelson, Todd G; Zimmerman, Trent K; Fernelius, Janette D; Magleby, Spencer P; Howell, Larry L
2016-09-01
Packing soft-sheet materials of approximately zero bending stiffness using Soft Origami (origami patterns applied to soft-sheet materials) into cylindrical volumes and their deployment via mechanisms or internal pressure (inflation) is of interest in fields including automobile airbags, deployable heart stents, inflatable space habitats, and dirigible and parachute packing. This paper explores twofold patterns, the 'flasher' and the 'inverted-cone fold', for packing soft-sheet materials into cylindrical volumes. Two initial packing methods and mechanisms are examined for each of the flasher and inverted-cone fold patterns. An application to driver's side automobile airbags is performed, and deployment tests are completed to compare the influence of packing method and origami pattern on deployment performance. Following deployment tests, two additional packing methods for the inverted-cone fold pattern are explored and applied to automobile airbags. It is shown that modifying the packing method (using different methods to impose the same base pattern on the soft-sheet material) can lead to different deployment performance. In total, two origami patterns and six packing methods are examined, and the benefits of using Soft Origami patterns and packing methods are discussed. Soft Origami is presented as a viable method for efficiently packing soft-sheet materials into cylindrical volumes.
[Development of a digital chest phantom for studies on energy subtraction techniques].
Hayashi, Norio; Taniguchi, Anna; Noto, Kimiya; Shimosegawa, Masayuki; Ogura, Toshihiro; Doi, Kunio
2014-03-01
Digital chest phantoms continue to play a significant role in optimizing imaging parameters for chest X-ray examinations. The purpose of this study was to develop a digital chest phantom for studies on energy subtraction techniques under ideal conditions without image noise. Computed tomography (CT) images from the LIDC (Lung Image Database Consortium) were employed to develop a digital chest phantom. The method consisted of the following four steps: 1) segmentation of the lung and bone regions on CT images; 2) creation of simulated nodules; 3) transformation to attenuation coefficient maps from the segmented images; and 4) projection from attenuation coefficient maps. To evaluate the usefulness of digital chest phantoms, we determined the contrast of the simulated nodules in projection images of the digital chest phantom using high and low X-ray energies, soft tissue images obtained by energy subtraction, and "gold standard" images of the soft tissues. Using our method, the lung and bone regions were segmented on the original CT images. The contrast of simulated nodules in soft tissue images obtained by energy subtraction closely matched that obtained using the gold standard images. We thus conclude that it is possible to carry out simulation studies based on energy subtraction techniques using the created digital chest phantoms. Our method is potentially useful for performing simulation studies for optimizing the imaging parameters in chest X-ray examinations.
Fast equilibration protocol for million atom systems of highly entangled linear polyethylene chains
DOE Office of Scientific and Technical Information (OSTI.GOV)
Sliozberg, Yelena R.; TKC Global, Inc., Aberdeen Proving Ground, Maryland 21005; Kröger, Martin
Equilibrated systems of entangled polymer melts cannot be produced using direct brute force equilibration due to the slow reptation dynamics exhibited by high molecular weight chains. Instead, these dense systems are produced using computational techniques such as Monte Carlo-Molecular Dynamics hybrid algorithms, though the use of soft potentials has also shown promise mainly for coarse-grained polymeric systems. Through the use of soft-potentials, the melt can be equilibrated via molecular dynamics at intermediate and long length scales prior to switching to a Lennard-Jones potential. We will outline two different equilibration protocols, which use various degrees of information to produce the startingmore » configurations. In one protocol, we use only the equilibrium bond angle, bond length, and target density during the construction of the simulation cell, where the information is obtained from available experimental data and extracted from the force field without performing any prior simulation. In the second protocol, we moreover utilize the equilibrium radial distribution function and dihedral angle distribution. This information can be obtained from experimental data or from a simulation of short unentangled chains. Both methods can be used to prepare equilibrated and highly entangled systems, but the second protocol is much more computationally efficient. These systems can be strictly monodisperse or optionally polydisperse depending on the starting chain distribution. Our protocols, which utilize a soft-core harmonic potential, will be applied for the first time to equilibrate a million particle system of polyethylene chains consisting of 1000 united atoms at various temperatures. Calculations of structural and entanglement properties demonstrate that this method can be used as an alternative towards the generation of entangled equilibrium structures.« less
Enhanced conformational sampling using enveloping distribution sampling.
Lin, Zhixiong; van Gunsteren, Wilfred F
2013-10-14
To lessen the problem of insufficient conformational sampling in biomolecular simulations is still a major challenge in computational biochemistry. In this article, an application of the method of enveloping distribution sampling (EDS) is proposed that addresses this challenge and its sampling efficiency is demonstrated in simulations of a hexa-β-peptide whose conformational equilibrium encompasses two different helical folds, i.e., a right-handed 2.7(10∕12)-helix and a left-handed 3(14)-helix, separated by a high energy barrier. Standard MD simulations of this peptide using the GROMOS 53A6 force field did not reach convergence of the free enthalpy difference between the two helices even after 500 ns of simulation time. The use of soft-core non-bonded interactions in the centre of the peptide did enhance the number of transitions between the helices, but at the same time led to neglect of relevant helical configurations. In the simulations of a two-state EDS reference Hamiltonian that envelops both the physical peptide and the soft-core peptide, sampling of the conformational space of the physical peptide ensures that physically relevant conformations can be visited, and sampling of the conformational space of the soft-core peptide helps to enhance the transitions between the two helices. The EDS simulations sampled many more transitions between the two helices and showed much faster convergence of the relative free enthalpy of the two helices compared with the standard MD simulations with only a slightly larger computational effort to determine optimized EDS parameters. Combined with various methods to smoothen the potential energy surface, the proposed EDS application will be a powerful technique to enhance the sampling efficiency in biomolecular simulations.
Swaine, Jillian M; Moe, Andrew; Breidahl, William; Bader, Daniel L; Oomens, Cees W J; Lester, Leanne; O'Loughlin, Edmond; Santamaria, Nick; Stacey, Michael C
2018-02-01
High strain in soft tissues that overly bony prominences are considered a risk factor for pressure ulcers (PUs) following spinal cord impairment (SCI) and have been computed using Finite Element methods (FEM). The aim of this study was to translate a MRI protocol into ultrasound (US) and determine between-operator reliability of expert sonographers measuring diameter of the inferior curvature of the ischial tuberosity (IT) and the thickness of the overlying soft tissue layers on able-bodied (AB) and SCI using real-time ultrasound. Part 1: Fourteen AB participants with a mean age of 36.7 ± 12.09 years with 7 males and 7 females had their 3 soft tissue layers in loaded and unloaded sitting measured independently by 2 sonographers: tendon/muscle, skin/fat and total soft tissue and the diameter of the IT in its short and long axis. Part 2: Nineteen participants with SCI were screened, three were excluded due to abnormal skin signs, and eight participants (42%) were excluded for abnormal US signs with normal skin. Eight SCI participants with a mean age of 31.6 ± 13.6 years and all male with 4 paraplegics and 4 tetraplegics were measured by the same sonographers for skin, fat, tendon, muscle and total. Skin/fat and tendon/muscle were computed. AB between-operator reliability was good (ICC = 0.81-0.90) for 3 soft tissues layers in unloaded and loaded sitting and poor for both IT short and long axis (ICC = -0.028 and -0.01). SCI between-operator reliability was good in unloaded and loaded for total, muscle, fat, skin/fat, tendon/muscle (ICC = 0.75-0.97) and poor for tendon (ICC = 0.26 unloaded and ICC = -0.71 loaded) and skin (ICC = 0.37 unloaded and ICC = 0.10). A MRI protocol was successfully adapted for a reliable 3 soft tissue layer model and could be used in a 2-D FEM model designed to estimate soft tissue strain as a novel risk factor for the development of a PU. Copyright © 2017 The Authors. Published by Elsevier Ltd.. All rights reserved.
Evaluating Application Resilience with XRay
DOE Office of Scientific and Technical Information (OSTI.GOV)
Chen, Sui; Bronevetsky, Greg; Li, Bin
2015-05-07
The rising count and shrinking feature size of transistors within modern computers is making them increasingly vulnerable to various types of soft faults. This problem is especially acute in high-performance computing (HPC) systems used for scientific computing, because these systems include many thousands of compute cores and nodes, all of which may be utilized in a single large-scale run. The increasing vulnerability of HPC applications to errors induced by soft faults is motivating extensive work on techniques to make these applications more resiilent to such faults, ranging from generic techniques such as replication or checkpoint/restart to algorithmspecific error detection andmore » tolerance techniques. Effective use of such techniques requires a detailed understanding of how a given application is affected by soft faults to ensure that (i) efforts to improve application resilience are spent in the code regions most vulnerable to faults and (ii) the appropriate resilience technique is applied to each code region. This paper presents XRay, a tool to view the application vulnerability to soft errors, and illustrates how XRay can be used in the context of a representative application. In addition to providing actionable insights into application behavior XRay automatically selects the number of fault injection experiments required to provide an informative view of application behavior, ensuring that the information is statistically well-grounded without performing unnecessary experiments.« less
Chattaraj, Pratim K; Ayers, Paul W; Melin, Junia
2007-08-07
Ayers, Parr, and Pearson recently showed that insight into the hard/soft acid/base (HSAB) principle could be obtained by analyzing the energy of reactions in hard/soft exchange reactions, i.e., reactions in which a soft acid replaces a hard acid or a soft base replaces a hard base [J. Chem. Phys., 2006, 124, 194107]. We show, in accord with the maximum hardness principle, that the hardness increases for favorable hard/soft exchange reactions and decreases when the HSAB principle indicates that hard/soft exchange reactions are unfavorable. This extends the previous work of the authors, which treated only the "double hard/soft exchange" reaction [P. K. Chattaraj and P. W. Ayers, J. Chem. Phys., 2005, 123, 086101]. We also discuss two different approaches to computing the hardness of molecules from the hardness of the composing fragments, and explain how the results differ. In the present context, it seems that the arithmetic mean of fragment softnesses is the preferable definition.
NASA Astrophysics Data System (ADS)
Hashim, Roslan; Roy, Chandrabhushan; Motamedi, Shervin; Shamshirband, Shahaboddin; Petković, Dalibor; Gocic, Milan; Lee, Siew Cheng
2016-05-01
Rainfall is a complex atmospheric process that varies over time and space. Researchers have used various empirical and numerical methods to enhance estimation of rainfall intensity. We developed a novel prediction model in this study, with the emphasis on accuracy to identify the most significant meteorological parameters having effect on rainfall. For this, we used five input parameters: wet day frequency (dwet), vapor pressure (e̅a), and maximum and minimum air temperatures (Tmax and Tmin) as well as cloud cover (cc). The data were obtained from the Indian Meteorological Department for the Patna city, Bihar, India. Further, a type of soft-computing method, known as the adaptive-neuro-fuzzy inference system (ANFIS), was applied to the available data. In this respect, the observation data from 1901 to 2000 were employed for testing, validating, and estimating monthly rainfall via the simulated model. In addition, the ANFIS process for variable selection was implemented to detect the predominant variables affecting the rainfall prediction. Finally, the performance of the model was compared to other soft-computing approaches, including the artificial neural network (ANN), support vector machine (SVM), extreme learning machine (ELM), and genetic programming (GP). The results revealed that ANN, ELM, ANFIS, SVM, and GP had R2 of 0.9531, 0.9572, 0.9764, 0.9525, and 0.9526, respectively. Therefore, we conclude that the ANFIS is the best method among all to predict monthly rainfall. Moreover, dwet was found to be the most influential parameter for rainfall prediction, and the best predictor of accuracy. This study also identified sets of two and three meteorological parameters that show the best predictions.
NASA Astrophysics Data System (ADS)
Zikmund, T.; Novotná, M.; Kavková, M.; Tesařová, M.; Kaucká, M.; Szarowská, B.; Adameyko, I.; Hrubá, E.; Buchtová, M.; Dražanová, E.; Starčuk, Z.; Kaiser, J.
2018-02-01
The biomedically focused brain research is largely performed on laboratory mice considering a high homology between the human and mouse genomes. A brain has an intricate and highly complex geometrical structure that is hard to display and analyse using only 2D methods. Applying some fast and efficient methods of brain visualization in 3D will be crucial for the neurobiology in the future. A post-mortem analysis of experimental animals' brains usually involves techniques such as magnetic resonance and computed tomography. These techniques are employed to visualize abnormalities in the brains' morphology or reparation processes. The X-ray computed microtomography (micro CT) plays an important role in the 3D imaging of internal structures of a large variety of soft and hard tissues. This non-destructive technique is applied in biological studies because the lab-based CT devices enable to obtain a several-micrometer resolution. However, this technique is always used along with some visualization methods, which are based on the tissue staining and thus differentiate soft tissues in biological samples. Here, a modified chemical contrasting protocol of tissues for a micro CT usage is introduced as the best tool for ex vivo 3D imaging of a post-mortem mouse brain. This way, the micro CT provides a high spatial resolution of the brain microscopic anatomy together with a high tissue differentiation contrast enabling to identify more anatomical details in the brain. As the micro CT allows a consequent reconstruction of the brain structures into a coherent 3D model, some small morphological changes can be given into context of their mutual spatial relationships.
Autonomous control systems: applications to remote sensing and image processing
NASA Astrophysics Data System (ADS)
Jamshidi, Mohammad
2001-11-01
One of the main challenges of any control (or image processing) paradigm is being able to handle complex systems under unforeseen uncertainties. A system may be called complex here if its dimension (order) is too high and its model (if available) is nonlinear, interconnected, and information on the system is uncertain such that classical techniques cannot easily handle the problem. Examples of complex systems are power networks, space robotic colonies, national air traffic control system, and integrated manufacturing plant, the Hubble Telescope, the International Space Station, etc. Soft computing, a consortia of methodologies such as fuzzy logic, neuro-computing, genetic algorithms and genetic programming, has proven to be powerful tools for adding autonomy and semi-autonomy to many complex systems. For such systems the size of soft computing control architecture will be nearly infinite. In this paper new paradigms using soft computing approaches are utilized to design autonomous controllers and image enhancers for a number of application areas. These applications are satellite array formations for synthetic aperture radar interferometry (InSAR) and enhancement of analog and digital images.
Image Analysis via Soft Computing: Prototype Applications at NASA KSC and Product Commercialization
NASA Technical Reports Server (NTRS)
Dominguez, Jesus A.; Klinko, Steve
2011-01-01
This slide presentation reviews the use of "soft computing" which differs from "hard computing" in that it is more tolerant of imprecision, partial truth, uncertainty, and approximation and its use in image analysis. Soft computing provides flexible information processing to handle real life ambiguous situations and achieve tractability, robustness low solution cost, and a closer resemblance to human decision making. Several systems are or have been developed: Fuzzy Reasoning Edge Detection (FRED), Fuzzy Reasoning Adaptive Thresholding (FRAT), Image enhancement techniques, and visual/pattern recognition. These systems are compared with examples that show the effectiveness of each. NASA applications that are reviewed are: Real-Time (RT) Anomaly Detection, Real-Time (RT) Moving Debris Detection and the Columbia Investigation. The RT anomaly detection reviewed the case of a damaged cable for the emergency egress system. The use of these techniques is further illustrated in the Columbia investigation with the location and detection of Foam debris. There are several applications in commercial usage: image enhancement, human screening and privacy protection, visual inspection, 3D heart visualization, tumor detections and x ray image enhancement.
A program to compute the soft Robinson-Foulds distance between phylogenetic networks.
Lu, Bingxin; Zhang, Louxin; Leong, Hon Wai
2017-03-14
Over the past two decades, phylogenetic networks have been studied to model reticulate evolutionary events. The relationships among phylogenetic networks, phylogenetic trees and clusters serve as the basis for reconstruction and comparison of phylogenetic networks. To understand these relationships, two problems are raised: the tree containment problem, which asks whether a phylogenetic tree is displayed in a phylogenetic network, and the cluster containment problem, which asks whether a cluster is represented at a node in a phylogenetic network. Both the problems are NP-complete. A fast exponential-time algorithm for the cluster containment problem on arbitrary networks is developed and implemented in C. The resulting program is further extended into a computer program for fast computation of the Soft Robinson-Foulds distance between phylogenetic networks. Two computer programs are developed for facilitating reconstruction and validation of phylogenetic network models in evolutionary and comparative genomics. Our simulation tests indicated that they are fast enough for use in practice. Additionally, the distribution of the Soft Robinson-Foulds distance between phylogenetic networks is demonstrated to be unlikely normal by our simulation data.
NASA Technical Reports Server (NTRS)
1972-01-01
The solar imaging X-ray telescope experiment (designated the S-056 experiment) is described. It will photograph the sun in the far ultraviolet or soft X-ray region. Because of the imaging characteristics of this telescope and the necessity of using special techniques for capturing images on film at these wave lengths, methods were developed for computer processing of the photographs. The problems of image restoration were addressed to develop and test digital computer techniques for applying a deconvolution process to restore overall S-056 image quality. Additional techniques for reducing or eliminating the effects of noise and nonlinearity in S-056 photographs were developed.
Stereolithography: a potential new tool in forensic medicine.
Dolz, M S; Cina, S J; Smith, R
2000-06-01
Stereolithography is a computer-mediated method that can be used to quickly create anatomically correct three-dimensional epoxy and acrylic resin models from various types of medical data. Multiple imaging modalities can be exploited, including computed tomography and magnetic resonance imaging. The technology was first developed and used in 1986 to overcome limitations in previous computer-aided manufacturing/milling techniques. Stereolithography is presently used to accurately reproduce both the external and internal anatomy of body structures. Current medical uses of stereolithography include preoperative planning of orthopedic and maxillofacial surgeries, the fabrication of custom prosthetic devices; and the assessment of the degree of bony and soft-tissue injury caused by trauma. We propose that there is a useful, as yet untapped, potential for this technology in forensic medicine.
CT Image Sequence Restoration Based on Sparse and Low-Rank Decomposition
Gou, Shuiping; Wang, Yueyue; Wang, Zhilong; Peng, Yong; Zhang, Xiaopeng; Jiao, Licheng; Wu, Jianshe
2013-01-01
Blurry organ boundaries and soft tissue structures present a major challenge in biomedical image restoration. In this paper, we propose a low-rank decomposition-based method for computed tomography (CT) image sequence restoration, where the CT image sequence is decomposed into a sparse component and a low-rank component. A new point spread function of Weiner filter is employed to efficiently remove blur in the sparse component; a wiener filtering with the Gaussian PSF is used to recover the average image of the low-rank component. And then we get the recovered CT image sequence by combining the recovery low-rank image with all recovery sparse image sequence. Our method achieves restoration results with higher contrast, sharper organ boundaries and richer soft tissue structure information, compared with existing CT image restoration methods. The robustness of our method was assessed with numerical experiments using three different low-rank models: Robust Principle Component Analysis (RPCA), Linearized Alternating Direction Method with Adaptive Penalty (LADMAP) and Go Decomposition (GoDec). Experimental results demonstrated that the RPCA model was the most suitable for the small noise CT images whereas the GoDec model was the best for the large noisy CT images. PMID:24023764
Soft bilateral filtering volumetric shadows using cube shadow maps
Ali, Hatam H.; Sunar, Mohd Shahrizal; Kolivand, Hoshang
2017-01-01
Volumetric shadows often increase the realism of rendered scenes in computer graphics. Typical volumetric shadows techniques do not provide a smooth transition effect in real-time with conservation on crispness of boundaries. This research presents a new technique for generating high quality volumetric shadows by sampling and interpolation. Contrary to conventional ray marching method, which requires extensive time, this proposed technique adopts downsampling in calculating ray marching. Furthermore, light scattering is computed in High Dynamic Range buffer to generate tone mapping. The bilateral interpolation is used along a view rays to smooth transition of volumetric shadows with respect to preserving-edges. In addition, this technique applied a cube shadow map to create multiple shadows. The contribution of this technique isreducing the number of sample points in evaluating light scattering and then introducing bilateral interpolation to improve volumetric shadows. This contribution is done by removing the inherent deficiencies significantly in shadow maps. This technique allows obtaining soft marvelous volumetric shadows, having a good performance and high quality, which show its potential for interactive applications. PMID:28632740
Wein, Wolfgang; Karamalis, Athanasios; Baumgartner, Adrian; Navab, Nassir
2015-06-01
The transfer of preoperative CT data into the tracking system coordinates within an operating room is of high interest for computer-aided orthopedic surgery. In this work, we introduce a solution for intra-operative ultrasound-CT registration of bones. We have developed methods for fully automatic real-time bone detection in ultrasound images and global automatic registration to CT. The bone detection algorithm uses a novel bone-specific feature descriptor and was thoroughly evaluated on both in-vivo and ex-vivo data. A global optimization strategy aligns the bone surface, followed by a soft tissue aware intensity-based registration to provide higher local registration accuracy. We evaluated the system on femur, tibia and fibula anatomy in a cadaver study with human legs, where magnetically tracked bone markers were implanted to yield ground truth information. An overall median system error of 3.7 mm was achieved on 11 datasets. Global and fully automatic registration of bones aquired with ultrasound to CT is feasible, with bone detection and tracking operating in real time for immediate feedback to the surgeon.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Liu, X; Belcher, AH; Wiersma, R
Purpose: In radiation therapy optimization the constraints can be either hard constraints which must be satisfied or soft constraints which are included but do not need to be satisfied exactly. Currently the voxel dose constraints are viewed as soft constraints and included as a part of the objective function and approximated as an unconstrained problem. However in some treatment planning cases the constraints should be specified as hard constraints and solved by constrained optimization. The goal of this work is to present a computation efficiency graph form alternating direction method of multipliers (ADMM) algorithm for constrained quadratic treatment planning optimizationmore » and compare it with several commonly used algorithms/toolbox. Method: ADMM can be viewed as an attempt to blend the benefits of dual decomposition and augmented Lagrangian methods for constrained optimization. Various proximal operators were first constructed as applicable to quadratic IMRT constrained optimization and the problem was formulated in a graph form of ADMM. A pre-iteration operation for the projection of a point to a graph was also proposed to further accelerate the computation. Result: The graph form ADMM algorithm was tested by the Common Optimization for Radiation Therapy (CORT) dataset including TG119, prostate, liver, and head & neck cases. Both unconstrained and constrained optimization problems were formulated for comparison purposes. All optimizations were solved by LBFGS, IPOPT, Matlab built-in toolbox, CVX (implementing SeDuMi) and Mosek solvers. For unconstrained optimization, it was found that LBFGS performs the best, and it was 3–5 times faster than graph form ADMM. However, for constrained optimization, graph form ADMM was 8 – 100 times faster than the other solvers. Conclusion: A graph form ADMM can be applied to constrained quadratic IMRT optimization. It is more computationally efficient than several other commercial and noncommercial optimizers and it also used significantly less computer memory.« less
Benic, Goran I; Elmasry, Moustafa; Hämmerle, Christoph H F
2015-09-01
To examine the literature on novel digital imaging techniques for the assessment of outcomes in oral rehabilitation with dental implants. An electronic search of Medline and Embase databases including studies published prior to 28th December 2014 was performed and supplemented by a manual search. A synthesis of the publications was presented describing the use of computed tomography (CT), magnetic resonance imaging (MRI), ultrasonography, optical scanning, spectrophotometry or optical coherence tomography (OCT) related to the outcome measures in implant therapy. Most of the digital imaging techniques have not yet sufficiently been validated to be used for outcome measures in implant dentistry. In clinical research, cone beam CT (CBCT) is increasingly being used for 3D assessment of bone and soft tissue following augmentation procedures and implant placement. Currently, there are no effective methods for the reduction of artifacts around implants in CBCT. Optical scanning is being used for the 3D assessment of changes in the soft tissue contour. The combination of optical scan with pre-operative CBCT allows the determination of the implant position and its spatial relation to anatomical structures. Spectrophotometry is the method most commonly used to objectively assess the color match of reconstructions and peri-implant mucosa to natural dentition and gingiva. New optical imaging techniques may be considered possible approaches for monitoring peri-implant soft tissue health. MRI and ultrasonography appear promising non-ionizing radiation imaging modalities for the assessment of soft tissue and bone defect morphologies. Optical scanners and OCT may represent efficient clinical methods for accurate assessment of the misfit between the reconstructions and the implants. © 2015 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.
Baldwin, Mark A; Clary, Chadd; Maletsky, Lorin P; Rullkoetter, Paul J
2009-10-16
Verified computational models represent an efficient method for studying the relationship between articular geometry, soft-tissue constraint, and patellofemoral (PF) mechanics. The current study was performed to evaluate an explicit finite element (FE) modeling approach for predicting PF kinematics in the natural and implanted knee. Experimental three-dimensional kinematic data were collected on four healthy cadaver specimens in their natural state and after total knee replacement in the Kansas knee simulator during a simulated deep knee bend activity. Specimen-specific FE models were created from medical images and CAD implant geometry, and included soft-tissue structures representing medial-lateral PF ligaments and the quadriceps tendon. Measured quadriceps loads and prescribed tibiofemoral kinematics were used to predict dynamic kinematics of an isolated PF joint between 10 degrees and 110 degrees femoral flexion. Model sensitivity analyses were performed to determine the effect of rigid or deformable patellar representations and perturbed PF ligament mechanical properties (pre-tension and stiffness) on model predictions and computational efficiency. Predicted PF kinematics from the deformable analyses showed average root mean square (RMS) differences for the natural and implanted states of less than 3.1 degrees and 1.7 mm for all rotations and translations. Kinematic predictions with rigid bodies increased average RMS values slightly to 3.7 degrees and 1.9 mm with a five-fold decrease in computational time. Two-fold increases and decreases in PF ligament initial strain and linear stiffness were found to most adversely affect kinematic predictions for flexion, internal-external tilt and inferior-superior translation in both natural and implanted states. The verified models could be used to further investigate the effects of component alignment or soft-tissue variability on natural and implant PF mechanics.
Ramo, Nicole L.; Puttlitz, Christian M.
2018-01-01
Compelling evidence that many biological soft tissues display both strain- and time-dependent behavior has led to the development of fully non-linear viscoelastic modeling techniques to represent the tissue’s mechanical response under dynamic conditions. Since the current stress state of a viscoelastic material is dependent on all previous loading events, numerical analyses are complicated by the requirement of computing and storing the stress at each step throughout the load history. This requirement quickly becomes computationally expensive, and in some cases intractable, for finite element models. Therefore, we have developed a strain-dependent numerical integration approach for capturing non-linear viscoelasticity that enables calculation of the current stress from a strain-dependent history state variable stored from the preceding time step only, which improves both fitting efficiency and computational tractability. This methodology was validated based on its ability to recover non-linear viscoelastic coefficients from simulated stress-relaxation (six strain levels) and dynamic cyclic (three frequencies) experimental stress-strain data. The model successfully fit each data set with average errors in recovered coefficients of 0.3% for stress-relaxation fits and 0.1% for cyclic. The results support the use of the presented methodology to develop linear or non-linear viscoelastic models from stress-relaxation or cyclic experimental data of biological soft tissues. PMID:29293558
Townsend, Molly T; Sarigul-Klijn, Nesrin
2016-01-01
Simplified material models are commonly used in computational simulation of biological soft tissue as an approximation of the complicated material response and to minimize computational resources. However, the simulation of complex loadings, such as long-duration tissue swelling, necessitates complex models that are not easy to formulate. This paper strives to offer the updated Lagrangian formulation comprehensive procedure of various non-linear material models for the application of finite element analysis of biological soft tissues including a definition of the Cauchy stress and the spatial tangential stiffness. The relationships between water content, osmotic pressure, ionic concentration and the pore pressure stress of the tissue are discussed with the merits of these models and their applications.
Lee, Hyeonjong; Paek, Janghyun; Noh, Kwantae; Kwon, Kung-Rock
2017-08-21
Reproducing soft tissue contours around a pontic area is important for the fabrication of an esthetic prosthesis, especially in the anterior area. A gingival model that precisely replicates the soft tissue structure around the pontic area can be easily obtained by taking a pick-up impression of an interim fixed dental prosthesis. After a working cast is fabricated using the customary technique, the pick-up model is superimposed onto the working model for the pontic area using computer-aided design and manufacturing (CAD/CAM). A definitive restoration using this technique would be well adapted to the pontic base, which is formed by the interim prosthesis. © 2017 by the American College of Prosthodontists.
Face-based smoothed finite element method for real-time simulation of soft tissue
NASA Astrophysics Data System (ADS)
Mendizabal, Andrea; Bessard Duparc, Rémi; Bui, Huu Phuoc; Paulus, Christoph J.; Peterlik, Igor; Cotin, Stéphane
2017-03-01
In soft tissue surgery, a tumor and other anatomical structures are usually located using the preoperative CT or MR images. However, due to the deformation of the concerned tissues, this information suffers from inaccuracy when employed directly during the surgery. In order to account for these deformations in the planning process, the use of a bio-mechanical model of the tissues is needed. Such models are often designed using the finite element method (FEM), which is, however, computationally expensive, in particular when a high accuracy of the simulation is required. In our work, we propose to use a smoothed finite element method (S-FEM) in the context of modeling of the soft tissue deformation. This numerical technique has been introduced recently to overcome the overly stiff behavior of the standard FEM and to improve the solution accuracy and the convergence rate in solid mechanics problems. In this paper, a face-based smoothed finite element method (FS-FEM) using 4-node tetrahedral elements is presented. We show that in some cases, the method allows for reducing the number of degrees of freedom, while preserving the accuracy of the discretization. The method is evaluated on a simulation of a cantilever beam loaded at the free end and on a simulation of a 3D cube under traction and compression forces. Further, it is applied to the simulation of the brain shift and of the kidney's deformation. The results demonstrate that the method outperforms the standard FEM in a bending scenario and that has similar accuracy as the standard FEM in the simulations of the brain-shift and of the kidney's deformation.
Prediction of Scour below Flip Bucket using Soft Computing Techniques
NASA Astrophysics Data System (ADS)
Azamathulla, H. Md.; Ab Ghani, Aminuddin; Azazi Zakaria, Nor
2010-05-01
The accurate prediction of the depth of scour around hydraulic structure (trajectory spillways) has been based on the experimental studies and the equations developed are mainly empirical in nature. This paper evaluates the performance of the soft computing (intelligence) techiques, Adaptive Neuro-Fuzzy System (ANFIS) and Genetic expression Programming (GEP) approach, in prediction of scour below a flip bucket spillway. The results are very promising, which support the use of these intelligent techniques in prediction of highly non-linear scour parameters.
Speed challenge: a case for hardware implementation in soft-computing
NASA Technical Reports Server (NTRS)
Daud, T.; Stoica, A.; Duong, T.; Keymeulen, D.; Zebulum, R.; Thomas, T.; Thakoor, A.
2000-01-01
For over a decade, JPL has been actively involved in soft computing research on theory, architecture, applications, and electronics hardware. The driving force in all our research activities, in addition to the potential enabling technology promise, has been creation of a niche that imparts orders of magnitude speed advantage by implementation in parallel processing hardware with algorithms made especially suitable for hardware implementation. We review our work on neural networks, fuzzy logic, and evolvable hardware with selected application examples requiring real time response capabilities.
Panzer, Stephanie; Pernter, Patrizia; Piombino-Mascali, Dario; Jankauskas, Rimantas; Zesch, Stephanie; Rosendahl, Wilfried; Hotz, Gerhard; Zink, Albert R
2017-12-01
Purpose Soft tissues make a skeleton into a mummy and they allow for a diagnosis beyond osteology. Following the approach of structured reporting in clinical radiology, a recently developed checklist was used to evaluate the soft tissue preservation status of the Tyrolean Iceman using computed tomography (CT). The purpose of this study was to apply the "Checklist and Scoring System for the Assessment of Soft Tissue Preservation in CT Examinations of Human Mummies" to the Tyrolean Iceman, and to compare the Iceman's soft tissue preservation score to the scores calculated for other mummies. Materials and Methods A whole-body (CT) (SOMATOM Definition Flash, Siemens, Forchheim, Germany) consisting of five scans, performed in January 2013 in the Department of Radiodiagnostics, Central Hospital, Bolzano, was used (slice thickness 0.6 mm; kilovolt ranging from 80 to 140). For standardized evaluation the "CT Checklist and Scoring System for the Assessment of Soft Tissue Preservation in Human Mummies" was used. Results All checkpoints under category "A. Soft Tissues of Head and Musculoskeletal System" and more than half in category "B. Organs and Organ Systems" were observed. The scoring system accounted for a total score of 153 (out of 200). The comparison of the scores between the Iceman and three mummy collections from Vilnius, Lithuania, and Palermo, Sicily, as well as one Egyptian mummy resulted in overall higher soft tissue preservation scores for the Iceman. Conclusion Application of the checklist allowed for standardized assessment and documentation of the Iceman's soft tissue preservation status. The scoring system allowed for a quantitative comparison between the Iceman and other mummies. The Iceman showed remarkable soft tissue preservation. Key Points · The approach of structured reporting can be transferred to paleoradiology.. · The checklist allowed for standardized soft tissue assessment and documentation.. · The scoring system facilitated a quantitative comparison among mummies.. · Based on CT, the Tyrolean Iceman demonstrated remarkable soft tissue preservation.. Citation Format · Panzer S, Pernter P, Piombino-Mascali D et al. Checklist and Scoring System for the Assessment of Soft Tissue Preservation in CT Examinations of Human Mummies: Application to the Tyrolean Iceman. Fortschr Röntgenstr 2017; 189: 1152 - 1160. © Georg Thieme Verlag KG Stuttgart · New York.
Llanes, Antonio; Muñoz, Andrés; Bueno-Crespo, Andrés; García-Valverde, Teresa; Sánchez, Antonia; Arcas-Túnez, Francisco; Pérez-Sánchez, Horacio; Cecilia, José M
2016-01-01
The protein-folding problem has been extensively studied during the last fifty years. The understanding of the dynamics of global shape of a protein and the influence on its biological function can help us to discover new and more effective drugs to deal with diseases of pharmacological relevance. Different computational approaches have been developed by different researchers in order to foresee the threedimensional arrangement of atoms of proteins from their sequences. However, the computational complexity of this problem makes mandatory the search for new models, novel algorithmic strategies and hardware platforms that provide solutions in a reasonable time frame. We present in this revision work the past and last tendencies regarding protein folding simulations from both perspectives; hardware and software. Of particular interest to us are both the use of inexact solutions to this computationally hard problem as well as which hardware platforms have been used for running this kind of Soft Computing techniques.
3D printing of soft-matter to open a new era of soft-matter MEMS/robotics (Conference Presentation)
NASA Astrophysics Data System (ADS)
Furukawa, Hidemitsu
2017-04-01
3D printing technology is becoming useful and applicable by the progress of information and communication technology (ICT). It means 3D printer is a kind of useful robot for additive manufacturing and is controlled by computer with human-friendly software. Once user starts to use 3D printing of soft-matter, one can immediately understand computer-aided design (CAD) and engineering (CAE) technology will be more important and applicable for soft-matter systems. User can easily design soft-matter objects and 3D-print them. User can easily apply 3D-printed soft-matter objects to develop new research and application on MEMS and robotics. Here we introduce the recent progress of 3D printing (i.e. additive manufacturing), especially focusing on our 3D gel printing. We are trying to develop new advanced research and applications of 3D gel printer, including GEL-MECHANICS, GEL-PHOTONICS, and GEL-ROBOTICS. In the gel-mechanics, we are developing new gel materials for mechanical engineering. Some gels have high-mechanical strength and shape memory properties. In the gel-photonics. We are applying our original characterizing system, named `Scanning Microscopic Light Scattering (SMILS)', to analyze 3D printed gel materials. In the gel-robotics, we focus on 3D printing of soft parts for soft-robotics made form gel materials, like gel finger. Also we are challenging to apply 3D gel printing to start new company, to innovate new businesses in county side, and to create new 3D-printed foods.
Nadjmi, Nasser; Defrancq, Ellen; Mollemans, Wouter; Hemelen, Geert Van; Bergé, Stefaan
2014-01-01
The aim of this study was to evaluate the accuracy of 3D soft tissue predictions generated by a computer-aided maxillofacial planning system in patients undergoing orthognathic surgery. Twenty patients with dentofacial dysmorphosis were treated with orthognathic surgery after a preoperative orthodontic treatment. Fourteen patients had an Angle Class II malocclusion; three patients had an Angle class III malocclusion, and three patients had an Angle Class I malocclusion. Skeletal asymmetry was observed in six patient. The surgeries were planned using the Maxilim software. Computer assisted surgical planning was transferred to the patient by digitally generated splints. The validation procedures were performed in the following steps: (1) Standardized registration of the pre- and postoperative Cone Beam CT volumes; (2) Automated adjustment of the bone-related planning to the actual operative bony displacement; (3) Simulation of soft tissue changes; (4) Calculation of the soft tissue differences between the predicted and the postoperative results by distance mapping. Eighty four percent of the mapped distances between the predicted and actual postoperative results measured between -2 mm and +2 mm. The mean absolute linear measurements between the predicted and actual postoperative surface was 1.18. Our study shows the overall prediction was dependent on neither the surgical procedures nor the dentofacial deformity type. Despite some shortcomings in the prediction of the final position of the lower lip and cheek area, this software promises a clinically acceptable soft tissue prediction for orthognathic surgical procedures.
Whole-Body Human Inverse Dynamics with Distributed Micro-Accelerometers, Gyros and Force Sensing †
Latella, Claudia; Kuppuswamy, Naveen; Romano, Francesco; Traversaro, Silvio; Nori, Francesco
2016-01-01
Human motion tracking is a powerful tool used in a large range of applications that require human movement analysis. Although it is a well-established technique, its main limitation is the lack of estimation of real-time kinetics information such as forces and torques during the motion capture. In this paper, we present a novel approach for a human soft wearable force tracking for the simultaneous estimation of whole-body forces along with the motion. The early stage of our framework encompasses traditional passive marker based methods, inertial and contact force sensor modalities and harnesses a probabilistic computational technique for estimating dynamic quantities, originally proposed in the domain of humanoid robot control. We present experimental analysis on subjects performing a two degrees-of-freedom bowing task, and we estimate the motion and kinetics quantities. The results demonstrate the validity of the proposed method. We discuss the possible use of this technique in the design of a novel soft wearable force tracking device and its potential applications. PMID:27213394
Aurorasaurus Database of Real-Time, Soft-Sensor Sourced Aurora Data for Space Weather Research
NASA Astrophysics Data System (ADS)
Kosar, B.; MacDonald, E.; Heavner, M.
2017-12-01
Aurorasaurus is an innovative citizen science project focused on two fundamental objectives i.e., collecting real-time, ground-based signals of auroral visibility from citizen scientists (soft-sensors) and incorporating this new type of data into scientific investigations pertaining to aurora. The project has been live since the Fall of 2014, and as of Summer 2017, the database compiled approximately 12,000 observations (5295 direct reports and 6413 verified tweets). In this presentation, we will focus on demonstrating the utility of this robust science quality data for space weather research needs. These data scale with the size of the event and are well-suited to capture the largest, rarest events. Emerging state-of-the-art computational methods based on statistical inference such as machine learning frameworks and data-model integration methods can offer new insights that could potentially lead to better real-time assessment and space weather prediction when citizen science data are combined with traditional sources.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Johnson, Perry B.; Geyer, Amy; Borrego, David
Purpose: To investigate the benefits and limitations of patient-phantom matching for determining organ dose during fluoroscopy guided interventions. Methods: In this study, 27 CT datasets representing patients of different sizes and genders were contoured and converted into patient-specific computational models. Each model was matched, based on height and weight, to computational phantoms selected from the UF hybrid patient-dependent series. In order to investigate the influence of phantom type on patient organ dose, Monte Carlo methods were used to simulate two cardiac projections (PA/left lateral) and two abdominal projections (RAO/LPO). Organ dose conversion coefficients were then calculated for each patient-specific andmore » patient-dependent phantom and also for a reference stylized and reference hybrid phantom. The coefficients were subsequently analyzed for any correlation between patient-specificity and the accuracy of the dose estimate. Accuracy was quantified by calculating an absolute percent difference using the patient-specific dose conversion coefficients as the reference. Results: Patient-phantom matching was shown most beneficial for estimating the dose to heavy patients. In these cases, the improvement over using a reference stylized phantom ranged from approximately 50% to 120% for abdominal projections and for a reference hybrid phantom from 20% to 60% for all projections. For lighter individuals, patient-phantom matching was clearly superior to using a reference stylized phantom, but not significantly better than using a reference hybrid phantom for certain fields and projections. Conclusions: The results indicate two sources of error when patients are matched with phantoms: Anatomical error, which is inherent due to differences in organ size and location, and error attributed to differences in the total soft tissue attenuation. For small patients, differences in soft tissue attenuation are minimal and are exceeded by inherent anatomical differences. For large patients, difference in soft tissue attenuation can be large. In these cases, patient-phantom matching proves most effective as differences in soft tissue attenuation are mitigated. With increasing obesity rates, overweight patients will continue to make up a growing fraction of all patients undergoing medical imaging. Thus, having phantoms that better represent this population represents a considerable improvement over previous methods. In response to this study, additional phantoms representing heavier weight percentiles will be added to the UFHADM and UFHADF patient-dependent series.« less
Determining flexor-tendon repair techniques via soft computing
NASA Technical Reports Server (NTRS)
Johnson, M.; Firoozbakhsh, K.; Moniem, M.; Jamshidi, M.
2001-01-01
An SC-based multi-objective decision-making method for determining the optimal flexor-tendon repair technique from experimental and clinical survey data, and with variable circumstances, was presented. Results were compared with those from the Taguchi method. Using the Taguchi method results in the need to perform ad-hoc decisions when the outcomes for individual objectives are contradictory to a particular preference or circumstance, whereas the SC-based multi-objective technique provides a rigorous straightforward computational process in which changing preferences and importance of differing objectives are easily accommodated. Also, adding more objectives is straightforward and easily accomplished. The use of fuzzy-set representations of information categories provides insight into their performance throughout the range of their universe of discourse. The ability of the technique to provide a "best" medical decision given a particular physician, hospital, patient, situation, and other criteria was also demonstrated.
Spatiotemporal video deinterlacing using control grid interpolation
NASA Astrophysics Data System (ADS)
Venkatesan, Ragav; Zwart, Christine M.; Frakes, David H.; Li, Baoxin
2015-03-01
With the advent of progressive format display and broadcast technologies, video deinterlacing has become an important video-processing technique. Numerous approaches exist in the literature to accomplish deinterlacing. While most earlier methods were simple linear filtering-based approaches, the emergence of faster computing technologies and even dedicated video-processing hardware in display units has allowed higher quality but also more computationally intense deinterlacing algorithms to become practical. Most modern approaches analyze motion and content in video to select different deinterlacing methods for various spatiotemporal regions. We introduce a family of deinterlacers that employs spectral residue to choose between and weight control grid interpolation based spatial and temporal deinterlacing methods. The proposed approaches perform better than the prior state-of-the-art based on peak signal-to-noise ratio, other visual quality metrics, and simple perception-based subjective evaluations conducted by human viewers. We further study the advantages of using soft and hard decision thresholds on the visual performance.
Determining flexor-tendon repair techniques via soft computing.
Johnson, M; Firoozbakhsh, K; Moniem, M; Jamshidi, M
2001-01-01
An SC-based multi-objective decision-making method for determining the optimal flexor-tendon repair technique from experimental and clinical survey data, and with variable circumstances, was presented. Results were compared with those from the Taguchi method. Using the Taguchi method results in the need to perform ad-hoc decisions when the outcomes for individual objectives are contradictory to a particular preference or circumstance, whereas the SC-based multi-objective technique provides a rigorous straightforward computational process in which changing preferences and importance of differing objectives are easily accommodated. Also, adding more objectives is straightforward and easily accomplished. The use of fuzzy-set representations of information categories provides insight into their performance throughout the range of their universe of discourse. The ability of the technique to provide a "best" medical decision given a particular physician, hospital, patient, situation, and other criteria was also demonstrated.
Regionalization by fuzzy expert system based approach optimized by genetic algorithm
NASA Astrophysics Data System (ADS)
Chavoshi, Sattar; Azmin Sulaiman, Wan Nor; Saghafian, Bahram; Bin Sulaiman, Md. Nasir; Manaf, Latifah Abd
2013-04-01
SummaryIn recent years soft computing methods are being increasingly used to model complex hydrologic processes. These methods can simulate the real life processes without prior knowledge of the exact relationship between their components. The principal aim of this paper is perform hydrological regionalization based on soft computing concepts in the southern strip of the Caspian Sea basin, north of Iran. The basin with an area of 42,400 sq. km has been affected by severe floods in recent years that caused damages to human life and properties. Although some 61 hydrometric stations and 31 weather stations with 44 years of observed data (1961-2005) are operated in the study area, previous flood studies in this region have been hampered by insufficient and/or reliable observed rainfall-runoff records. In order to investigate the homogeneity (h) of catchments and overcome incompatibility that may occur on boundaries of cluster groups, a fuzzy expert system (FES) approach is used which incorporates physical and climatic characteristics, as well as flood seasonality and geographic location. Genetic algorithm (GA) was employed to adjust parameters of FES and optimize the system. In order to achieve the objective, a MATLAB programming code was developed which considers the heterogeneity criteria of less than 1 (H < 1) as the satisfying criteria. The adopted approach was found superior to the conventional hydrologic regionalization methods in the region because it employs greater number of homogeneity parameters and produces lower values of heterogeneity criteria.
Multi-GPU Jacobian accelerated computing for soft-field tomography.
Borsic, A; Attardo, E A; Halter, R J
2012-10-01
Image reconstruction in soft-field tomography is based on an inverse problem formulation, where a forward model is fitted to the data. In medical applications, where the anatomy presents complex shapes, it is common to use finite element models (FEMs) to represent the volume of interest and solve a partial differential equation that models the physics of the system. Over the last decade, there has been a shifting interest from 2D modeling to 3D modeling, as the underlying physics of most problems are 3D. Although the increased computational power of modern computers allows working with much larger FEM models, the computational time required to reconstruct 3D images on a fine 3D FEM model can be significant, on the order of hours. For example, in electrical impedance tomography (EIT) applications using a dense 3D FEM mesh with half a million elements, a single reconstruction iteration takes approximately 15-20 min with optimized routines running on a modern multi-core PC. It is desirable to accelerate image reconstruction to enable researchers to more easily and rapidly explore data and reconstruction parameters. Furthermore, providing high-speed reconstructions is essential for some promising clinical application of EIT. For 3D problems, 70% of the computing time is spent building the Jacobian matrix, and 25% of the time in forward solving. In this work, we focus on accelerating the Jacobian computation by using single and multiple GPUs. First, we discuss an optimized implementation on a modern multi-core PC architecture and show how computing time is bounded by the CPU-to-memory bandwidth; this factor limits the rate at which data can be fetched by the CPU. Gains associated with the use of multiple CPU cores are minimal, since data operands cannot be fetched fast enough to saturate the processing power of even a single CPU core. GPUs have much faster memory bandwidths compared to CPUs and better parallelism. We are able to obtain acceleration factors of 20 times on a single NVIDIA S1070 GPU, and of 50 times on four GPUs, bringing the Jacobian computing time for a fine 3D mesh from 12 min to 14 s. We regard this as an important step toward gaining interactive reconstruction times in 3D imaging, particularly when coupled in the future with acceleration of the forward problem. While we demonstrate results for EIT, these results apply to any soft-field imaging modality where the Jacobian matrix is computed with the adjoint method.
Multi-GPU Jacobian Accelerated Computing for Soft Field Tomography
Borsic, A.; Attardo, E. A.; Halter, R. J.
2012-01-01
Image reconstruction in soft-field tomography is based on an inverse problem formulation, where a forward model is fitted to the data. In medical applications, where the anatomy presents complex shapes, it is common to use Finite Element Models to represent the volume of interest and to solve a partial differential equation that models the physics of the system. Over the last decade, there has been a shifting interest from 2D modeling to 3D modeling, as the underlying physics of most problems are three-dimensional. Though the increased computational power of modern computers allows working with much larger FEM models, the computational time required to reconstruct 3D images on a fine 3D FEM model can be significant, on the order of hours. For example, in Electrical Impedance Tomography applications using a dense 3D FEM mesh with half a million elements, a single reconstruction iteration takes approximately 15 to 20 minutes with optimized routines running on a modern multi-core PC. It is desirable to accelerate image reconstruction to enable researchers to more easily and rapidly explore data and reconstruction parameters. Further, providing high-speed reconstructions are essential for some promising clinical application of EIT. For 3D problems 70% of the computing time is spent building the Jacobian matrix, and 25% of the time in forward solving. In the present work, we focus on accelerating the Jacobian computation by using single and multiple GPUs. First, we discuss an optimized implementation on a modern multi-core PC architecture and show how computing time is bounded by the CPU-to-memory bandwidth; this factor limits the rate at which data can be fetched by the CPU. Gains associated with use of multiple CPU cores are minimal, since data operands cannot be fetched fast enough to saturate the processing power of even a single CPU core. GPUs have a much faster memory bandwidths compared to CPUs and better parallelism. We are able to obtain acceleration factors of 20 times on a single NVIDIA S1070 GPU, and of 50 times on 4 GPUs, bringing the Jacobian computing time for a fine 3D mesh from 12 minutes to 14 seconds. We regard this as an important step towards gaining interactive reconstruction times in 3D imaging, particularly when coupled in the future with acceleration of the forward problem. While we demonstrate results for Electrical Impedance Tomography, these results apply to any soft-field imaging modality where the Jacobian matrix is computed with the Adjoint Method. PMID:23010857
Development of soft-sphere contact models for thermal heat conduction in granular flows
DOE Office of Scientific and Technical Information (OSTI.GOV)
Morris, A. B.; Pannala, S.; Ma, Z.
2016-06-08
Conductive heat transfer to flowing particles occurs when two particles (or a particle and wall) come into contact. The direct conduction between the two bodies depends on the collision dynamics, namely the size of the contact area and the duration of contact. For soft-sphere discrete-particle simulations, it is computationally expensive to resolve the true collision time because doing so would require a restrictively small numerical time step. To improve the computational speed, it is common to increase the 'softness' of the material to artificially increase the collision time, but doing so affects the heat transfer. In this work, two physically-basedmore » correction terms are derived to compensate for the increased contact area and time stemming from artificial particle softening. By including both correction terms, the impact that artificial softening has on the conductive heat transfer is removed, thus enabling simulations at greatly reduced computational times without sacrificing physical accuracy.« less
Dimensional Changes of Fresh Sockets With Reactive Soft Tissue Preservation: A Cone Beam CT Study.
Crespi, Roberto; Capparé, Paolo; Crespi, Giovanni; Gastaldi, Giorgio; Gherlone, Enrico Felice
2017-06-01
The aim of this study was to assess dimensional changes of the fresh sockets grafted with collagen sheets and maintenance of reactive soft tissue, using cone beam computed tomography (CBCT). Tooth extractions were performed with maximum preservation of the alveolar housing, reactive soft tissue was left into the sockets and collagen sheets filled bone defects. Cone beam computed tomography were performed before and 3 months after extractions. One hundred forty-five teeth, 60 monoradiculars and 85 molars, were extracted. In total, 269 alveoli were evaluated. In Group A, not statistically significant differences were found between monoradiculars, whereas statistically significant differences (P < 0.05) were found between molars, both for mesial and distal alveoli. In Group B, not statistically significant differences were found between maxillary and mandibular bone changes values (P > 0.05) for all types of teeth. This study reported an atraumatic tooth extraction, reactive soft tissue left in situ, and grafted collagen sponge may be helpful to reduce fresh socket collapse after extraction procedures.
Mithraratne, K; Ho, H; Hunter, P J; Fernandez, J W
2012-10-01
A coupled computational model of the foot consisting of a three-dimensional soft tissue continuum and a one-dimensional (1D) transient blood flow network is presented in this article. The primary aim of the model is to investigate the blood flow in major arteries of the pathologic foot where the soft tissue stiffening occurs. It has been reported in the literature that there could be up to about five-fold increase in the mechanical stiffness of the plantar soft tissues in pathologic (e.g. diabetic) feet compared with healthy ones. The increased stiffness results in higher tissue hydrostatic pressure within the plantar area of the foot when loaded. The hydrostatic pressure acts on the external surface of blood vessels and tend to reduce the flow cross-section area and hence the blood supply. The soft tissue continuum model of the foot was modelled as a tricubic Hermite finite element mesh representing all the muscles, skin and fat of the foot and treated as incompressible with transversely isotropic properties. The details of the mechanical model of soft tissue are presented in the companion paper, Part 1. The deformed state of the soft tissue continuum because of the applied ground reaction force at three foot positions (heel-strike, midstance and toe-off) was obtained by solving the Cauchy equations based on the theory of finite elasticity using the Galerkin finite element method. The geometry of the main arterial network in the foot was represented using a 1D Hermite cubic finite element mesh. The flow model consists of 1D Navier-Stokes equations and a nonlinear constitutive equation to describe vessel radius-transmural pressure relation. The latter was defined as the difference between the fluid and soft tissue hydrostatic pressure. Transient flow governing equations were numerically solved using the two-step Lax-Wendroff finite difference method. The geometry of both the soft tissue continuum and arterial network is anatomically-based and was developed using the data derived from visible human images and magnetic resonance images of a healthy male volunteer. Simulation results reveal that a two-fold increase in tissue stiffness leads to about 28% reduction in blood flow to the affected region. Copyright © 2012 John Wiley & Sons, Ltd.
Idris A, Elbakri; Fessler, Jeffrey A
2003-08-07
This paper describes a statistical image reconstruction method for x-ray CT that is based on a physical model that accounts for the polyenergetic x-ray source spectrum and the measurement nonlinearities caused by energy-dependent attenuation. Unlike our earlier work, the proposed algorithm does not require pre-segmentation of the object into the various tissue classes (e.g., bone and soft tissue) and allows mixed pixels. The attenuation coefficient of each voxel is modelled as the product of its unknown density and a weighted sum of energy-dependent mass attenuation coefficients. We formulate a penalized-likelihood function for this polyenergetic model and develop an iterative algorithm for estimating the unknown density of each voxel. Applying this method to simulated x-ray CT measurements of objects containing both bone and soft tissue yields images with significantly reduced beam hardening artefacts relative to conventional beam hardening correction methods. We also apply the method to real data acquired from a phantom containing various concentrations of potassium phosphate solution. The algorithm reconstructs an image with accurate density values for the different concentrations, demonstrating its potential for quantitative CT applications.
Experiment and application of soft x-ray grazing incidence optical scattering phenomena
NASA Astrophysics Data System (ADS)
Chen, Shuyan; Li, Cheng; Zhang, Yang; Su, Liping; Geng, Tao; Li, Kun
2017-08-01
For short wavelength imaging systems,surface scattering effects is one of important factors degrading imaging performance. Study of non-intuitive surface scatter effects resulting from practical optical fabrication tolerances is a necessary work for optical performance evaluation of high resolution short wavelength imaging systems. In this paper, Soft X-ray optical scattering distribution is measured by a soft X-ray reflectometer installed by my lab, for different sample mirrors、wavelength and grazing angle. Then aim at space solar telescope, combining these scattered light distributions, and surface scattering numerical model of grazing incidence imaging system, PSF and encircled energy of optical system of space solar telescope are computed. We can conclude that surface scattering severely degrade imaging performance of grazing incidence systems through analysis and computation.
Non Lipomatous Benign Lesions Mimicking Soft-tissue Sarcomas: A Pictorial Essay.
Coran, Alessandro; Orsatti, Giovanna; Crimì, Filippo; Rastrelli, Marco; DI Maggio, Antonio; Ponzoni, Alberto; Attar, Shady; Stramare, Roberto
2018-01-01
The incidental finding of soft tissue masses is a challenge for the radiologist. Benign and malignant lesions can be differentiated relying on patient history, symptoms and mostly with the help of imaging. Ultrasound (US), computed tomography (CT) and magnetic resonance imaging (MRI) become fundamental in order to distinguish these lesions but the radiologist needs to know the main characteristics of benign soft tissue masses and sarcomas. Herein, we present a pictorial review of lesions mimicking soft tissue sarcomas features. Copyright© 2018, International Institute of Anticancer Research (Dr. George J. Delinasios), All rights reserved.
Holographic diagnostics of biological microparticles
NASA Astrophysics Data System (ADS)
Dyomin, Victor V.; Sokolov, Vladimir V.
1996-05-01
Problem of studies of biological microojects is actual one for ecology, medicine, biology. Holographic techniques are useful to solve the problem. The above microojects are transparent or semitransparent ones in a visible light rather often. The case of an optically soft particle, (that is of a particle whose substance has the refractive index close to that of the surrounding medium) is quite probable in biological water suspensions. Some peculiarities of holographing optically soft microparticles are analyzed in this paper. We propose a technique to calculate a light intensity distribution in the plane of a hologram and in the plane of a holographic image of a particle of an arbitrary shape at an arbitrary distance from the latter plane. The efficiency of the approach proposed is demonstrated by calculational results obtained analytically for some simple cases. In a more complicated cases the technique can make a basis for numerical computations. The method of determining of refractive index of transparent and semitransparent microparticles is proposed. We also present in this paper some experimental results on holographic detection of the water drops and such optically soft particles as ovums of helmints in human jaundice.
Deformation of a soft helical filament in an axial flow at low Reynolds number.
Jawed, Mohammad K; Reis, Pedro M
2016-02-14
We perform a numerical investigation of the deformation of a rotating helical filament subjected to an axial flow, under low Reynolds number conditions, motivated by the propulsion of bacteria using helical flagella. Given its slenderness, the helical rod is intrinsically soft and deforms due to the interplay between elastic forces and hydrodynamic loading. We make use of a previously developed and experimentally validated computational tool framework that models the elasticity of the filament using the discrete elastic rod method and the fluid forces are treated using Lighthill's slender body theory. Under axial flow, and in the absence of rotation, the initially helical rod is extended. Above a critical flow speed its configuration comprises a straight portion connected to a localized helix near the free end. When the rod is also rotated about its helical axis, propulsion is only possible in a finite range of angular velocity, with an upper bound that is limited by buckling of the soft helix arising due to viscous stresses. A systematic exploration of the parameter space allows us to quantify regimes for successful propulsion for a number of specific bacteria.
Oldenburg, Amy L
2010-01-01
We present a new method for performing dynamic elastography of soft tissue samples. By sensing nanoscale displacements with optical coherence tomography, a chirped, modulated force is applied to acquire the mechanical spectrum of a tissue sample within a few seconds. This modulated force is applied via magnetic nanoparticles, named ‘nanotransducers’, which are diffused into the tissue, and which contribute negligible inertia to the soft tissue mechanical system. Using this novel system, we observed that excised tissues exhibit mechanical resonance modes which are well described by a linear damped harmonic oscillator. Results are validated by using cylindrical tissue phantoms of agarose in which resonant frequencies (30–400 Hz) are consistent with longitudinal modes and the sample boundary conditions. We furthermore show that the Young’s modulus can be computed from their measured resonance frequencies, analogous to resonant ultrasound spectroscopy for stiff material analysis. Using this new technique, named magnetomotive resonant acoustic spectroscopy (MRAS), we monitored the relative stiffening of an excised rat liver during a chemical fixation process. PMID:20124653
Improving finite element results in modeling heart valve mechanics.
Earl, Emily; Mohammadi, Hadi
2018-06-01
Finite element analysis is a well-established computational tool which can be used for the analysis of soft tissue mechanics. Due to the structural complexity of the leaflet tissue of the heart valve, the currently available finite element models do not adequately represent the leaflet tissue. A method of addressing this issue is to implement computationally expensive finite element models, characterized by precise constitutive models including high-order and high-density mesh techniques. In this study, we introduce a novel numerical technique that enhances the results obtained from coarse mesh finite element models to provide accuracy comparable to that of fine mesh finite element models while maintaining a relatively low computational cost. Introduced in this study is a method by which the computational expense required to solve linear and nonlinear constitutive models, commonly used in heart valve mechanics simulations, is reduced while continuing to account for large and infinitesimal deformations. This continuum model is developed based on the least square algorithm procedure coupled with the finite difference method adhering to the assumption that the components of the strain tensor are available at all nodes of the finite element mesh model. The suggested numerical technique is easy to implement, practically efficient, and requires less computational time compared to currently available commercial finite element packages such as ANSYS and/or ABAQUS.
Computer-Assisted Drug Formulation Design: Novel Approach in Drug Delivery.
Metwally, Abdelkader A; Hathout, Rania M
2015-08-03
We hypothesize that, by using several chemo/bio informatics tools and statistical computational methods, we can study and then predict the behavior of several drugs in model nanoparticulate lipid and polymeric systems. Accordingly, two different matrices comprising tripalmitin, a core component of solid lipid nanoparticles (SLN), and PLGA were first modeled using molecular dynamics simulation, and then the interaction of drugs with these systems was studied by means of computing the free energy of binding using the molecular docking technique. These binding energies were hence correlated with the loadings of these drugs in the nanoparticles obtained experimentally from the available literature. The obtained relations were verified experimentally in our laboratory using curcumin as a model drug. Artificial neural networks were then used to establish the effect of the drugs' molecular descriptors on the binding energies and hence on the drug loading. The results showed that the used soft computing methods can provide an accurate method for in silico prediction of drug loading in tripalmitin-based and PLGA nanoparticulate systems. These results have the prospective of being applied to other nano drug-carrier systems, and this integrated statistical and chemo/bio informatics approach offers a new toolbox to the formulation science by proposing what we present as computer-assisted drug formulation design (CADFD).
Marwah, Nikhil
2016-01-01
ABSTRACT Objective: The aim of our study is to use cone beam computed tomography (CBCT) to assess the dimensional changes in the nasopharyngeal soft-tissue characteristics in children of Indian origin with repaired cleft lip and palate (CLP) and to compare the results with patients with ideal occlusion. Materials and methods: A sample of 20 children (10 girls, 10 boys) with repaired CLP was selected. Cone beam computed tomography scans were taken to measure the nasopharyngeal airway changes in terms of linear measurements and sagittal cross-sectional areas. Error analysis was performed to prevent systematic or random errors. Independent means t-tests and Pearson correlation analysis were used to evaluate sex differences and the correlations among the variables. Results: Nasopharyngeal soft-tissue characteristics were different in the control and the study groups. Subjects with repaired CLP had lesser lower aerial width, lower adenoidal width and lower airway width. The upper airway width was also significantly lesser. The retropalatal and the total airway area were significantly greater in the control group. Conclusion: The narrow pharyngeal airway in patients with CLP might result in functional impairment of breathing in patients. Further investigations are necessary to clarify the relationship between pharyngeal structure and airway function in patients with CLP. How to cite this article: Agarwal A, Marwah N. Assessment of the Airway Characteristics in Children with Cleft Lip and Palate using Cone Beam Computed Tomography. Int J Clin Pediatr Dent 2016;9(1):5-9. PMID:27274147
Training Software in Artificial-Intelligence Computing Techniques
NASA Technical Reports Server (NTRS)
Howard, Ayanna; Rogstad, Eric; Chalfant, Eugene
2005-01-01
The Artificial Intelligence (AI) Toolkit is a computer program for training scientists, engineers, and university students in three soft-computing techniques (fuzzy logic, neural networks, and genetic algorithms) used in artificial-intelligence applications. The program promotes an easily understandable tutorial interface, including an interactive graphical component through which the user can gain hands-on experience in soft-computing techniques applied to realistic example problems. The tutorial provides step-by-step instructions on the workings of soft-computing technology, whereas the hands-on examples allow interaction and reinforcement of the techniques explained throughout the tutorial. In the fuzzy-logic example, a user can interact with a robot and an obstacle course to verify how fuzzy logic is used to command a rover traverse from an arbitrary start to the goal location. For the genetic algorithm example, the problem is to determine the minimum-length path for visiting a user-chosen set of planets in the solar system. For the neural-network example, the problem is to decide, on the basis of input data on physical characteristics, whether a person is a man, woman, or child. The AI Toolkit is compatible with the Windows 95,98, ME, NT 4.0, 2000, and XP operating systems. A computer having a processor speed of at least 300 MHz, and random-access memory of at least 56MB is recommended for optimal performance. The program can be run on a slower computer having less memory, but some functions may not be executed properly.
Differentiating between Women in Hard and Soft Science and Engineering Disciplines
ERIC Educational Resources Information Center
Camp, Amanda G.; Gilleland, Diane S.; Pearson, Carolyn; Vander Putten, James
2010-01-01
The intent of this study was to investigate characteristics that differentiate between women in soft (social, psychological, and life sciences) and hard (engineering, mathematics, computer science, physical science) science and engineering disciplines. Using the Beginning Postsecondary Students Longitudinal Study: 1996-2001 (2002), a descriptive…
Distributed data fusion across multiple hard and soft mobile sensor platforms
NASA Astrophysics Data System (ADS)
Sinsley, Gregory
One of the biggest challenges currently facing the robotics field is sensor data fusion. Unmanned robots carry many sophisticated sensors including visual and infrared cameras, radar, laser range finders, chemical sensors, accelerometers, gyros, and global positioning systems. By effectively fusing the data from these sensors, a robot would be able to form a coherent view of its world that could then be used to facilitate both autonomous and intelligent operation. Another distinct fusion problem is that of fusing data from teammates with data from onboard sensors. If an entire team of vehicles has the same worldview they will be able to cooperate much more effectively. Sharing worldviews is made even more difficult if the teammates have different sensor types. The final fusion challenge the robotics field faces is that of fusing data gathered by robots with data gathered by human teammates (soft sensors). Humans sense the world completely differently from robots, which makes this problem particularly difficult. The advantage of fusing data from humans is that it makes more information available to the entire team, thus helping each agent to make the best possible decisions. This thesis presents a system for fusing data from multiple unmanned aerial vehicles, unmanned ground vehicles, and human observers. The first issue this thesis addresses is that of centralized data fusion. This is a foundational data fusion issue, which has been very well studied. Important issues in centralized fusion include data association, classification, tracking, and robotics problems. Because these problems are so well studied, this thesis does not make any major contributions in this area, but does review it for completeness. The chapter on centralized fusion concludes with an example unmanned aerial vehicle surveillance problem that demonstrates many of the traditional fusion methods. The second problem this thesis addresses is that of distributed data fusion. Distributed data fusion is a younger field than centralized fusion. The main issues in distributed fusion that are addressed are distributed classification and distributed tracking. There are several well established methods for performing distributed fusion that are first reviewed. The chapter on distributed fusion concludes with a multiple unmanned vehicle collaborative test involving an unmanned aerial vehicle and an unmanned ground vehicle. The third issue this thesis addresses is that of soft sensor only data fusion. Soft-only fusion is a newer field than centralized or distributed hard sensor fusion. Because of the novelty of the field, the chapter on soft only fusion contains less background information and instead focuses on some new results in soft sensor data fusion. Specifically, it discusses a novel fuzzy logic based soft sensor data fusion method. This new method is tested using both simulations and field measurements. The biggest issue addressed in this thesis is that of combined hard and soft fusion. Fusion of hard and soft data is the newest area for research in the data fusion community; therefore, some of the largest theoretical contributions in this thesis are in the chapter on combined hard and soft fusion. This chapter presents a novel combined hard and soft data fusion method based on random set theory, which processes random set data using a particle filter. Furthermore, the particle filter is designed to be distributed across multiple robots and portable computers (used by human observers) so that there is no centralized failure point in the system. After laying out a theoretical groundwork for hard and soft sensor data fusion the thesis presents practical applications for hard and soft sensor data fusion in simulation. Through a series of three progressively more difficult simulations, some important hard and soft sensor data fusion capabilities are demonstrated. The first simulation demonstrates fusing data from a single soft sensor and a single hard sensor in order to track a car that could be driving normally or erratically. The second simulation adds the extra complication of classifying the type of target to the simulation. The third simulation uses multiple hard and soft sensors, with a limited field of view, to track a moving target and classify it as a friend, foe, or neutral. The final chapter builds on the work done in previous chapters by performing a field test of the algorithms for hard and soft sensor data fusion. The test utilizes an unmanned aerial vehicle, an unmanned ground vehicle, and a human observer with a laptop. The test is designed to mimic a collaborative human and robot search and rescue problem. This test makes some of the most important practical contributions of the thesis by showing that the algorithms that have been developed for hard and soft sensor data fusion are capable of running in real time on relatively simple hardware.
[INVITED] Computational intelligence for smart laser materials processing
NASA Astrophysics Data System (ADS)
Casalino, Giuseppe
2018-03-01
Computational intelligence (CI) involves using a computer algorithm to capture hidden knowledge from data and to use them for training ;intelligent machine; to make complex decisions without human intervention. As simulation is becoming more prevalent from design and planning to manufacturing and operations, laser material processing can also benefit from computer generating knowledge through soft computing. This work is a review of the state-of-the-art on the methodology and applications of CI in laser materials processing (LMP), which is nowadays receiving increasing interest from world class manufacturers and 4.0 industry. The focus is on the methods that have been proven effective and robust in solving several problems in welding, cutting, drilling, surface treating and additive manufacturing using the laser beam. After a basic description of the most common computational intelligences employed in manufacturing, four sections, namely, laser joining, machining, surface, and additive covered the most recent applications in the already extensive literature regarding the CI in LMP. Eventually, emerging trends and future challenges were identified and discussed.
Relationship between local structure and relaxation in out-of-equilibrium glassy systems
Schoenholz, Samuel S.; Cubuk, Ekin D.; Kaxiras, Efthimios; ...
2016-12-27
The dynamical glass transition is typically taken to be the temperature at which a glassy liquid is no longer able to equilibrate on experimental timescales. Consequently, the physical properties of these systems just above or below the dynamical glass transition, such as viscosity, can change by many orders of magnitude over long periods of time following external perturbation. During this progress toward equilibrium, glassy systems exhibit a history dependence that has complicated their study. In previous work, we bridged the gap between structure and dynamics in glassy liquids above their dynamical glass transition temperatures by introducing a scalar field calledmore » “softness,” a quantity obtained using machine-learning methods. Softness is designed to capture the hidden patterns in relative particle positions that correlate strongly with dynamical rearrangements of particle positions. Here we show that the out-of-equilibrium behavior of a model glass-forming system can be understood in terms of softness. We first demonstrate that the evolution of behavior following a temperature quench is a primarily structural phenomenon: The structure changes considerably, but the relationship between structure and dynamics remains invariant. We then show that the relaxation time can be robustly computed from structure as quantified by softness, with the same relation holding both in equilibrium and as the system ages. Together, these results show that the history dependence of the relaxation time in glasses requires knowledge only of the softness in addition to the usual state variables.« less
Relationship between local structure and relaxation in out-of-equilibrium glassy systems.
Schoenholz, Samuel S; Cubuk, Ekin D; Kaxiras, Efthimios; Liu, Andrea J
2017-01-10
The dynamical glass transition is typically taken to be the temperature at which a glassy liquid is no longer able to equilibrate on experimental timescales. Consequently, the physical properties of these systems just above or below the dynamical glass transition, such as viscosity, can change by many orders of magnitude over long periods of time following external perturbation. During this progress toward equilibrium, glassy systems exhibit a history dependence that has complicated their study. In previous work, we bridged the gap between structure and dynamics in glassy liquids above their dynamical glass transition temperatures by introducing a scalar field called "softness," a quantity obtained using machine-learning methods. Softness is designed to capture the hidden patterns in relative particle positions that correlate strongly with dynamical rearrangements of particle positions. Here we show that the out-of-equilibrium behavior of a model glass-forming system can be understood in terms of softness. To do this we first demonstrate that the evolution of behavior following a temperature quench is a primarily structural phenomenon: The structure changes considerably, but the relationship between structure and dynamics remains invariant. We then show that the relaxation time can be robustly computed from structure as quantified by softness, with the same relation holding both in equilibrium and as the system ages. Together, these results show that the history dependence of the relaxation time in glasses requires knowledge only of the softness in addition to the usual state variables.
Toward quantifying the composition of soft tissues by spectral CT with Medipix3.
Ronaldson, J Paul; Zainon, Rafidah; Scott, Nicola Jean Agnes; Gieseg, Steven Paul; Butler, Anthony P; Butler, Philip H; Anderson, Nigel G
2012-11-01
To determine the potential of spectral computed tomography (CT) with Medipix3 for quantifying fat, calcium, and iron in soft tissues within small animal models and surgical specimens of diseases such as fatty liver (metabolic syndrome) and unstable atherosclerosis. The spectroscopic method was applied to tomographic data acquired using a micro-CT system incorporating a Medipix3 detector array with silicon sensor layer and microfocus x-ray tube operating at 50 kVp. A 10 mm diameter perspex phantom containing a fat surrogate (sunflower oil) and aqueous solutions of ferric nitrate, calcium chloride, and iodine was imaged with multiple energy bins. The authors used the spectroscopic characteristics of the CT number to establish a basis for the decomposition of soft tissue components. The potential of the method of constrained least squares for quantifying different sets of materials was evaluated in terms of information entropy and degrees of freedom, with and without the use of a volume conservation constraint. The measurement performance was evaluated quantitatively using atheroma and mouse equivalent phantoms. Finally the decomposition method was assessed qualitatively using a euthanized mouse and an excised human atherosclerotic plaque. Spectral CT measurements of a phantom containing tissue surrogates confirmed the ability to distinguish these materials by the spectroscopic characteristics of their CT number. The assessment of performance potential in terms of information entropy and degrees of freedom indicated that certain sets of up to three materials could be decomposed by the method of constrained least squares. However, there was insufficient information within the data set to distinguish calcium from iron within soft tissues. The quantification of calcium concentration and fat mass fraction within atheroma and mouse equivalent phantoms by spectral CT correlated well with the nominal values (R(2) = 0.990 and R(2) = 0.985, respectively). In the euthanized mouse and excised human atherosclerotic plaque, regions of calcium and fat were appropriately decomposed according to their spectroscopic characteristics. Spectral CT, using the Medipix3 detector and silicon sensor layer, can quantify certain sets of up to three materials using the proposed method of constrained least squares. The system has some ability to independently distinguish calcium, fat, and water, and these have been quantified within phantom equivalents of fatty liver and atheroma. In this configuration, spectral CT cannot distinguish iron from calcium within soft tissues.
Computation of the soft anomalous dimension matrix in coordinate space
NASA Astrophysics Data System (ADS)
Mitov, Alexander; Sterman, George; Sung, Ilmo
2010-08-01
We complete the coordinate space calculation of the three-parton correlation in the two-loop massive soft anomalous dimension matrix. The full answer agrees with the result found previously by a different approach. The coordinate space treatment of renormalized two-loop gluon exchange diagrams exhibits their color symmetries in a transparent fashion. We compare coordinate space calculations of the soft anomalous dimension matrix with massive and massless eikonal lines and examine its nonuniform limit at absolute threshold.
Zhu, Dianwen; Li, Changqing
2014-12-01
Fluorescence molecular tomography (FMT) is a promising imaging modality and has been actively studied in the past two decades since it can locate the specific tumor position three-dimensionally in small animals. However, it remains a challenging task to obtain fast, robust and accurate reconstruction of fluorescent probe distribution in small animals due to the large computational burden, the noisy measurement and the ill-posed nature of the inverse problem. In this paper we propose a nonuniform preconditioning method in combination with L (1) regularization and ordered subsets technique (NUMOS) to take care of the different updating needs at different pixels, to enhance sparsity and suppress noise, and to further boost convergence of approximate solutions for fluorescence molecular tomography. Using both simulated data and phantom experiment, we found that the proposed nonuniform updating method outperforms its popular uniform counterpart by obtaining a more localized, less noisy, more accurate image. The computational cost was greatly reduced as well. The ordered subset (OS) technique provided additional 5 times and 3 times speed enhancements for simulation and phantom experiments, respectively, without degrading image qualities. When compared with the popular L (1) algorithms such as iterative soft-thresholding algorithm (ISTA) and Fast iterative soft-thresholding algorithm (FISTA) algorithms, NUMOS also outperforms them by obtaining a better image in much shorter period of time.
Soft Skills in Practice and in Education: An Evaluation
ERIC Educational Resources Information Center
Wahl, Harald; Kaufmann, Christian; Eckkrammer, Florian; Mense, Alexander; Gollner, Helmut; Himmler, Christian; Rogner, Wolf; Baierl, Thomas; Slobodian, Roman
2012-01-01
The paper measures the soft skills needs of companies and industry to technical oriented academic graduates, especially coming from IT course programs like business informatics, computer science, or information management. Therefore, between March and September 2010, two groups of researchers at the University of Applied Sciences (UAS) Technikum…
Schweppe, M; Geigel, J
2011-01-01
Industry has increasingly emphasized the need for "soft" or interpersonal skills development and team-building experience in the college curriculum. Here, we discuss our experiences with providing such opportunities via a collaborative project called the Virtual Theater. In this joint project between the Rochester Institute of Technology's School of Design and Department of Computer Science, the goal is to enable live performance in a virtual space with participants in different physical locales. Students work in teams, collaborating with other students in and out of their disciplines.
Binary weight distributions of some Reed-Solomon codes
NASA Technical Reports Server (NTRS)
Pollara, F.; Arnold, S.
1992-01-01
The binary weight distributions of the (7,5) and (15,9) Reed-Solomon (RS) codes and their duals are computed using the MacWilliams identities. Several mappings of symbols to bits are considered and those offering the largest binary minimum distance are found. These results are then used to compute bounds on the soft-decoding performance of these codes in the presence of additive Gaussian noise. These bounds are useful for finding large binary block codes with good performance and for verifying the performance obtained by specific soft-coding algorithms presently under development.
Assessment of traffic noise levels in urban areas using different soft computing techniques.
Tomić, J; Bogojević, N; Pljakić, M; Šumarac-Pavlović, D
2016-10-01
Available traffic noise prediction models are usually based on regression analysis of experimental data, and this paper presents the application of soft computing techniques in traffic noise prediction. Two mathematical models are proposed and their predictions are compared to data collected by traffic noise monitoring in urban areas, as well as to predictions of commonly used traffic noise models. The results show that application of evolutionary algorithms and neural networks may improve process of development, as well as accuracy of traffic noise prediction.
NASA Astrophysics Data System (ADS)
Frenkel, Daan
2007-03-01
During the past decade there has been a unique synergy between theory, experiment and simulation in Soft Matter Physics. In colloid science, computer simulations that started out as studies of highly simplified model systems, have acquired direct experimental relevance because experimental realizations of these simple models can now be synthesized. Whilst many numerical predictions concerning the phase behavior of colloidal systems have been vindicated by experiments, the jury is still out on others. In my talk I will discuss some of the recent technical developments, new findings and open questions in computational soft-matter science.
Detection of Failure in Asynchronous Motor Using Soft Computing Method
NASA Astrophysics Data System (ADS)
Vinoth Kumar, K.; Sony, Kevin; Achenkunju John, Alan; Kuriakose, Anto; John, Ano P.
2018-04-01
This paper investigates the stator short winding failure of asynchronous motor also their effects on motor current spectrums. A fuzzy logic approach i.e., model based technique possibly will help to detect the asynchronous motor failure. Actually, fuzzy logic similar to humanoid intelligent methods besides expected linguistic empowering inferences through vague statistics. The dynamic model is technologically advanced for asynchronous motor by means of fuzzy logic classifier towards investigate the stator inter turn failure in addition open phase failure. A hardware implementation was carried out with LabVIEW for the online-monitoring of faults.
Soft thermal contributions to 3-loop gauge coupling
NASA Astrophysics Data System (ADS)
Laine, M.; Schicho, P.; Schröder, Y.
2018-05-01
We analyze 3-loop contributions to the gauge coupling felt by ultrasoft ("magnetostatic") modes in hot Yang-Mills theory. So-called soft/hard terms, originating from dimension-six operators within the soft effective theory, are shown to cancel 1097/1098 of the IR divergence found in a recent determination of the hard 3-loop contribution to the soft gauge coupling. The remaining 1/1098 originates from ultrasoft/hard contributions, induced by dimension-six operators in the ultrasoft effective theory. Soft 3-loop contributions are likewise computed, and are found to be IR divergent, rendering the ultrasoft gauge coupling non-perturbative at relative order O({α}s^{3/2}) . We elaborate on the implications of these findings for effective theory studies of physical observables in thermal QCD.
A Hybrid Soft-computing Method for Image Analysis of Digital Plantar Scanners.
Razjouyan, Javad; Khayat, Omid; Siahi, Mehdi; Mansouri, Ali Alizadeh
2013-01-01
Digital foot scanners have been developed in recent years to yield anthropometrists digital image of insole with pressure distribution and anthropometric information. In this paper, a hybrid algorithm containing gray level spatial correlation (GLSC) histogram and Shanbag entropy is presented for analysis of scanned foot images. An evolutionary algorithm is also employed to find the optimum parameters of GLSC and transform function of the membership values. Resulting binary images as the thresholded images are undergone anthropometric measurements taking in to account the scale factor of pixel size to metric scale. The proposed method is finally applied to plantar images obtained through scanning feet of randomly selected subjects by a foot scanner system as our experimental setup described in the paper. Running computation time and the effects of GLSC parameters are investigated in the simulation results.
... test uses patches (also called electrodes) and a computer to check how the auditory nerve reacts to ... baby’s ear. The earphone is connected to a computer. Your baby’s provider sends a soft clicking sound ...
Panzer, Stephanie; Mc Coy, Mark R; Hitzl, Wolfgang; Piombino-Mascali, Dario; Jankauskas, Rimantas; Zink, Albert R; Augat, Peter
2015-01-01
The purpose of this study was to develop a checklist for standardized assessment of soft tissue preservation in human mummies based on whole-body computed tomography examinations, and to add a scoring system to facilitate quantitative comparison of mummies. Computed tomography examinations of 23 mummies from the Capuchin Catacombs of Palermo, Sicily (17 adults, 6 children; 17 anthropogenically and 6 naturally mummified) and 7 mummies from the crypt of the Dominican Church of the Holy Spirit of Vilnius, Lithuania (5 adults, 2 children; all naturally mummified) were used to develop the checklist following previously published guidelines. The scoring system was developed by assigning equal scores for checkpoints with equivalent quality. The checklist was evaluated by intra- and inter-observer reliability. The finalized checklist was applied to compare the groups of anthropogenically and naturally mummified bodies. The finalized checklist contains 97 checkpoints and was divided into two main categories, "A. Soft Tissues of Head and Musculoskeletal System" and "B. Organs and Organ Systems", each including various subcategories. The complete checklist had an intra-observer reliability of 98% and an inter-observer reliability of 93%. Statistical comparison revealed significantly higher values in anthropogenically compared to naturally mummified bodies for the total score and for three subcategories. In conclusion, the developed checklist allows for a standardized assessment and documentation of soft tissue preservation in whole-body computed tomography examinations of human mummies. The scoring system facilitates a quantitative comparison of the soft tissue preservation status between single mummies or mummy collections.
Huang, Hsuan-Ming; Hsiao, Ing-Tsung
2017-01-01
Over the past decade, image quality in low-dose computed tomography has been greatly improved by various compressive sensing- (CS-) based reconstruction methods. However, these methods have some disadvantages including high computational cost and slow convergence rate. Many different speed-up techniques for CS-based reconstruction algorithms have been developed. The purpose of this paper is to propose a fast reconstruction framework that combines a CS-based reconstruction algorithm with several speed-up techniques. First, total difference minimization (TDM) was implemented using the soft-threshold filtering (STF). Second, we combined TDM-STF with the ordered subsets transmission (OSTR) algorithm for accelerating the convergence. To further speed up the convergence of the proposed method, we applied the power factor and the fast iterative shrinkage thresholding algorithm to OSTR and TDM-STF, respectively. Results obtained from simulation and phantom studies showed that many speed-up techniques could be combined to greatly improve the convergence speed of a CS-based reconstruction algorithm. More importantly, the increased computation time (≤10%) was minor as compared to the acceleration provided by the proposed method. In this paper, we have presented a CS-based reconstruction framework that combines several acceleration techniques. Both simulation and phantom studies provide evidence that the proposed method has the potential to satisfy the requirement of fast image reconstruction in practical CT.
Wang, Shijun; McKenna, Matthew T; Nguyen, Tan B; Burns, Joseph E; Petrick, Nicholas; Sahiner, Berkman; Summers, Ronald M
2012-05-01
In this paper, we present development and testing results for a novel colonic polyp classification method for use as part of a computed tomographic colonography (CTC) computer-aided detection (CAD) system. Inspired by the interpretative methodology of radiologists using 3-D fly-through mode in CTC reading, we have developed an algorithm which utilizes sequences of images (referred to here as videos) for classification of CAD marks. For each CAD mark, we created a video composed of a series of intraluminal, volume-rendered images visualizing the detection from multiple viewpoints. We then framed the video classification question as a multiple-instance learning (MIL) problem. Since a positive (negative) bag may contain negative (positive) instances, which in our case depends on the viewing angles and camera distance to the target, we developed a novel MIL paradigm to accommodate this class of problems. We solved the new MIL problem by maximizing a L2-norm soft margin using semidefinite programming, which can optimize relevant parameters automatically. We tested our method by analyzing a CTC data set obtained from 50 patients from three medical centers. Our proposed method showed significantly better performance compared with several traditional MIL methods.
Wang, Shijun; McKenna, Matthew T.; Nguyen, Tan B.; Burns, Joseph E.; Petrick, Nicholas; Sahiner, Berkman
2012-01-01
In this paper we present development and testing results for a novel colonic polyp classification method for use as part of a computed tomographic colonography (CTC) computer-aided detection (CAD) system. Inspired by the interpretative methodology of radiologists using 3D fly-through mode in CTC reading, we have developed an algorithm which utilizes sequences of images (referred to here as videos) for classification of CAD marks. For each CAD mark, we created a video composed of a series of intraluminal, volume-rendered images visualizing the detection from multiple viewpoints. We then framed the video classification question as a multiple-instance learning (MIL) problem. Since a positive (negative) bag may contain negative (positive) instances, which in our case depends on the viewing angles and camera distance to the target, we developed a novel MIL paradigm to accommodate this class of problems. We solved the new MIL problem by maximizing a L2-norm soft margin using semidefinite programming, which can optimize relevant parameters automatically. We tested our method by analyzing a CTC data set obtained from 50 patients from three medical centers. Our proposed method showed significantly better performance compared with several traditional MIL methods. PMID:22552333
DE and NLP Based QPLS Algorithm
NASA Astrophysics Data System (ADS)
Yu, Xiaodong; Huang, Dexian; Wang, Xiong; Liu, Bo
As a novel evolutionary computing technique, Differential Evolution (DE) has been considered to be an effective optimization method for complex optimization problems, and achieved many successful applications in engineering. In this paper, a new algorithm of Quadratic Partial Least Squares (QPLS) based on Nonlinear Programming (NLP) is presented. And DE is used to solve the NLP so as to calculate the optimal input weights and the parameters of inner relationship. The simulation results based on the soft measurement of diesel oil solidifying point on a real crude distillation unit demonstrate that the superiority of the proposed algorithm to linear PLS and QPLS which is based on Sequential Quadratic Programming (SQP) in terms of fitting accuracy and computational costs.
Talking about Code: Integrating Pedagogical Code Reviews into Early Computing Courses
ERIC Educational Resources Information Center
Hundhausen, Christopher D.; Agrawal, Anukrati; Agarwal, Pawan
2013-01-01
Given the increasing importance of soft skills in the computing profession, there is good reason to provide students withmore opportunities to learn and practice those skills in undergraduate computing courses. Toward that end, we have developed an active learning approach for computing education called the "Pedagogical Code Review"…
NASA Astrophysics Data System (ADS)
Nebashi, Ryusuke; Sakimura, Noboru; Sugibayashi, Tadahiko
2017-08-01
We evaluated the soft-error tolerance and energy consumption of an embedded computer with magnetic random access memory (MRAM) using two computer simulators. One is a central processing unit (CPU) simulator of a typical embedded computer system. We simulated the radiation-induced single-event-upset (SEU) probability in a spin-transfer-torque MRAM cell and also the failure rate of a typical embedded computer due to its main memory SEU error. The other is a delay tolerant network (DTN) system simulator. It simulates the power dissipation of wireless sensor network nodes of the system using a revised CPU simulator and a network simulator. We demonstrated that the SEU effect on the embedded computer with 1 Gbit MRAM-based working memory is less than 1 failure in time (FIT). We also demonstrated that the energy consumption of the DTN sensor node with MRAM-based working memory can be reduced to 1/11. These results indicate that MRAM-based working memory enhances the disaster tolerance of embedded computers.
Survey: Computer Usage in Design Courses.
ERIC Educational Resources Information Center
Henley, Ernest J.
1983-01-01
Presents results of a survey of chemical engineering departments regarding computer usage in senior design courses. Results are categorized according to: computer usage (use of process simulators, student-written programs, faculty-written or "canned" programs; costs (hard and soft money); and available software. Programs offered are…
Toyota, Taro; Banno, Taisuke; Nitta, Sachiko; Takinoue, Masahiro; Nomoto, Tomonori; Natsume, Yuno; Matsumura, Shuichi; Fujinami, Masanori
2014-01-01
This review briefly summarizes recent developments in the construction of biologically/environmentally compatible chemical machinery composed of soft matter. Since environmental and living systems are open systems, chemical machinery must continuously fulfill its functions not only through the influx and generation of molecules but also via the degradation and dissipation of molecules. If the degradation or dissipation of soft matter molecular building blocks and biomaterial molecules/polymers can be achieved, soft matter particles composed of them can be used to realize chemical machinery such as selfpropelled droplets, drug delivery carriers, tissue regeneration scaffolds, protocell models, cell-/tissuemarkers, and molecular computing systems.
Gambon, D L; Brand, H S; Nieuw Amerongen, A V
2010-10-21
This case report describes a 9-year-old boy with severe tooth wear as a result of drinking a single glass of soft drink per day. This soft drink was consumed over a period of one to two hours, while he was gaming intensively on his computer. As a result, a deep bite, enamel cupping, sensitivity of primary teeth and loss of fillings occurred. Therefore, dentists should be aware that in patients who are gaming intensively, the erosive potential of soft drinks can be potentiated by mechanical forces leading to excessive tooth wear.
Spilker, R L; de Almeida, E S; Donzelli, P S
1992-01-01
This chapter addresses computationally demanding numerical formulations in the biomechanics of soft tissues. The theory of mixtures can be used to represent soft hydrated tissues in the human musculoskeletal system as a two-phase continuum consisting of an incompressible solid phase (collagen and proteoglycan) and an incompressible fluid phase (interstitial water). We first consider the finite deformation of soft hydrated tissues in which the solid phase is represented as hyperelastic. A finite element formulation of the governing nonlinear biphasic equations is presented based on a mixed-penalty approach and derived using the weighted residual method. Fluid and solid phase deformation, velocity, and pressure are interpolated within each element, and the pressure variables within each element are eliminated at the element level. A system of nonlinear, first-order differential equations in the fluid and solid phase deformation and velocity is obtained. In order to solve these equations, the contributions of the hyperelastic solid phase are incrementally linearized, a finite difference rule is introduced for temporal discretization, and an iterative scheme is adopted to achieve equilibrium at the end of each time increment. We demonstrate the accuracy and adequacy of the procedure using a six-node, isoparametric axisymmetric element, and we present an example problem for which independent numerical solution is available. Next, we present an automated, adaptive environment for the simulation of soft tissue continua in which the finite element analysis is coupled with automatic mesh generation, error indicators, and projection methods. Mesh generation and updating, including both refinement and coarsening, for the two-dimensional examples examined in this study are performed using the finite quadtree approach. The adaptive analysis is based on an error indicator which is the L2 norm of the difference between the finite element solution and a projected finite element solution. Total stress, calculated as the sum of the solid and fluid phase stresses, is used in the error indicator. To allow the finite difference algorithm to proceed in time using an updated mesh, solution values must be transferred to the new nodal locations. This rezoning is accomplished using a projected field for the primary variables. The accuracy and effectiveness of this adaptive finite element analysis is demonstrated using a linear, two-dimensional, axisymmetric problem corresponding to the indentation of a thin sheet of soft tissue. The method is shown to effectively capture the steep gradients and to produce solutions in good agreement with independent, converged, numerical solutions.
2016-01-01
Semiempirical (SE) methods can be derived from either Hartree–Fock or density functional theory by applying systematic approximations, leading to efficient computational schemes that are several orders of magnitude faster than ab initio calculations. Such numerical efficiency, in combination with modern computational facilities and linear scaling algorithms, allows application of SE methods to very large molecular systems with extensive conformational sampling. To reliably model the structure, dynamics, and reactivity of biological and other soft matter systems, however, good accuracy for the description of noncovalent interactions is required. In this review, we analyze popular SE approaches in terms of their ability to model noncovalent interactions, especially in the context of describing biomolecules, water solution, and organic materials. We discuss the most significant errors and proposed correction schemes, and we review their performance using standard test sets of molecular systems for quantum chemical methods and several recent applications. The general goal is to highlight both the value and limitations of SE methods and stimulate further developments that allow them to effectively complement ab initio methods in the analysis of complex molecular systems. PMID:27074247
Biomechanics of the soft-palate in sleep apnea patients with polycystic ovarian syndrome.
Subramaniam, Dhananjay Radhakrishnan; Arens, Raanan; Wagshul, Mark E; Sin, Sanghun; Wootton, David M; Gutmark, Ephraim J
2018-05-17
Highly compliant tissue supporting the pharynx and low muscle tone enhance the possibility of upper airway occlusion in children with obstructive sleep apnea (OSA). The present study describes subject-specific computational modeling of flow-induced velopharyngeal narrowing in a female child with polycystic ovarian syndrome (PCOS) with OSA and a non-OSA control. Anatomically accurate three-dimensional geometries of the upper airway and soft-palate were reconstructed for both subjects using magnetic resonance (MR) images. A fluid-structure interaction (FSI) shape registration analysis was performed using subject-specific values of flow rate to iteratively compute the biomechanical properties of the soft-palate. The optimized shear modulus for the control was 38 percent higher than the corresponding value for the OSA patient. The proposed computational FSI model was then employed for planning surgical treatment for the apneic subject. A virtual surgery comprising of a combined adenoidectomy, palatoplasty and genioglossus advancement was performed to estimate the resulting post-operative patterns of airflow and tissue displacement. Maximum flow velocity and velopharyngeal resistance decreased by 80 percent and 66 percent respectively following surgery. Post-operative flow-induced forces on the anterior and posterior faces of the soft-palate were equilibrated and the resulting magnitude of tissue displacement was 63 percent lower compared to the pre-operative case. Results from this pilot study indicate that FSI computational modeling can be employed to characterize the mechanical properties of pharyngeal tissue and evaluate the effectiveness of various upper airway surgeries prior to their application. Copyright © 2018. Published by Elsevier Ltd.
Zuhtuogullari, Kursat; Allahverdi, Novruz; Arikan, Nihat
2013-01-01
The systems consisting high input spaces require high processing times and memory usage. Most of the attribute selection algorithms have the problems of input dimensions limits and information storage problems. These problems are eliminated by means of developed feature reduction software using new modified selection mechanism with middle region solution candidates adding. The hybrid system software is constructed for reducing the input attributes of the systems with large number of input variables. The designed software also supports the roulette wheel selection mechanism. Linear order crossover is used as the recombination operator. In the genetic algorithm based soft computing methods, locking to the local solutions is also a problem which is eliminated by using developed software. Faster and effective results are obtained in the test procedures. Twelve input variables of the urological system have been reduced to the reducts (reduced input attributes) with seven, six, and five elements. It can be seen from the obtained results that the developed software with modified selection has the advantages in the fields of memory allocation, execution time, classification accuracy, sensitivity, and specificity values when compared with the other reduction algorithms by using the urological test data.
Zuhtuogullari, Kursat; Allahverdi, Novruz; Arikan, Nihat
2013-01-01
The systems consisting high input spaces require high processing times and memory usage. Most of the attribute selection algorithms have the problems of input dimensions limits and information storage problems. These problems are eliminated by means of developed feature reduction software using new modified selection mechanism with middle region solution candidates adding. The hybrid system software is constructed for reducing the input attributes of the systems with large number of input variables. The designed software also supports the roulette wheel selection mechanism. Linear order crossover is used as the recombination operator. In the genetic algorithm based soft computing methods, locking to the local solutions is also a problem which is eliminated by using developed software. Faster and effective results are obtained in the test procedures. Twelve input variables of the urological system have been reduced to the reducts (reduced input attributes) with seven, six, and five elements. It can be seen from the obtained results that the developed software with modified selection has the advantages in the fields of memory allocation, execution time, classification accuracy, sensitivity, and specificity values when compared with the other reduction algorithms by using the urological test data. PMID:23573172
Challenges in Soft Computing: Case Study with Louisville MSD CSO Modeling
NASA Astrophysics Data System (ADS)
Ormsbee, L.; Tufail, M.
2005-12-01
The principal constituents of soft computing include fuzzy logic, neural computing, evolutionary computation, machine learning, and probabilistic reasoning. There are numerous applications of these constituents (both individually and combination of two or more) in the area of water resources and environmental systems. These range from development of data driven models to optimal control strategies to assist in more informed and intelligent decision making process. Availability of data is critical to such applications and having scarce data may lead to models that do not represent the response function over the entire domain. At the same time, too much data has a tendency to lead to over-constraining of the problem. This paper will describe the application of a subset of these soft computing techniques (neural computing and genetic algorithms) to the Beargrass Creek watershed in Louisville, Kentucky. The application include development of inductive models as substitutes for more complex process-based models to predict water quality of key constituents (such as dissolved oxygen) and use them in an optimization framework for optimal load reductions. Such a process will facilitate the development of total maximum daily loads for the impaired water bodies in the watershed. Some of the challenges faced in this application include 1) uncertainty in data sets, 2) model application, and 3) development of cause-and-effect relationships between water quality constituents and watershed parameters through use of inductive models. The paper will discuss these challenges and how they affect the desired goals of the project.
Chatzistergos, Panagiotis E; Naemi, Roozbeh; Chockalingam, Nachiappan
2015-06-01
This study aims to develop a numerical method that can be used to investigate the cushioning properties of different insole materials on a subject-specific basis. Diabetic footwear and orthotic insoles play an important role for the reduction of plantar pressure in people with diabetes (type-2). Despite that, little information exists about their optimum cushioning properties. A new in-vivo measurement based computational procedure was developed which entails the generation of 2D subject-specific finite element models of the heel pad based on ultrasound indentation. These models are used to inverse engineer the material properties of the heel pad and simulate the contact between plantar soft tissue and a flat insole. After its validation this modelling procedure was utilised to investigate the importance of plantar soft tissue stiffness, thickness and loading for the correct selection of insole material. The results indicated that heel pad stiffness and thickness influence plantar pressure but not the optimum insole properties. On the other hand loading appears to significantly influence the optimum insole material properties. These results indicate that parameters that affect the loading of the plantar soft tissues such as body mass or a person's level of physical activity should be carefully considered during insole material selection. Copyright © 2015 IPEM. Published by Elsevier Ltd. All rights reserved.
Preventing Terror Attacks in the Homeland: A New Mission for State and Local Police
2005-09-01
18 Dale Couprie, Alan Goodbrand, Bin Li, and David Zhu, “ Soft Systems Methodology ,” Department of Computer Science (University of Calgary, 2002...Activities Authorization Act.” (50 USC. 403-1). June 2005. Couprie, Dale, Alan Goodbrand, Bin Li, and David Zhu. “ Soft Systems Methodology .” Department
1987-03-01
contends his soft systems methodology is such an approach. [Ref. 2: pp. 105-107] Overview of this Methodology is meant flor addressing fuzzy., ill...could form the basis of office systems development: Checkland’s (1981) soft systems methodology , Pava’s (1983) sociotechnical design, and Mumlbrd and
The State of Simulations: Soft-Skill Simulations Emerge as a Powerful New Form of E-Learning.
ERIC Educational Resources Information Center
Aldrich, Clark
2001-01-01
Presents responses of leaders from six simulation companies about challenges and opportunities of soft-skills simulations in e-learning. Discussion includes: evaluation metrics; role of subject matter experts in developing simulations; video versus computer graphics; technology needed to run simulations; technology breakthroughs; pricing;…
Heiland, Max; Pohlenz, Philipp; Blessmann, Marco; Habermann, Christian R; Oesterhelweg, Lars; Begemann, Philipp C; Schmidgunst, Christian; Blake, Felix A S; Püschel, Klaus; Schmelzle, Rainer; Schulze, Dirk
2007-12-01
The aim of this study was to evaluate soft tissue image quality of a mobile cone-beam computed tomography (CBCT) scanner with an integrated flat-panel detector. Eight fresh human cadavers were used in this study. For evaluation of soft tissue visualization, CBCT data sets and corresponding computed tomography (CT) and magnetic resonance imaging (MRI) data sets were acquired. Evaluation was performed with the help of 10 defined cervical anatomical structures. The statistical analysis of the scoring results of 3 examiners revealed the CBCT images to be of inferior quality regarding the visualization of most of the predefined structures. Visualization without a significant difference was found regarding the demarcation of the vertebral bodies and the pyramidal cartilages, the arteriosclerosis of the carotids (compared with CT), and the laryngeal skeleton (compared with MRI). Regarding arteriosclerosis of the carotids compared with MRI, CBCT proved to be superior. The integration of a flat-panel detector improves soft tissue visualization using a mobile CBCT scanner.
NASA Astrophysics Data System (ADS)
Ong, S. T.; Chaudhary, K.; Ali, J.; Lee, S.
2014-07-01
Numerical experiments using the Lee model were performed to study the neutron yield and soft x-ray emission from the IR-MPF-100 plasma focus using the current fitting technique. The mass sweeping factor and the current factor for the axial and radial phase were used to represent the imperfections encountered in experiments. All gross properties including the yields were realistically simulated once the computed and measured current profiles were well fitted. The computed neutron yield Yn was in agreement with the experimentally measured Yn at 20 kV (E0 ˜ 30 kJ) charging voltage. The optimum computed neutron yield of Yn = 1.238 × 109 neutrons per shot was obtained at optimum physics parameters of the plasma focus operated with deuterium gas. It was also observed that no soft x-rays were emitted from the IR-MPF-100 plasma focus operated with argon gas due to the absence of helium-like and hydrogen-like ions at a low plasma temperature (˜0.094 keV) and axial speed (8.12 cm µs-1). However, the soft x-ray yield can be achieved by increasing the charging voltage, using a higher ratio of outer anode radius to inner anode radius c or shorter anode length z0, or using neon as the operating gas.
Campbell, Graeme M; Sophocleous, Antonia
2014-01-01
Micro-computed tomography (micro-CT) is a high-resolution imaging modality that is capable of analysing bone structure with a voxel size on the order of 10 μm. With the development of in vivo micro-CT, where disease progression and treatment can be monitored in a living animal over a period of time, this modality has become a standard tool for preclinical assessment of bone architecture during disease progression and treatment. For meaningful comparison between micro-CT studies, it is essential that the same parameters for data acquisition and analysis methods be used. This protocol outlines the common procedures that are currently used for sample preparation, scanning, reconstruction and analysis in micro-CT studies. Scan and analysis methods for trabecular and cortical bone are covered for the femur, tibia, vertebra and the full neonate body of small rodents. The analysis procedures using the software provided by ScancoMedical and Bruker are discussed, and the routinely used bone architectural parameters are outlined. This protocol also provides a section dedicated to in vivo scanning and analysis, which covers the topics of anaesthesia, radiation dose and image registration. Because of the expanding research using micro-CT to study other skeletal sites, as well as soft tissues, we also provide a review of current techniques to examine the skull and mandible, adipose tissue, vasculature, tumour severity and cartilage. Lists of recommended further reading and literature references are included to provide the reader with more detail on the methods described. PMID:25184037
Gordaliza, P M; Muñoz-Barrutia, A; Via, L E; Sharpe, S; Desco, M; Vaquero, J J
2018-05-29
Computed tomography (CT) images enable capturing specific manifestations of tuberculosis (TB) that are undetectable using common diagnostic tests, which suffer from limited specificity. In this study, we aimed to automatically quantify the burden of Mycobacterium tuberculosis (Mtb) using biomarkers extracted from x-ray CT images. Nine macaques were aerosol-infected with Mtb and treated with various antibiotic cocktails. Chest CT scans were acquired in all animals at specific times independently of disease progression. First, a fully automatic segmentation of the healthy lungs from the acquired chest CT volumes was performed and air-like structures were extracted. Next, unsegmented pulmonary regions corresponding to damaged parenchymal tissue and TB lesions were included. CT biomarkers were extracted by classification of the probability distribution of the intensity of the segmented images into three tissue types: (1) Healthy tissue, parenchyma free from infection; (2) soft diseased tissue, and (3) hard diseased tissue. The probability distribution of tissue intensities was assumed to follow a Gaussian mixture model. The thresholds identifying each region were automatically computed using an expectation-maximization algorithm. The estimated longitudinal course of TB infection shows that subjects that have followed the same antibiotic treatment present a similar response (relative change in the diseased volume) with respect to baseline. More interestingly, the correlation between the diseased volume (soft tissue + hard tissue), which was manually delineated by an expert, and the automatically extracted volume with the proposed method was very strong (R 2 ≈ 0.8). We present a methodology that is suitable for automatic extraction of a radiological biomarker from CT images for TB disease burden. The method could be used to describe the longitudinal evolution of Mtb infection in a clinical trial devoted to the design of new drugs.
Bio-inspired computational heuristics to study Lane-Emden systems arising in astrophysics model.
Ahmad, Iftikhar; Raja, Muhammad Asif Zahoor; Bilal, Muhammad; Ashraf, Farooq
2016-01-01
This study reports novel hybrid computational methods for the solutions of nonlinear singular Lane-Emden type differential equation arising in astrophysics models by exploiting the strength of unsupervised neural network models and stochastic optimization techniques. In the scheme the neural network, sub-part of large field called soft computing, is exploited for modelling of the equation in an unsupervised manner. The proposed approximated solutions of higher order ordinary differential equation are calculated with the weights of neural networks trained with genetic algorithm, and pattern search hybrid with sequential quadratic programming for rapid local convergence. The results of proposed solvers for solving the nonlinear singular systems are in good agreements with the standard solutions. Accuracy and convergence the design schemes are demonstrated by the results of statistical performance measures based on the sufficient large number of independent runs.
Thermodynamic free energy methods to investigate shape transitions in bilayer membranes.
Ramakrishnan, N; Tourdot, Richard W; Radhakrishnan, Ravi
2016-06-01
The conformational free energy landscape of a system is a fundamental thermodynamic quantity of importance particularly in the study of soft matter and biological systems, in which the entropic contributions play a dominant role. While computational methods to delineate the free energy landscape are routinely used to analyze the relative stability of conformational states, to determine phase boundaries, and to compute ligand-receptor binding energies its use in problems involving the cell membrane is limited. Here, we present an overview of four different free energy methods to study morphological transitions in bilayer membranes, induced either by the action of curvature remodeling proteins or due to the application of external forces. Using a triangulated surface as a model for the cell membrane and using the framework of dynamical triangulation Monte Carlo, we have focused on the methods of Widom insertion, thermodynamic integration, Bennett acceptance scheme, and umbrella sampling and weighted histogram analysis. We have demonstrated how these methods can be employed in a variety of problems involving the cell membrane. Specifically, we have shown that the chemical potential, computed using Widom insertion, and the relative free energies, computed using thermodynamic integration and Bennett acceptance method, are excellent measures to study the transition from curvature sensing to curvature inducing behavior of membrane associated proteins. The umbrella sampling and WHAM analysis has been used to study the thermodynamics of tether formation in cell membranes and the quantitative predictions of the computational model are in excellent agreement with experimental measurements. Furthermore, we also present a method based on WHAM and thermodynamic integration to handle problems related to end-point-catastrophe that are common in most free energy methods.
Optical Assessment of Soft Contact Lens Edge-Thickness
Tankam, Patrice; Won, Jungeun; Canavesi, Cristina; Cox, Ian; Rolland, Jannick P.
2016-01-01
Purpose To assess the edge shape of soft contact lenses using Gabor-Domain Optical Coherence Microscopy (GD-OCM) with a 2 μm imaging resolution in three dimensions, and to generate edge-thickness profiles at different distances from the edge tip of soft contact lenses. Methods A high-speed custom-designed GD-OCM system was used to produce 3D images of the edge of an experimental soft contact lens (Bausch + Lomb, Rochester NY) in four different configurations: in air, submerged into water, submerged into saline with contrast agent, and placed onto the cornea of a porcine eyeball. An algorithm to compute the edge-thickness was developed and applied to cross-sectional images. The proposed algorithm includes the accurate detection of the interfaces between the lens and the environment, and the correction of the refraction error. Results The sharply defined edge tip of a soft contact lens was visualized in 3D. Results showed precise thickness measurement of the contact lens edge profile. 50 cross-sectional image frames for each configuration were used to test the robustness of the algorithm in evaluating the edge-thickness at any distance from the edge tip. The precision of the measurements was less than 0.2 μm. Conclusions The results confirmed the ability of GD-OCM to provide high definition images of soft contact lens edges. As a non-destructive, precise, and fast metrology tool for soft contact lens measurement, the integration of GD-OCM in the design and manufacturing of contact lenses will be beneficial for further improvement in edge design and quality control. In the clinical perspective, the in-vivo evaluation of the lens fitted onto the cornea will advance our understanding of how the edge interacts with the ocular surface. The latter will provide insights into the impact of long-term use of contact lenses on the visual performance. PMID:27232902
Slimani, N; Ferrari, P; Ocké, M; Welch, A; Boeing, H; Liere, M; Pala, V; Amiano, P; Lagiou, A; Mattisson, I; Stripp, C; Engeset, D; Charrondière, R; Buzzard, M; Staveren, W; Riboli, E
2000-12-01
Despite increasing interest in the concept of calibration in dietary surveys, there is still little experience in the use and standardization of a common reference dietary method, especially in international studies. In this paper, we present the general theoretical framework and the approaches developed to standardize the computer-assisted 24 h diet recall method (EPIC-SOFT) used to collect about 37 000 24-h dietary recall measurements (24-HDR) from the 10 countries participating in the European Prospective Investigation into Cancer and Nutrition (EPIC). In addition, an analysis of variance was performed to examine the level of standardization of EPIC-SOFT across the 90 interviewers involved in the study. The analysis of variance used a random effects model in which mean energy intake per interviewer was used as the dependent variable, while age, body mass index (BMI), energy requirement, week day, season, special diet, special day, physical activity and the EPIC-SOFT version were used as independent variables. The analysis was performed separately for men and women. The results show no statistical difference between interviewers in all countries for men and five out of eight countries for women, after adjustment for physical activity and the EPIC-SOFT program version used, and the exclusion of one interviewer in Germany (for men), and one in Denmark (for women). These results showed an interviewer effect in certain countries and a significant difference between gender, suggesting an underlying respondent's effect due to the higher under-reporting among women that was consistently observed in EPIC. However, the actual difference between interviewer and country mean energy intakes is about 10%. Furthermore, no statistical differences in mean energy intakes were observed across centres from the same country, except in Italy and Germany for men, and France and Spain for women, where the populations were recruited from areas scattered throughout the countries. Despite these encouraging results and the efforts to standardize the 24-HDR interview method, conscious or unconscious behaviour of respondents and/or interviewer bias cannot be prevented entirely. Further evaluation of the reliability of EPIC-SOFT measurements will be conducted through validation against independent biological markers (nitrogen, potassium).
Soft tissue modelling with conical springs.
Omar, Nadzeri; Zhong, Yongmin; Jazar, Reza N; Subic, Aleksandar; Smith, Julian; Shirinzadeh, Bijan
2015-01-01
This paper presents a new method for real-time modelling soft tissue deformation. It improves the traditional mass-spring model with conical springs to deal with nonlinear mechanical behaviours of soft tissues. A conical spring model is developed to predict soft tissue deformation with reference to deformation patterns. The model parameters are formulated according to tissue deformation patterns and the nonlinear behaviours of soft tissues are modelled with the stiffness variation of conical spring. Experimental results show that the proposed method can describe different tissue deformation patterns using one single equation and also exhibit the typical mechanical behaviours of soft tissues.
Gas-liquid coexistence in a system of dipolar soft spheres.
Jia, Ran; Braun, Heiko; Hentschke, Reinhard
2010-12-01
The existence of gas-liquid coexistence in dipolar fluids with no other contribution to attractive interaction than dipole-dipole interaction is a basic and open question in the theory of fluids. Here we compute the gas-liquid critical point in a system of dipolar soft spheres subject to an external electric field using molecular dynamics computer simulation. Tracking the critical point as the field strength is approaching zero we find the following limiting values: T(c)=0.063 and ρ(c)=0.0033 (dipole moment μ=1). These values are confirmed by independent simulation at zero field strength.
NASA Technical Reports Server (NTRS)
1990-01-01
Magnetic Resonance Imaging (MRI) and Computer-aided Tomography (CT) images are often complementary. In most cases, MRI is good for viewing soft tissue but not bone, while CT images are good for bone but not always good for soft tissue discrimination. Physicians and engineers in the Department of Radiology at the University of Michigan Hospitals are developing a technique for combining the best features of MRI and CT scans to increase the accuracy of discriminating one type of body tissue from another. One of their research tools is a computer program called HICAP. The program can be used to distinguish between healthy and diseased tissue in body images.
Fracture characterization of inhomogeneous wrinkled metallic films deposited on soft substrates
NASA Astrophysics Data System (ADS)
Kishida, Hiroshi; Ishizaka, Satoshi; Nagakura, Takumi; Suzuki, Hiroaki; Yonezu, Akio
2017-12-01
This study investigated the fracture properties of wrinkled metallic films on a polydimethylsiloxane (PDMS) soft substrate. In particular, the crack density of the wrinkled film during tensile deformation was examined. In order to achieve better deformability of metallic thin films, a method to fabricate a wrinkled thin film on a PDMS soft substrate was first established. The copper (Cu) nano-film fabricated in this study possessed a wrinkled geometry, which plays a critical role in determining the extent of large elastic deformation. To create the wrinkled structure, wet-etching with a polymeric sacrificial layer was used. A sacrificial layer was first deposited onto a silicone rubber sheet. During the curing process of the layer, a compressive strain was applied such that the hardened surface layer buckled, and a wrinkled form was obtained. Subsequently, a PDMS solution was used to cover the layer in order to form a wrinkled PDMS substrate. Finally, the Cu film was deposited onto the wrinkled PDMS, such that the wrinkled Cu film on a soft PDMS substrate was fabricated. The use of uni-axial tensile tests resulted in film crack generation at the stress concentration zone in the wrinkled structure of the films. When the tensile loading was increased, the number of cracks increased. It was found that the increase in crack density was strongly related to the inhomogeneous nature of the wrinkled structure. Such a trend in crack density was investigated using FEM (finite element method) computations, such that this study established a simple mechanical model that may be used to predict the increase in crack density during tensile deformation. This model was verified through several experiments using various wrinkle patterns. The proposed mechanical model may be useful to predict the crack density of a wrinkled metallic film subject to tensile loading.
Annual Rainfall Forecasting by Using Mamdani Fuzzy Inference System
NASA Astrophysics Data System (ADS)
Fallah-Ghalhary, G.-A.; Habibi Nokhandan, M.; Mousavi Baygi, M.
2009-04-01
Long-term rainfall prediction is very important to countries thriving on agro-based economy. In general, climate and rainfall are highly non-linear phenomena in nature giving rise to what is known as "butterfly effect". The parameters that are required to predict the rainfall are enormous even for a short period. Soft computing is an innovative approach to construct computationally intelligent systems that are supposed to possess humanlike expertise within a specific domain, adapt themselves and learn to do better in changing environments, and explain how they make decisions. Unlike conventional artificial intelligence techniques the guiding principle of soft computing is to exploit tolerance for imprecision, uncertainty, robustness, partial truth to achieve tractability, and better rapport with reality. In this paper, 33 years of rainfall data analyzed in khorasan state, the northeastern part of Iran situated at latitude-longitude pairs (31°-38°N, 74°- 80°E). this research attempted to train Fuzzy Inference System (FIS) based prediction models with 33 years of rainfall data. For performance evaluation, the model predicted outputs were compared with the actual rainfall data. Simulation results reveal that soft computing techniques are promising and efficient. The test results using by FIS model showed that the RMSE was obtained 52 millimeter.
Soft-tissue and phase-contrast imaging at the Swiss Light Source
NASA Astrophysics Data System (ADS)
Schneider, Philipp; Mohan, Nishant; Stampanoni, Marco; Muller, Ralph
2004-05-01
Recent results show that bone vasculature is a major contributor to local tissue porosity, and therefore can be directly linked to the mechanical properties of bone tissue. With the advent of third generation synchrotron radiation (SR) sources, micro-computed tomography (μCT) with resolutions in the order of 1 μm and better has become feasible. This technique has been employed frequently to analyze trabecular architecture and local bone tissue properties, i.e. the hard or mineralized bone tissue. Nevertheless, less is known about the soft tissues in bone, mainly due to inadequate imaging capabilities. Here, we discuss three different methods and applications to visualize soft tissues. The first approach is referred to as negative imaging. In this case the material around the soft tissue provides the absorption contrast necessary for X-ray based tomography. Bone vasculature from two different mouse strains was investigated and compared qualitatively. Differences were observed in terms of local vessel number and vessel orientation. The second technique represents corrosion casting, which is principally adapted for imaging of vascular systems. The technique of corrosion casting has already been applied successfully at the Swiss Light Source. Using the technology we were able to show that pathological features reminiscent of Alzheimer"s disease could be distinguished in the brain vasculature of APP transgenic mice. The third technique discussed here is phase contrast imaging exploiting the high degree of coherence of third generation synchrotron light sources, which provide the necessary physical conditions for phase contrast. The in-line approach followed here for phase contrast retrieval is a modification of the Gerchberg-Saxton-Fienup type. Several measurements and theoretical thoughts concerning phase contrast imaging are presented, including mathematical phase retrieval. Although up-to-now only phase images have been computed, the approach is now ready to retrieve the phase for a large number of angular positions of the specimen allowing application of holotomography, which is the three-dimensional reconstruction of phase images.
WE-EF-303-10: Single- Detector Proton Radiography as a Portal Imaging Equivalent for Proton Therapy
DOE Office of Scientific and Technical Information (OSTI.GOV)
Doolan, P; Bentefour, E; Testa, M
2015-06-15
Purpose: In proton therapy, patient alignment is of critical importance due to the sensitivity of the proton range to tissue heterogeneities. Traditionally proton radiography is used for verification of the water-equivalent path length (WEPL), which dictates the depth protons reach. In this work we propose its use for alignment. Additionally, many new proton centers have cone-beam computed tomography in place of beamline X-ray imaging and so proton radiography offers a unique patient alignment verification similar to portal imaging in photon therapy. Method: Proton radiographs of a CIRS head phantom were acquired using the Beam Imaging System (BIS) (IBA, Louvain-la-Neuve) inmore » a horizontal beamline. A scattered beam was produced using a small, dedicated, range modulator (RM) wheel fabricated out of aluminum. The RM wheel was rotated slowly (20 sec/rev) using a stepper motor to compensate for the frame rate of the BIS (120 ms). Dose rate functions (DRFs) over two RM wheel rotations were acquired. Calibration was made with known thicknesses of homogeneous solid water. For each pixel the time width, skewness and kurtosis of the DRFs were computed. The time width was used to compute the object WEPL. In the heterogeneous phantom, the excess skewness and excess kurtosis (i.e. difference from homogeneous cases) were computed and assessed for suitability for patient set up. Results: The technique allowed for the simultaneous production of images that can be used for WEPL verification, showing few internal details, and excess skewness and kurtosis images that can be used for soft tissue alignment. These latter images highlight areas where range mixing has occurred, correlating with phantom heterogeneities. Conclusion: The excess skewness and kurtosis images contain details that are not visible in the WET images. These images, unique to the time-resolved proton radiographic method, could be used for patient set up according to soft tissues.« less
Lee, Vinson R.; Blew, Rob M.; Farr, Josh N.; Tomas, Rita; Lohman, Timothy G.; Going, Scott B.
2013-01-01
Objective Assess the utility of peripheral quantitative computed tomography (pQCT) for estimating whole body fat in adolescent girls. Research Methods and Procedures Our sample included 458 girls (aged 10.7 ± 1.1y, mean BMI = 18.5 ± 3.3 kg/m2) who had DXA scans for whole body percent fat (DXA %Fat). Soft tissue analysis of pQCT scans provided thigh and calf subcutaneous percent fat and thigh and calf muscle density (muscle fat content surrogates). Anthropometric variables included weight, height and BMI. Indices of maturity included age and maturity offset. The total sample was split into validation (VS; n = 304) and cross-validation (CS; n = 154) samples. Linear regression was used to develop prediction equations for estimating DXA %Fat from anthropometric variables and pQCT-derived soft tissue components in VS and the best prediction equation was applied to CS. Results Thigh and calf SFA %Fat were positively correlated with DXA %Fat (r = 0.84 to 0.85; p <0.001) and thigh and calf muscle densities were inversely related to DXA %Fat (r = −0.30 to −0.44; p < 0.001). The best equation for estimating %Fat included thigh and calf SFA %Fat and thigh and calf muscle density (adj. R2 = 0.90; SEE = 2.7%). Bland-Altman analysis in CS showed accurate estimates of percent fat (adj. R2 = 0.89; SEE = 2.7%) with no bias. Discussion Peripheral QCT derived indices of adiposity can be used to accurately estimate whole body percent fat in adolescent girls. PMID:25147482
NASA Astrophysics Data System (ADS)
Pattabhiraman, Harini; Gantapara, Anjan P.; Dijkstra, Marjolein
2015-10-01
Using computer simulations, we study the phase behavior of a model system of colloidal hard disks with a diameter σ and a soft corona of width 1.4σ. The particles interact with a hard core and a repulsive square-shoulder potential. We calculate the free energy of the random-tiling quasicrystal and its crystalline approximants using the Frenkel-Ladd method. We explicitly account for the configurational entropy associated with the number of distinct configurations of the random-tiling quasicrystal. We map out the phase diagram and find that the random tiling dodecagonal quasicrystal is stabilised by entropy at finite temperatures with respect to the crystalline approximants that we considered, and its stability region seems to extend to zero temperature as the energies of the defect-free quasicrystal and the crystalline approximants are equal within our statistical accuracy.
Recent advances in computational mechanics of the human knee joint.
Kazemi, M; Dabiri, Y; Li, L P
2013-01-01
Computational mechanics has been advanced in every area of orthopedic biomechanics. The objective of this paper is to provide a general review of the computational models used in the analysis of the mechanical function of the knee joint in different loading and pathological conditions. Major review articles published in related areas are summarized first. The constitutive models for soft tissues of the knee are briefly discussed to facilitate understanding the joint modeling. A detailed review of the tibiofemoral joint models is presented thereafter. The geometry reconstruction procedures as well as some critical issues in finite element modeling are also discussed. Computational modeling can be a reliable and effective method for the study of mechanical behavior of the knee joint, if the model is constructed correctly. Single-phase material models have been used to predict the instantaneous load response for the healthy knees and repaired joints, such as total and partial meniscectomies, ACL and PCL reconstructions, and joint replacements. Recently, poromechanical models accounting for fluid pressurization in soft tissues have been proposed to study the viscoelastic response of the healthy and impaired knee joints. While the constitutive modeling has been considerably advanced at the tissue level, many challenges still exist in applying a good material model to three-dimensional joint simulations. A complete model validation at the joint level seems impossible presently, because only simple data can be obtained experimentally. Therefore, model validation may be concentrated on the constitutive laws using multiple mechanical tests of the tissues. Extensive model verifications at the joint level are still crucial for the accuracy of the modeling.
Recent Advances in Computational Mechanics of the Human Knee Joint
Kazemi, M.; Dabiri, Y.; Li, L. P.
2013-01-01
Computational mechanics has been advanced in every area of orthopedic biomechanics. The objective of this paper is to provide a general review of the computational models used in the analysis of the mechanical function of the knee joint in different loading and pathological conditions. Major review articles published in related areas are summarized first. The constitutive models for soft tissues of the knee are briefly discussed to facilitate understanding the joint modeling. A detailed review of the tibiofemoral joint models is presented thereafter. The geometry reconstruction procedures as well as some critical issues in finite element modeling are also discussed. Computational modeling can be a reliable and effective method for the study of mechanical behavior of the knee joint, if the model is constructed correctly. Single-phase material models have been used to predict the instantaneous load response for the healthy knees and repaired joints, such as total and partial meniscectomies, ACL and PCL reconstructions, and joint replacements. Recently, poromechanical models accounting for fluid pressurization in soft tissues have been proposed to study the viscoelastic response of the healthy and impaired knee joints. While the constitutive modeling has been considerably advanced at the tissue level, many challenges still exist in applying a good material model to three-dimensional joint simulations. A complete model validation at the joint level seems impossible presently, because only simple data can be obtained experimentally. Therefore, model validation may be concentrated on the constitutive laws using multiple mechanical tests of the tissues. Extensive model verifications at the joint level are still crucial for the accuracy of the modeling. PMID:23509602
Random Walk Graph Laplacian-Based Smoothness Prior for Soft Decoding of JPEG Images.
Liu, Xianming; Cheung, Gene; Wu, Xiaolin; Zhao, Debin
2017-02-01
Given the prevalence of joint photographic experts group (JPEG) compressed images, optimizing image reconstruction from the compressed format remains an important problem. Instead of simply reconstructing a pixel block from the centers of indexed discrete cosine transform (DCT) coefficient quantization bins (hard decoding), soft decoding reconstructs a block by selecting appropriate coefficient values within the indexed bins with the help of signal priors. The challenge thus lies in how to define suitable priors and apply them effectively. In this paper, we combine three image priors-Laplacian prior for DCT coefficients, sparsity prior, and graph-signal smoothness prior for image patches-to construct an efficient JPEG soft decoding algorithm. Specifically, we first use the Laplacian prior to compute a minimum mean square error initial solution for each code block. Next, we show that while the sparsity prior can reduce block artifacts, limiting the size of the overcomplete dictionary (to lower computation) would lead to poor recovery of high DCT frequencies. To alleviate this problem, we design a new graph-signal smoothness prior (desired signal has mainly low graph frequencies) based on the left eigenvectors of the random walk graph Laplacian matrix (LERaG). Compared with the previous graph-signal smoothness priors, LERaG has desirable image filtering properties with low computation overhead. We demonstrate how LERaG can facilitate recovery of high DCT frequencies of a piecewise smooth signal via an interpretation of low graph frequency components as relaxed solutions to normalized cut in spectral clustering. Finally, we construct a soft decoding algorithm using the three signal priors with appropriate prior weights. Experimental results show that our proposal outperforms the state-of-the-art soft decoding algorithms in both objective and subjective evaluations noticeably.
Genetic networks and soft computing.
Mitra, Sushmita; Das, Ranajit; Hayashi, Yoichi
2011-01-01
The analysis of gene regulatory networks provides enormous information on various fundamental cellular processes involving growth, development, hormone secretion, and cellular communication. Their extraction from available gene expression profiles is a challenging problem. Such reverse engineering of genetic networks offers insight into cellular activity toward prediction of adverse effects of new drugs or possible identification of new drug targets. Tasks such as classification, clustering, and feature selection enable efficient mining of knowledge about gene interactions in the form of networks. It is known that biological data is prone to different kinds of noise and ambiguity. Soft computing tools, such as fuzzy sets, evolutionary strategies, and neurocomputing, have been found to be helpful in providing low-cost, acceptable solutions in the presence of various types of uncertainties. In this paper, we survey the role of these soft methodologies and their hybridizations, for the purpose of generating genetic networks.
Soft Electronics Enabled Ergonomic Human-Computer Interaction for Swallowing Training
Lee, Yongkuk; Nicholls, Benjamin; Sup Lee, Dong; Chen, Yanfei; Chun, Youngjae; Siang Ang, Chee; Yeo, Woon-Hong
2017-01-01
We introduce a skin-friendly electronic system that enables human-computer interaction (HCI) for swallowing training in dysphagia rehabilitation. For an ergonomic HCI, we utilize a soft, highly compliant (“skin-like”) electrode, which addresses critical issues of an existing rigid and planar electrode combined with a problematic conductive electrolyte and adhesive pad. The skin-like electrode offers a highly conformal, user-comfortable interaction with the skin for long-term wearable, high-fidelity recording of swallowing electromyograms on the chin. Mechanics modeling and experimental quantification captures the ultra-elastic mechanical characteristics of an open mesh microstructured sensor, conjugated with an elastomeric membrane. Systematic in vivo studies investigate the functionality of the soft electronics for HCI-enabled swallowing training, which includes the application of a biofeedback system to detect swallowing behavior. The collection of results demonstrates clinical feasibility of the ergonomic electronics in HCI-driven rehabilitation for patients with swallowing disorders. PMID:28429757
Soft Electronics Enabled Ergonomic Human-Computer Interaction for Swallowing Training
NASA Astrophysics Data System (ADS)
Lee, Yongkuk; Nicholls, Benjamin; Sup Lee, Dong; Chen, Yanfei; Chun, Youngjae; Siang Ang, Chee; Yeo, Woon-Hong
2017-04-01
We introduce a skin-friendly electronic system that enables human-computer interaction (HCI) for swallowing training in dysphagia rehabilitation. For an ergonomic HCI, we utilize a soft, highly compliant (“skin-like”) electrode, which addresses critical issues of an existing rigid and planar electrode combined with a problematic conductive electrolyte and adhesive pad. The skin-like electrode offers a highly conformal, user-comfortable interaction with the skin for long-term wearable, high-fidelity recording of swallowing electromyograms on the chin. Mechanics modeling and experimental quantification captures the ultra-elastic mechanical characteristics of an open mesh microstructured sensor, conjugated with an elastomeric membrane. Systematic in vivo studies investigate the functionality of the soft electronics for HCI-enabled swallowing training, which includes the application of a biofeedback system to detect swallowing behavior. The collection of results demonstrates clinical feasibility of the ergonomic electronics in HCI-driven rehabilitation for patients with swallowing disorders.
Starbuck, John Marlow; Ghoneima, Ahmed; Kula, Katherine
2014-03-01
Cleft lip with or without cleft palate (CL/P) is a relatively common craniofacial malformation involving bony and soft-tissue disruptions of the nasolabial and dentoalveolar regions. The combination of CL/P and subsequent craniofacial surgeries to close the cleft and improve appearance of the cutaneous upper lip and nose can cause scarring and muscle pull, possibly resulting in soft-tissue depth asymmetries across the face. We tested the hypothesis that tissue depths in children with unilateral CL/P exhibit differences in symmetry across the sides of the face. Twenty-eight tissue depths were measured on cone-beam computed tomography images of children with unilateral CL/P (n = 55), aged 7 to 17 years, using Dolphin software (version 11.5). Significant differences in tissue depth symmetry were found around the cutaneous upper lip and nose in patients with unilateral CL/P.
Soft evolution of multi-jet final states
Gerwick, Erik; Schumann, Steffen; Höche, Stefan; ...
2015-02-16
We present a new framework for computing resummed and matched distributions in processes with many hard QCD jets. The intricate color structure of soft gluon emission at large angles renders resummed calculations highly non-trivial in this case. We automate all ingredients necessary for the color evolution of the soft function at next-to-leading-logarithmic accuracy, namely the selection of the color bases and the projections of color operators and Born amplitudes onto those bases. Explicit results for all QCD processes with up to 2 → 5 partons are given. We also devise a new tree-level matching scheme for resummed calculations which exploitsmore » a quasi-local subtraction based on the Catani-Seymour dipole formalism. We implement both resummation and matching in the Sherpa event generator. As a proof of concept, we compute the resummed and matched transverse-thrust distribution for hadronic collisions.« less
Schröder, Jan; Hsu, Arthur; Boyle, Samantha E.; Macintyre, Geoff; Cmero, Marek; Tothill, Richard W.; Johnstone, Ricky W.; Shackleton, Mark; Papenfuss, Anthony T.
2014-01-01
Motivation: Methods for detecting somatic genome rearrangements in tumours using next-generation sequencing are vital in cancer genomics. Available algorithms use one or more sources of evidence, such as read depth, paired-end reads or split reads to predict structural variants. However, the problem remains challenging due to the significant computational burden and high false-positive or false-negative rates. Results: In this article, we present Socrates (SOft Clip re-alignment To idEntify Structural variants), a highly efficient and effective method for detecting genomic rearrangements in tumours that uses only split-read data. Socrates has single-nucleotide resolution, identifies micro-homologies and untemplated sequence at break points, has high sensitivity and high specificity and takes advantage of parallelism for efficient use of resources. We demonstrate using simulated and real data that Socrates performs well compared with a number of existing structural variant detection tools. Availability and implementation: Socrates is released as open source and available from http://bioinf.wehi.edu.au/socrates. Contact: papenfuss@wehi.edu.au Supplementary information: Supplementary data are available at Bioinformatics online. PMID:24389656
Trajectory optimization for lunar soft landing with complex constraints
NASA Astrophysics Data System (ADS)
Chu, Huiping; Ma, Lin; Wang, Kexin; Shao, Zhijiang; Song, Zhengyu
2017-11-01
A unified trajectory optimization framework with initialization strategies is proposed in this paper for lunar soft landing for various missions with specific requirements. Two main missions of interest are Apollo-like Landing from low lunar orbit and Vertical Takeoff Vertical Landing (a promising mobility method) on the lunar surface. The trajectory optimization is characterized by difficulties arising from discontinuous thrust, multi-phase connections, jump of attitude angle, and obstacles avoidance. Here R-function is applied to deal with the discontinuities of thrust, checkpoint constraints are introduced to connect multiple landing phases, attitude angular rate is designed to get rid of radical changes, and safeguards are imposed to avoid collision with obstacles. The resulting dynamic problems are generally with complex constraints. The unified framework based on Gauss Pseudospectral Method (GPM) and Nonlinear Programming (NLP) solver are designed to solve the problems efficiently. Advanced initialization strategies are developed to enhance both the convergence and computation efficiency. Numerical results demonstrate the adaptability of the framework for various landing missions, and the performance of successful solution of difficult dynamic problems.
Soft tissue deformation modelling through neural dynamics-based reaction-diffusion mechanics.
Zhang, Jinao; Zhong, Yongmin; Gu, Chengfan
2018-05-30
Soft tissue deformation modelling forms the basis of development of surgical simulation, surgical planning and robotic-assisted minimally invasive surgery. This paper presents a new methodology for modelling of soft tissue deformation based on reaction-diffusion mechanics via neural dynamics. The potential energy stored in soft tissues due to a mechanical load to deform tissues away from their rest state is treated as the equivalent transmembrane potential energy, and it is distributed in the tissue masses in the manner of reaction-diffusion propagation of nonlinear electrical waves. The reaction-diffusion propagation of mechanical potential energy and nonrigid mechanics of motion are combined to model soft tissue deformation and its dynamics, both of which are further formulated as the dynamics of cellular neural networks to achieve real-time computational performance. The proposed methodology is implemented with a haptic device for interactive soft tissue deformation with force feedback. Experimental results demonstrate that the proposed methodology exhibits nonlinear force-displacement relationship for nonlinear soft tissue deformation. Homogeneous, anisotropic and heterogeneous soft tissue material properties can be modelled through the inherent physical properties of mass points. Graphical abstract Soft tissue deformation modelling with haptic feedback via neural dynamics-based reaction-diffusion mechanics.
Haj-Mirzaian, Arya; Thawait, Gaurav K; Tanaka, Miho J; Demehri, Shadpour
2017-06-01
Patellofemoral instability (PI) is defined as single or multiple episodes of patellar dislocation. Imaging modalities are useful for characterization of patellar malalignment, maltracking, underlying morphologic abnormalities, and stabilizing soft-tissue injuries. Using these findings, orthopedic surgeons can decide when to operate, determine the best operation, and measure degree of correction postoperatively in PI patients. Also, these methods assist with PI diagnosis in some suspicious cases. Magnetic resonance imaging is the preferred method especially in the setting of acute dislocations. Multidetector computed tomography allows a more accurate assessment for malalignment such as patellar tilt and lateral subluxation and secondary osteoarthritis. Dynamic magnetic resonance imaging and 4-dimensional computed tomography have been introduced for better kinematic assessment of the patellofemoral maltracking during extension-flexion motions. In this review article, we will discuss the currently available evidence regarding both the conventional and the novel imaging modalities that can be used for diagnosis and characterization of PI.
Ji, Haoran; Wang, Chengshan; Li, Peng; ...
2017-09-20
The integration of distributed generators (DGs) exacerbates the feeder power flow fluctuation and load unbalanced condition in active distribution networks (ADNs). The unbalanced feeder load causes inefficient use of network assets and network congestion during system operation. The flexible interconnection based on the multi-terminal soft open point (SOP) significantly benefits the operation of ADNs. The multi-terminal SOP, which is a controllable power electronic device installed to replace the normally open point, provides accurate active and reactive power flow control to enable the flexible connection of feeders. An enhanced SOCP-based method for feeder load balancing using the multi-terminal SOP is proposedmore » in this paper. Furthermore, by regulating the operation of the multi-terminal SOP, the proposed method can mitigate the unbalanced condition of feeder load and simultaneously reduce the power losses of ADNs. Then, the original non-convex model is converted into a second-order cone programming (SOCP) model using convex relaxation. In order to tighten the SOCP relaxation and improve the computation efficiency, an enhanced SOCP-based approach is developed to solve the proposed model. Finally, case studies are performed on the modified IEEE 33-node system to verify the effectiveness and efficiency of the proposed method.« less
DOE Office of Scientific and Technical Information (OSTI.GOV)
Ji, Haoran; Wang, Chengshan; Li, Peng
The integration of distributed generators (DGs) exacerbates the feeder power flow fluctuation and load unbalanced condition in active distribution networks (ADNs). The unbalanced feeder load causes inefficient use of network assets and network congestion during system operation. The flexible interconnection based on the multi-terminal soft open point (SOP) significantly benefits the operation of ADNs. The multi-terminal SOP, which is a controllable power electronic device installed to replace the normally open point, provides accurate active and reactive power flow control to enable the flexible connection of feeders. An enhanced SOCP-based method for feeder load balancing using the multi-terminal SOP is proposedmore » in this paper. Furthermore, by regulating the operation of the multi-terminal SOP, the proposed method can mitigate the unbalanced condition of feeder load and simultaneously reduce the power losses of ADNs. Then, the original non-convex model is converted into a second-order cone programming (SOCP) model using convex relaxation. In order to tighten the SOCP relaxation and improve the computation efficiency, an enhanced SOCP-based approach is developed to solve the proposed model. Finally, case studies are performed on the modified IEEE 33-node system to verify the effectiveness and efficiency of the proposed method.« less
[Soft contactlenses in general practice (author's transl)].
Miller, B
1975-07-01
In contrast to the hard lenses the soft lens has enough permeability for oxygen and water-soluble substances, whereas high molecular substances, bacteria and virus cannot penetrate the soft lenses, so long as their surfaces are intact. The two principal production methods, the spin cast method and the lathe-turned method are compared. The duration of wearing of the soft lens depends on the deposits of proteins from the tears on the surface of the lens and the desinfection method. The daily boiling of the lenses shortens their useful life, while chemical desinfection causes besides bacteriolysis, damage of the corneal cell protein. The new cleaners on the base of proteolytic plant enzymes promise good results. For the optical correction of astigmatism with more than 1 cyl, soft lenses with conic outer surface are used or combinations of a soft and a hard lens (Duosystem). The therapeutic use of soft lenses has as aim: protection of the cornea against mechanical irritation, release of pain, protracted administration output of medicaments. Further indications for use: aseptic corneal inflammation and corneal defects.
Nondestructive pavement evaluation using ILLI-PAVE based artificial neural network models.
DOT National Transportation Integrated Search
2008-09-01
The overall objective in this research project is to develop advanced pavement structural analysis models for more accurate solutions with fast computation schemes. Soft computing and modeling approaches, specifically the Artificial Neural Network (A...
Gambon, D. L; Brand, H. S; Nieuw Amerongen, A.V
2010-01-01
This case report describes a 9-year-old boy with severe tooth wear as a result of drinking a single glass of soft drink per day. This soft drink was consumed over a period of one to two hours, while he was gaming intensively on his computer. As a result, a deep bite, enamel cupping, sensitivity of primary teeth and loss of fillings occurred. Therefore, dentists should be aware that in patients who are gaming intensively, the erosive potential of soft drinks can be potentiated by mechanical forces leading to excessive tooth wear. PMID:21243073
3D exemplar-based random walks for tooth segmentation from cone-beam computed tomography images
DOE Office of Scientific and Technical Information (OSTI.GOV)
Pei, Yuru, E-mail: peiyuru@cis.pku.edu.cn; Ai, Xin
Purpose: Tooth segmentation is an essential step in acquiring patient-specific dental geometries from cone-beam computed tomography (CBCT) images. Tooth segmentation from CBCT images is still a challenging task considering the comparatively low image quality caused by the limited radiation dose, as well as structural ambiguities from intercuspation and nearby alveolar bones. The goal of this paper is to present and discuss the latest accomplishments in semisupervised tooth segmentation with adaptive 3D shape constraints. Methods: The authors propose a 3D exemplar-based random walk method of tooth segmentation from CBCT images. The proposed method integrates semisupervised label propagation and regularization by 3Dmore » exemplar registration. To begin with, the pure random walk method is to get an initial segmentation of the teeth, which tends to be erroneous because of the structural ambiguity of CBCT images. And then, as an iterative refinement, the authors conduct a regularization by using 3D exemplar registration, as well as label propagation by random walks with soft constraints, to improve the tooth segmentation. In the first stage of the iteration, 3D exemplars with well-defined topologies are adapted to fit the tooth contours, which are obtained from the random walks based segmentation. The soft constraints on voxel labeling are defined by shape-based foreground dentine probability acquired by the exemplar registration, as well as the appearance-based probability from a support vector machine (SVM) classifier. In the second stage, the labels of the volume-of-interest (VOI) are updated by the random walks with soft constraints. The two stages are optimized iteratively. Instead of the one-shot label propagation in the VOI, an iterative refinement process can achieve a reliable tooth segmentation by virtue of exemplar-based random walks with adaptive soft constraints. Results: The proposed method was applied for tooth segmentation of twenty clinically captured CBCT images. Three metrics, including the Dice similarity coefficient (DSC), the Jaccard similarity coefficient (JSC), and the mean surface deviation (MSD), were used to quantitatively analyze the segmentation of anterior teeth including incisors and canines, premolars, and molars. The segmentation of the anterior teeth achieved a DSC up to 98%, a JSC of 97%, and an MSD of 0.11 mm compared with manual segmentation. For the premolars, the average values of DSC, JSC, and MSD were 98%, 96%, and 0.12 mm, respectively. The proposed method yielded a DSC of 95%, a JSC of 89%, and an MSD of 0.26 mm for molars. Aside from the interactive definition of label priors by the user, automatic tooth segmentation can be achieved in an average of 1.18 min. Conclusions: The proposed technique enables an efficient and reliable tooth segmentation from CBCT images. This study makes it clinically practical to segment teeth from CBCT images, thus facilitating pre- and interoperative uses of dental morphologies in maxillofacial and orthodontic treatments.« less
[Gas gangrene or inflammation of the neck--diagnostic difficulties].
Kedzierski, B; Całka, K; Wilczyński, K; Bojarski, B; Jaźwiec, P; Bogdał, M T; Stokrocki, W
2000-01-01
The authors describe a patient with an extensive inflammation of the neck soft tissues as a complication of the peritonsillar abscess. Follow-up computed tomography revealed gasi-form follicles in the inflammed neck soft tissues, suggesting gas gangrene. We report disseminate ways of the inflammation process on the financial tonsil, reasons of the gangrene also the infections of soft tissues caused by anaerobic bacteries--Clostridium. CT--examination in inflammatory tumors of the neck is valuable, permits to exclude expansion process, but it cannot give unequivocal answer to differentiate gas gangrene and phlegmon.
Roger W. Perry; Ronald E. Thill; Philip A. Tappe; David G. Peitz
2004-01-01
Abstract - Recent policy changes have eliminated clearcutting as the primary pine regeneration method on Federal lands in the Southern United States. However, the effects of alternative natural regeneration methods on soft mast production are unknown. We compared plant coverage and mast production of 37 soft mast-producing plants among four...
Harris, Bryan T; Montero, Daniel; Grant, Gerald T; Morton, Dean; Llop, Daniel R; Lin, Wei-Shao
2017-02-01
This clinical report proposes a digital workflow using 2-dimensional (2D) digital photographs, a 3D extraoral facial scan, and cone beam computed tomography (CBCT) volumetric data to create a 3D virtual patient with craniofacial hard tissue, remaining dentition (including surrounding intraoral soft tissue), and the realistic appearance of facial soft tissue at an exaggerated smile under static conditions. The 3D virtual patient was used to assist the virtual diagnostic tooth arrangement process, providing patient with a pleasing preoperative virtual smile design that harmonized with facial features. The 3D virtual patient was also used to gain patient's pretreatment approval (as a communication tool), design a prosthetically driven surgical plan for computer-guided implant surgery, and fabricate the computer-aided design and computer-aided manufacturing (CAD-CAM) interim prostheses. Copyright © 2016 Editorial Council for the Journal of Prosthetic Dentistry. Published by Elsevier Inc. All rights reserved.
[Magnetic resonance imaging in facial injuries and digital fusion CT/MRI].
Kozakiewicz, Marcin; Olszycki, Marek; Arkuszewski, Piotr; Stefańczyk, Ludomir
2006-01-01
Magnetic resonance images [MRI] and their digital fusion with computed tomography [CT] data, observed in patients affected with facial injuries, are presented in this study. The MR imaging of 12 posttraumatic patients was performed in the same plains as their previous CT scans. Evaluation focused on quality of the facial soft tissues depicting, which was unsatisfactory in CT. Using the own "Dental Studio" programme the digital fusion of the both modalities was performed. Pathologic dislocations and injures of facial soft tissues are visualized better in MRI than in CT examination. Especially MRI properly reveals disturbances in intraorbital soft structures. MRI-based assessment is valuable in patients affected with facial soft tissues injuries, especially in case of orbita/sinuses hernia. Fusion CT/MRI scans allows to evaluate simultaneously bone structure and soft tissues of the same region.
Soft Actuators for Small-Scale Robotics.
Hines, Lindsey; Petersen, Kirstin; Lum, Guo Zhan; Sitti, Metin
2017-04-01
This review comprises a detailed survey of ongoing methodologies for soft actuators, highlighting approaches suitable for nanometer- to centimeter-scale robotic applications. Soft robots present a special design challenge in that their actuation and sensing mechanisms are often highly integrated with the robot body and overall functionality. When less than a centimeter, they belong to an even more special subcategory of robots or devices, in that they often lack on-board power, sensing, computation, and control. Soft, active materials are particularly well suited for this task, with a wide range of stimulants and a number of impressive examples, demonstrating large deformations, high motion complexities, and varied multifunctionality. Recent research includes both the development of new materials and composites, as well as novel implementations leveraging the unique properties of soft materials. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
Towards an ab initio theory for metal L-edge soft X-ray spectroscopy of molecular aggregates.
Preuße, Marie; Bokarev, Sergey I; Aziz, Saadullah G; Kühn, Oliver
2016-11-01
The Frenkel exciton model was adapted to describe X-ray absorption and resonant inelastic scattering spectra of polynuclear transition metal complexes by means of the restricted active space self-consistent field method. The proposed approach allows to substantially decrease the requirements on computational resources if compared to a full supermolecular quantum chemical treatment. This holds true, in particular, in cases where the dipole approximation to the electronic transition charge density can be applied. The computational protocol was applied to the calculation of X-ray spectra of the hemin complex, which forms dimers in aqueous solution. The aggregation effects were found to be comparable to the spectral alterations due to the replacement of the axial ligand by solvent molecules.
Response Funtions for Computing Absorbed Dose to Skeletal Tissues from Photon Irradiation
DOE Office of Scientific and Technical Information (OSTI.GOV)
Eckerman, Keith F; Bolch, W E; Zankl, M
2007-01-01
The calculation of absorbed dose in skeletal tissues at radiogenic risk has been a difficult problem because the relevant structures cannot be represented in conventional geometric terms nor can they be visualised in the tomographic image data used to define the computational models of the human body. The active marrow, the tissue of concern in leukaemia induction, is present within the spongiosa regions of trabecular bone, whereas the osteoprogenitor cells at risk for bone cancer induction are considered to be within the soft tissues adjacent to the mineral surfaces. The International Commission on Radiological Protection (ICRP) recommends averaging the absorbedmore » energy over the active marrow within the spongiosa and over the soft tissues within 10 mm of the mineral surface for leukaemia and bone cancer induction, respectively. In its forthcoming recommendation, it is expected that the latter guidance will be changed to include soft tissues within 50 mm of the mineral surfaces. To address the computational problems, the skeleton of the proposed ICRP reference computational phantom has been subdivided to identify those voxels associated with cortical shell, spongiosa and the medullary cavity of the long bones. It is further proposed that the Monte Carlo calculations with these phantoms compute the energy deposition in the skeletal target tissues as the product of the particle fluence in the skeletal subdivisions and applicable fluence-to-dose response functions. This paper outlines the development of such response functions for photons.« less
Estimating patient-specific soft-tissue properties in a TKA knee.
Ewing, Joseph A; Kaufman, Michelle K; Hutter, Erin E; Granger, Jeffrey F; Beal, Matthew D; Piazza, Stephen J; Siston, Robert A
2016-03-01
Surgical technique is one factor that has been identified as critical to success of total knee arthroplasty. Researchers have shown that computer simulations can aid in determining how decisions in the operating room generally affect post-operative outcomes. However, to use simulations to make clinically relevant predictions about knee forces and motions for a specific total knee patient, patient-specific models are needed. This study introduces a methodology for estimating knee soft-tissue properties of an individual total knee patient. A custom surgical navigation system and stability device were used to measure the force-displacement relationship of the knee. Soft-tissue properties were estimated using a parameter optimization that matched simulated tibiofemoral kinematics with experimental tibiofemoral kinematics. Simulations using optimized ligament properties had an average root mean square error of 3.5° across all tests while simulations using generic ligament properties taken from literature had an average root mean square error of 8.4°. Specimens showed large variability among ligament properties regardless of similarities in prosthetic component alignment and measured knee laxity. These results demonstrate the importance of soft-tissue properties in determining knee stability, and suggest that to make clinically relevant predictions of post-operative knee motions and forces using computer simulations, patient-specific soft-tissue properties are needed. © 2015 Orthopaedic Research Society. Published by Wiley Periodicals, Inc.
Application of a Dense Gas Technique for Sterilizing Soft Biomaterials
Karajanagi, Sandeep S.; Yoganathan, Roshan; Mammucari, Raffaella; Park, Hyoungshin; Cox, Julian; Zeitels, Steven M.; Langer, Robert; Foster, Neil R.
2017-01-01
Sterilization of soft biomaterials such as hydrogels is challenging because existing methods such as gamma irradiation, steam sterilization, or ethylene oxide sterilization, while effective at achieving high sterility assurance levels (SAL), may compromise their physicochemical properties and biocompatibility. New methods that effectively sterilize soft biomaterials without compromising their properties are therefore required. In this report, a dense-carbon dioxide (CO2)-based technique was used to sterilize soft polyethylene glycol (PEG)-based hydrogels while retaining their structure and physicochemical properties. Conventional sterilization methods such as gamma irradiation and steam sterilization severely compromised the structure of the hydrogels. PEG hydrogels with high water content and low elastic shear modulus (a measure of stiffness) were deliberately inoculated with bacteria and spores and then subjected to dense CO2. The dense CO2-based methods effectively sterilized the hydrogels achieving a SAL of 10−7 without compromising the viscoelastic properties, pH, water-content, and structure of the gels. Furthermore, dense CO2-treated gels were biocompatible and non-toxic when implanted subcutaneously in ferrets. The application of novel dense CO2-based methods to sterilize soft biomaterials has implications in developing safe sterilization methods for soft biomedical implants such as dermal fillers and viscosupplements. PMID:21337339
Akashi, Masaya; Teraoka, Shun; Kakei, Yasumasa; Kusumoto, Junya; Hasegawa, Takumi; Minamikawa, Tsutomu; Hashikawa, Kazunobu; Komori, Takahide
2018-04-01
This study aimed to evaluate posttreatment soft-tissue changes in patients with oral cancer with computed tomography (CT). To accomplish that purpose, a scoring system was established, referring to the criteria of lower leg lymphedema (LE). One hundred and six necks in 95 patients who underwent oral oncologic surgery with neck dissection (ND) were analyzed retrospectively using routine follow-up CT images. A two-point scoring system to evaluate soft-tissue changes (so-called "LE score") was established as follows: Necks with a "honeycombing" appearance were assigned 1 point. Necks with "taller than wide" fat lobules were assigned 1 point. Necks with neither appearance were assigned 0 points. Comparisons between patients with LE score ≥1 and LE score = 0 at 6 months postoperatively were performed using the Fisher exact test for discrete variables and the Mann-Whitney U test for continuous variables. Univariate predictors associated with posttreatment changes (i.e., LE score ≥1 at 6 months postoperatively) were entered into a multivariate logistic regression analysis. Values of p < 0.05 were considered to indicate statistical significance. The occurrence of the posttreatment soft-tissue changes was 32%. Multivariate logistic regression analysis showed that postoperative radiation therapy (RT) and bilateral ND were potential risk factors of posttreatment soft-tissue changes on CT images. Sequential evaluation of "honeycombing" and the "taller than wide" appearances on routine follow-up CT revealed the persistence of posttreatment soft-tissue changes in patients who underwent oral cancer treatment, and those potential risk factors were postoperative RT and bilateral ND.
Simulation and observation of line-slip structures in columnar structures of soft spheres
NASA Astrophysics Data System (ADS)
Winkelmann, J.; Haffner, B.; Weaire, D.; Mughal, A.; Hutzler, S.
2017-07-01
We present the computed phase diagram of columnar structures of soft spheres under pressure, of which the main feature is the appearance and disappearance of line slips, the shearing of adjacent spirals, as pressure is increased. A comparable experimental observation is made on a column of bubbles under forced drainage, clearly exhibiting the expected line slip.
Simulation and observation of line-slip structures in columnar structures of soft spheres.
Winkelmann, J; Haffner, B; Weaire, D; Mughal, A; Hutzler, S
2017-07-01
We present the computed phase diagram of columnar structures of soft spheres under pressure, of which the main feature is the appearance and disappearance of line slips, the shearing of adjacent spirals, as pressure is increased. A comparable experimental observation is made on a column of bubbles under forced drainage, clearly exhibiting the expected line slip.
Numerical simulation of a soft-x-ray Li laser pumped with synchrotron radiation
DOE Office of Scientific and Technical Information (OSTI.GOV)
Rozsnyai, B.; Watanabe, H.; Csonka, P.L.
1985-07-01
Results of a computer simulation are reported for a lithium soft-x-ray laser pumped by synchro- tron radiation. Coherent stimulated emission of the photons of interest occurs in Li II 1s2p..-->..Li II 1s/sup 2/ transitions. Calculated results include the dominant ion and photon densities and the laser gain.
KIM, Jaehwan; EOM, Kidong; YOON, Hakyoung
2017-01-01
A 14-year-old dog weighing 4 kg presented with hypotension only in the right forelimb. Thoracic radiography revealed a round soft tissue opacity near the aortic arch and below the second thoracic vertebra on a lateral view. Three-dimensional computed tomography angiography clearly revealed stenosis and aneurysmal dilation of an aberrant right subclavian artery. Stenosis and aneurysm of an aberrant subclavian artery should be included as a differential diagnosis in dogs showing a round soft tissue opacity near the aortic arch and below the thoracic vertebra on the lateral thoracic radiograph. PMID:28496026
Kim, Jaehwan; Eom, Kidong; Yoon, Hakyoung
2017-06-16
A 14-year-old dog weighing 4 kg presented with hypotension only in the right forelimb. Thoracic radiography revealed a round soft tissue opacity near the aortic arch and below the second thoracic vertebra on a lateral view. Three-dimensional computed tomography angiography clearly revealed stenosis and aneurysmal dilation of an aberrant right subclavian artery. Stenosis and aneurysm of an aberrant subclavian artery should be included as a differential diagnosis in dogs showing a round soft tissue opacity near the aortic arch and below the thoracic vertebra on the lateral thoracic radiograph.
Verifying Stability of Dynamic Soft-Computing Systems
NASA Technical Reports Server (NTRS)
Wen, Wu; Napolitano, Marcello; Callahan, John
1997-01-01
Soft computing is a general term for algorithms that learn from human knowledge and mimic human skills. Example of such algorithms are fuzzy inference systems and neural networks. Many applications, especially in control engineering, have demonstrated their appropriateness in building intelligent systems that are flexible and robust. Although recent research have shown that certain class of neuro-fuzzy controllers can be proven bounded and stable, they are implementation dependent and difficult to apply to the design and validation process. Many practitioners adopt the trial and error approach for system validation or resort to exhaustive testing using prototypes. In this paper, we describe our on-going research towards establishing necessary theoretic foundation as well as building practical tools for the verification and validation of soft-computing systems. A unified model for general neuro-fuzzy system is adopted. Classic non-linear system control theory and recent results of its applications to neuro-fuzzy systems are incorporated and applied to the unified model. It is hoped that general tools can be developed to help the designer to visualize and manipulate the regions of stability and boundedness, much the same way Bode plots and Root locus plots have helped conventional control design and validation.
Use of Soft Computing Technologies For Rocket Engine Control
NASA Technical Reports Server (NTRS)
Trevino, Luis C.; Olcmen, Semih; Polites, Michael
2003-01-01
The problem to be addressed in this paper is to explore how the use of Soft Computing Technologies (SCT) could be employed to further improve overall engine system reliability and performance. Specifically, this will be presented by enhancing rocket engine control and engine health management (EHM) using SCT coupled with conventional control technologies, and sound software engineering practices used in Marshall s Flight Software Group. The principle goals are to improve software management, software development time and maintenance, processor execution, fault tolerance and mitigation, and nonlinear control in power level transitions. The intent is not to discuss any shortcomings of existing engine control and EHM methodologies, but to provide alternative design choices for control, EHM, implementation, performance, and sustaining engineering. The approaches outlined in this paper will require knowledge in the fields of rocket engine propulsion, software engineering for embedded systems, and soft computing technologies (i.e., neural networks, fuzzy logic, and Bayesian belief networks), much of which is presented in this paper. The first targeted demonstration rocket engine platform is the MC-1 (formerly FASTRAC Engine) which is simulated with hardware and software in the Marshall Avionics & Software Testbed laboratory that
A review of setup error in supine breast radiotherapy using cone-beam computed tomography
DOE Office of Scientific and Technical Information (OSTI.GOV)
Batumalai, Vikneswary, E-mail: Vikneswary.batumalai@sswahs.nsw.gov.au; Liverpool and Macarthur Cancer Therapy Centres, New South Wales; Ingham Institute of Applied Medical Research, Sydney, New South Wales
2016-10-01
Setup error in breast radiotherapy (RT) measured with 3-dimensional cone-beam computed tomography (CBCT) is becoming more common. The purpose of this study is to review the literature relating to the magnitude of setup error in breast RT measured with CBCT. The different methods of image registration between CBCT and planning computed tomography (CT) scan were also explored. A literature search, not limited by date, was conducted using Medline and Google Scholar with the following key words: breast cancer, RT, setup error, and CBCT. This review includes studies that reported on systematic and random errors, and the methods used when registeringmore » CBCT scans with planning CT scan. A total of 11 relevant studies were identified for inclusion in this review. The average magnitude of error is generally less than 5 mm across a number of studies reviewed. The common registration methods used when registering CBCT scans with planning CT scan are based on bony anatomy, soft tissue, and surgical clips. No clear relationships between the setup errors detected and methods of registration were observed from this review. Further studies are needed to assess the benefit of CBCT over electronic portal image, as CBCT remains unproven to be of wide benefit in breast RT.« less
Cassereau, Didier; Nauleau, Pierre; Bendjoudi, Aniss; Minonzio, Jean-Gabriel; Laugier, Pascal; Bossy, Emmanuel; Grimal, Quentin
2014-07-01
The development of novel quantitative ultrasound (QUS) techniques to measure the hip is critically dependent on the possibility to simulate the ultrasound propagation. One specificity of hip QUS is that ultrasounds propagate through a large thickness of soft tissue, which can be modeled by a homogeneous fluid in a first approach. Finite difference time domain (FDTD) algorithms have been widely used to simulate QUS measurements but they are not adapted to simulate ultrasonic propagation over long distances in homogeneous media. In this paper, an hybrid numerical method is presented to simulate hip QUS measurements. A two-dimensional FDTD simulation in the vicinity of the bone is coupled to the semi-analytic calculation of the Rayleigh integral to compute the wave propagation between the probe and the bone. The method is used to simulate a setup dedicated to the measurement of circumferential guided waves in the cortical compartment of the femoral neck. The proposed approach is validated by comparison with a full FDTD simulation and with an experiment on a bone phantom. For a realistic QUS configuration, the computation time is estimated to be sixty times less with the hybrid method than with a full FDTD approach. Copyright © 2013 Elsevier B.V. All rights reserved.
Autonomous undulatory serpentine locomotion utilizing body dynamics of a fluidic soft robot.
Onal, Cagdas D; Rus, Daniela
2013-06-01
Soft robotics offers the unique promise of creating inherently safe and adaptive systems. These systems bring man-made machines closer to the natural capabilities of biological systems. An important requirement to enable self-contained soft mobile robots is an on-board power source. In this paper, we present an approach to create a bio-inspired soft robotic snake that can undulate in a similar way to its biological counterpart using pressure for actuation power, without human intervention. With this approach, we develop an autonomous soft snake robot with on-board actuation, power, computation and control capabilities. The robot consists of four bidirectional fluidic elastomer actuators in series to create a traveling curvature wave from head to tail along its body. Passive wheels between segments generate the necessary frictional anisotropy for forward locomotion. It takes 14 h to build the soft robotic snake, which can attain an average locomotion speed of 19 mm s(-1).
Markvicka, Eric J; Bartlett, Michael D; Huang, Xiaonan; Majidi, Carmel
2018-07-01
Large-area stretchable electronics are critical for progress in wearable computing, soft robotics and inflatable structures. Recent efforts have focused on engineering electronics from soft materials-elastomers, polyelectrolyte gels and liquid metal. While these materials enable elastic compliance and deformability, they are vulnerable to tearing, puncture and other mechanical damage modes that cause electrical failure. Here, we introduce a material architecture for soft and highly deformable circuit interconnects that are electromechanically stable under typical loading conditions, while exhibiting uncompromising resilience to mechanical damage. The material is composed of liquid metal droplets suspended in a soft elastomer; when damaged, the droplets rupture to form new connections with neighbours and re-route electrical signals without interruption. Since self-healing occurs spontaneously, these materials do not require manual repair or external heat. We demonstrate this unprecedented electronic robustness in a self-repairing digital counter and self-healing soft robotic quadruped that continue to function after significant damage.
Chaturvedi, Saurabh; Khaled Addas, Mohamed; Al Humaidi, Abdullah Saad Ali; Al Qahtani, Abdulrazaq Mohammed; Al Qahtani, Mubarak Daghash
2017-01-01
To determine the prevalence of type of soft palate in targeted population. Using computer technology in dentistry, intraoral digital scanner, and 3D analysis software tool, study was conducted. 100 patients selected from the outpatient clinics were divided into two groups based on the ages of 20-40 years and 41-60 years with equal ratio of males and females. Each selected patient's maxillary arch was scanned with intraoral scanner; images so obtained were sectioned in anteroposterior cross section and with the 3D analysis software; the angulation between hard and soft palate was determined. The prevalence of type II soft palate (angulation between hard and soft palate is between 10 and 45 degrees) was highest, 60% in group 1 and 44% in group 2. The difference between genders was statistically significant with p value <0.05 in both the groups, although females had higher angulation compared to the males in all classes of both groups. In targeted population of Aseer Province, Saudi Arabia, the prevalence of type II soft palate was more common, with higher soft palate angulation among females. The advanced age had no effect in the type of soft palate in the region.
SoftWAXS: a computational tool for modeling wide-angle X-ray solution scattering from biomolecules.
Bardhan, Jaydeep; Park, Sanghyun; Makowski, Lee
2009-10-01
This paper describes a computational approach to estimating wide-angle X-ray solution scattering (WAXS) from proteins, which has been implemented in a computer program called SoftWAXS. The accuracy and efficiency of SoftWAXS are analyzed for analytically solvable model problems as well as for proteins. Key features of the approach include a numerical procedure for performing the required spherical averaging and explicit representation of the solute-solvent boundary and the surface of the hydration layer. These features allow the Fourier transform of the excluded volume and hydration layer to be computed directly and with high accuracy. This approach will allow future investigation of different treatments of the electron density in the hydration shell. Numerical results illustrate the differences between this approach to modeling the excluded volume and a widely used model that treats the excluded-volume function as a sum of Gaussians representing the individual atomic excluded volumes. Comparison of the results obtained here with those from explicit-solvent molecular dynamics clarifies shortcomings inherent to the representation of solvent as a time-averaged electron-density profile. In addition, an assessment is made of how the calculated scattering patterns depend on input parameters such as the solute-atom radii, the width of the hydration shell and the hydration-layer contrast. These results suggest that obtaining predictive calculations of high-resolution WAXS patterns may require sophisticated treatments of solvent.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Kam, S; Youn, H; Kim, H
2014-06-01
Purpose: To compare and analyze two novel algorithms for the assessment of modulation transfer functions (MTFs) of computed tomography (CT) systems using a simple acrylic cylindrical phantom Method and Materials: Images of the acrylic cylindrical phantom were acquired by a GE LightSpeed 16 RT (GE Healthcare, Milwaukee, WI) using 120 kVp, 330 mA, 2.5 mm slice thickness, 10 cm field-of view (FOV), four reconstruction kernels (e.g. standard, soft, detail, bone, and lung). Two different algorithms were used to analyze images for MTF assessment. First, Richard et al. suggested a task-based MTF assessment method through an edge spread function (ESF) whichmore » described pixel intensities as a function of distance from the center. The MTF was obtained as the absolute value of Fourier transform of the differentiated ESF. Second, Ohkubo et al. devised an effective method to determine the point spread function (PSF) of CT system accompanied with verification. The line spread function (LSF), which was the one-dimensional integration of the PSF, was used to obtain the MTF. We validated the reliability of two above-mentioned methods through the comparison with a conventional method using a thin tungsten wire phantom. Results: The measured MTFs by two methods were mostly similar each other for standard, soft, and detail kernels. In 0.6 lp/mm, the MTF difference between two methods were 0.012(standard), 0.004(soft), and 0.037(detail). They also coincided with the MTF by the conventional method well. However, there were considerable distinctions for bone and lung kernels containing edge enhancement that might cause undershoots near the peak of the LSF. Conclusions: We compared two novel methods to assess task-based MTFs for clinical CT systems especially using a simple acrylic cylindrical phantom with high-convenience and low-cost, and validated them against a conventional method. This work can provide a practical solution to users for the quality assurance of CT.« less
CAE "FOCUS" for modelling and simulating electron optics systems: development and application
NASA Astrophysics Data System (ADS)
Trubitsyn, Andrey; Grachev, Evgeny; Gurov, Victor; Bochkov, Ilya; Bochkov, Victor
2017-02-01
Electron optics is a theoretical base of scientific instrument engineering. Mathematical simulation of occurring processes is a base for contemporary design of complicated devices of the electron optics. Problems of the numerical mathematical simulation are effectively solved by CAE system means. CAE "FOCUS" developed by the authors includes fast and accurate methods: boundary element method (BEM) for the electric field calculation, Runge-Kutta- Fieghlberg method for the charged particle trajectory computation controlling an accuracy of calculations, original methods for search of terms for the angular and time-of-flight focusing. CAE "FOCUS" is organized as a collection of modules each of which solves an independent (sub) task. A range of physical and analytical devices, in particular a microfocus X-ray tube of high power, has been developed using this soft.
LDPC decoder with a limited-precision FPGA-based floating-point multiplication coprocessor
NASA Astrophysics Data System (ADS)
Moberly, Raymond; O'Sullivan, Michael; Waheed, Khurram
2007-09-01
Implementing the sum-product algorithm, in an FPGA with an embedded processor, invites us to consider a tradeoff between computational precision and computational speed. The algorithm, known outside of the signal processing community as Pearl's belief propagation, is used for iterative soft-decision decoding of LDPC codes. We determined the feasibility of a coprocessor that will perform product computations. Our FPGA-based coprocessor (design) performs computer algebra with significantly less precision than the standard (e.g. integer, floating-point) operations of general purpose processors. Using synthesis, targeting a 3,168 LUT Xilinx FPGA, we show that key components of a decoder are feasible and that the full single-precision decoder could be constructed using a larger part. Soft-decision decoding by the iterative belief propagation algorithm is impacted both positively and negatively by a reduction in the precision of the computation. Reducing precision reduces the coding gain, but the limited-precision computation can operate faster. A proposed solution offers custom logic to perform computations with less precision, yet uses the floating-point format to interface with the software. Simulation results show the achievable coding gain. Synthesis results help theorize the the full capacity and performance of an FPGA-based coprocessor.
3D exemplar-based random walks for tooth segmentation from cone-beam computed tomography images.
Pei, Yuru; Ai, Xingsheng; Zha, Hongbin; Xu, Tianmin; Ma, Gengyu
2016-09-01
Tooth segmentation is an essential step in acquiring patient-specific dental geometries from cone-beam computed tomography (CBCT) images. Tooth segmentation from CBCT images is still a challenging task considering the comparatively low image quality caused by the limited radiation dose, as well as structural ambiguities from intercuspation and nearby alveolar bones. The goal of this paper is to present and discuss the latest accomplishments in semisupervised tooth segmentation with adaptive 3D shape constraints. The authors propose a 3D exemplar-based random walk method of tooth segmentation from CBCT images. The proposed method integrates semisupervised label propagation and regularization by 3D exemplar registration. To begin with, the pure random walk method is to get an initial segmentation of the teeth, which tends to be erroneous because of the structural ambiguity of CBCT images. And then, as an iterative refinement, the authors conduct a regularization by using 3D exemplar registration, as well as label propagation by random walks with soft constraints, to improve the tooth segmentation. In the first stage of the iteration, 3D exemplars with well-defined topologies are adapted to fit the tooth contours, which are obtained from the random walks based segmentation. The soft constraints on voxel labeling are defined by shape-based foreground dentine probability acquired by the exemplar registration, as well as the appearance-based probability from a support vector machine (SVM) classifier. In the second stage, the labels of the volume-of-interest (VOI) are updated by the random walks with soft constraints. The two stages are optimized iteratively. Instead of the one-shot label propagation in the VOI, an iterative refinement process can achieve a reliable tooth segmentation by virtue of exemplar-based random walks with adaptive soft constraints. The proposed method was applied for tooth segmentation of twenty clinically captured CBCT images. Three metrics, including the Dice similarity coefficient (DSC), the Jaccard similarity coefficient (JSC), and the mean surface deviation (MSD), were used to quantitatively analyze the segmentation of anterior teeth including incisors and canines, premolars, and molars. The segmentation of the anterior teeth achieved a DSC up to 98%, a JSC of 97%, and an MSD of 0.11 mm compared with manual segmentation. For the premolars, the average values of DSC, JSC, and MSD were 98%, 96%, and 0.12 mm, respectively. The proposed method yielded a DSC of 95%, a JSC of 89%, and an MSD of 0.26 mm for molars. Aside from the interactive definition of label priors by the user, automatic tooth segmentation can be achieved in an average of 1.18 min. The proposed technique enables an efficient and reliable tooth segmentation from CBCT images. This study makes it clinically practical to segment teeth from CBCT images, thus facilitating pre- and interoperative uses of dental morphologies in maxillofacial and orthodontic treatments.
A high throughput architecture for a low complexity soft-output demapping algorithm
NASA Astrophysics Data System (ADS)
Ali, I.; Wasenmüller, U.; Wehn, N.
2015-11-01
Iterative channel decoders such as Turbo-Code and LDPC decoders show exceptional performance and therefore they are a part of many wireless communication receivers nowadays. These decoders require a soft input, i.e., the logarithmic likelihood ratio (LLR) of the received bits with a typical quantization of 4 to 6 bits. For computing the LLR values from a received complex symbol, a soft demapper is employed in the receiver. The implementation cost of traditional soft-output demapping methods is relatively large in high order modulation systems, and therefore low complexity demapping algorithms are indispensable in low power receivers. In the presence of multiple wireless communication standards where each standard defines multiple modulation schemes, there is a need to have an efficient demapper architecture covering all the flexibility requirements of these standards. Another challenge associated with hardware implementation of the demapper is to achieve a very high throughput in double iterative systems, for instance, MIMO and Code-Aided Synchronization. In this paper, we present a comprehensive communication and hardware performance evaluation of low complexity soft-output demapping algorithms to select the best algorithm for implementation. The main goal of this work is to design a high throughput, flexible, and area efficient architecture. We describe architectures to execute the investigated algorithms. We implement these architectures on a FPGA device to evaluate their hardware performance. The work has resulted in a hardware architecture based on the figured out best low complexity algorithm delivering a high throughput of 166 Msymbols/second for Gray mapped 16-QAM modulation on Virtex-5. This efficient architecture occupies only 127 slice registers, 248 slice LUTs and 2 DSP48Es.
Soft Tissue Structure Modelling for Use in Orthopaedic Applications and Musculoskeletal Biomechanics
NASA Astrophysics Data System (ADS)
Audenaert, E. A.; Mahieu, P.; van Hoof, T.; Pattyn, C.
2009-12-01
We present our methodology for the three-dimensional anatomical and geometrical description of soft tissues, relevant for orthopaedic surgical applications and musculoskeletal biomechanics. The technique involves the segmentation and geometrical description of muscles and neurovascular structures from high-resolution computer tomography scanning for the reconstruction of generic anatomical models. These models can be used for quantitative interpretation of anatomical and biomechanical aspects of different soft tissue structures. This approach should allow the use of these data in other application fields, such as musculoskeletal modelling, simulations for radiation therapy, and databases for use in minimally invasive, navigated and robotic surgery.
Qiu, Lin; Lan, Lianjun; Feng, Yue; Huang, Zhanwen; Chen, Yue
2015-01-01
Here we report a case of 41-year-old man with a soft tissue density mass at right upper lung and palpable abscesses at right upper backside and right wrist. (18)F-fluorodeoxyglucose positron emission tomography/computed tomography demonstrated a 7.8 × 5.0 cm mass with soft-tissue density in the upper lobe of the right lung with high metabolic activity. The infiltrative mass extended to adjacent chest wall soft tissue. Final diagnosis of pulmonary actinomycosis with multiple abscesses was made. The patient responded well to antibiotics treatment.
Dynamic load testing on the bearing capacity of prestressed tubular concrete piles in soft ground
NASA Astrophysics Data System (ADS)
Yu, Chuang; Liu, Songyu
2008-11-01
Dynamic load testing (DLT) is a high strain test method for assessing pile performance. The shaft capacity of a driven PTC (prestressed tubular concrete) pile in marine soft ground will vary with time after installation. The DLT method has been successfully transferred to the testing of prestressed pipe piles in marine soft clay of Lianyungang area in China. DLT is investigated to determine the ultimate bearing capacity of single pile at different period after pile installation. The ultimate bearing capacity of single pile was founded to increase more than 70% during the inventing 3 months, which demonstrate the time effect of rigid pile bearing capacity in marine soft ground. Furthermore, the skin friction and axial force along the pile shaft are presented as well, which present the load transfer mechanism of pipe pile in soft clay. It shows the economy and efficiency of DLT method compared to static load testing method.
Gutiérrez, J. J.; Russell, James K.
2016-01-01
Background. Cardiopulmonary resuscitation (CPR) feedback devices are being increasingly used. However, current accelerometer-based devices overestimate chest displacement when CPR is performed on soft surfaces, which may lead to insufficient compression depth. Aim. To assess the performance of a new algorithm for measuring compression depth and rate based on two accelerometers in a simulated resuscitation scenario. Materials and Methods. Compressions were provided to a manikin on two mattresses, foam and sprung, with and without a backboard. One accelerometer was placed on the chest and the second at the manikin's back. Chest displacement and mattress displacement were calculated from the spectral analysis of the corresponding acceleration every 2 seconds and subtracted to compute the actual sternal-spinal displacement. Compression rate was obtained from the chest acceleration. Results. Median unsigned error in depth was 2.1 mm (4.4%). Error was 2.4 mm in the foam and 1.7 mm in the sprung mattress (p < 0.001). Error was 3.1/2.0 mm and 1.8/1.6 mm with/without backboard for foam and sprung, respectively (p < 0.001). Median error in rate was 0.9 cpm (1.0%), with no significant differences between test conditions. Conclusion. The system provided accurate feedback on chest compression depth and rate on soft surfaces. Our solution compensated mattress displacement, avoiding overestimation of compression depth when CPR is performed on soft surfaces. PMID:27999808
Gebremedhin, Daniel H; Weatherford, Charles A
2015-02-01
This is a response to the comment we received on our recent paper "Calculations for the one-dimensional soft Coulomb problem and the hard Coulomb limit." In that paper, we introduced a computational algorithm that is appropriate for solving stiff initial value problems, and which we applied to the one-dimensional time-independent Schrödinger equation with a soft Coulomb potential. We solved for the eigenpairs using a shooting method and hence turned it into an initial value problem. In particular, we examined the behavior of the eigenpairs as the softening parameter approached zero (hard Coulomb limit). The commenters question the existence of the ground state of the hard Coulomb potential, which we inferred by extrapolation of the softening parameter to zero. A key distinction between the commenters' approach and ours is that they consider only the half-line while we considered the entire x axis. Based on mathematical considerations, the commenters consider only a vanishing solution function at the origin, and they question our conclusion that the ground state of the hard Coulomb potential exists. The ground state we inferred resembles a δ(x), and hence it cannot even be addressed based on their argument. For the excited states, there is agreement with the fact that the particle is always excluded from the origin. Our discussion with regard to the symmetry of the excited states is an extrapolation of the soft Coulomb case and is further explained herein.
Clinical and computed tomography features of secondary renal hyperparathyroidism
Vanbrugghe, Benoît; Blond, Laurent; Carioto, Lisa; Carmel, Eric Norman; Nadeau, Marie-Eve
2011-01-01
An atypical case of secondary renal hyperparathyroidism was diagnosed in a 9-year-old miniature schnauzer after a skull computed tomography (CT) showed the presence of 2 bilateral and symmetrical soft tissue maxillary masses, and osteopenia of the skull. PMID:21532826
Joint Carrier-Phase Synchronization and LDPC Decoding
NASA Technical Reports Server (NTRS)
Simon, Marvin; Valles, Esteban
2009-01-01
A method has been proposed to increase the degree of synchronization of a radio receiver with the phase of a suppressed carrier signal modulated with a binary- phase-shift-keying (BPSK) or quaternary- phase-shift-keying (QPSK) signal representing a low-density parity-check (LDPC) code. This method is an extended version of the method described in Using LDPC Code Constraints to Aid Recovery of Symbol Timing (NPO-43112), NASA Tech Briefs, Vol. 32, No. 10 (October 2008), page 54. Both methods and the receiver architectures in which they would be implemented belong to a class of timing- recovery methods and corresponding receiver architectures characterized as pilotless in that they do not require transmission and reception of pilot signals. The proposed method calls for the use of what is known in the art as soft decision feedback to remove the modulation from a replica of the incoming signal prior to feeding this replica to a phase-locked loop (PLL) or other carrier-tracking stage in the receiver. Soft decision feedback refers to suitably processed versions of intermediate results of iterative computations involved in the LDPC decoding process. Unlike a related prior method in which hard decision feedback (the final sequence of decoded symbols) is used to remove the modulation, the proposed method does not require estimation of the decoder error probability. In a basic digital implementation of the proposed method, the incoming signal (having carrier phase theta theta (sub c) plus noise would first be converted to inphase (I) and quadrature (Q) baseband signals by mixing it with I and Q signals at the carrier frequency [wc/(2 pi)] generated by a local oscillator. The resulting demodulated signals would be processed through one-symbol-period integrate and- dump filters, the outputs of which would be sampled and held, then multiplied by a soft-decision version of the baseband modulated signal. The resulting I and Q products consist of terms proportional to the cosine and sine of the carrier phase cc as well as correlated noise components. These products would be fed as inputs to a digital PLL that would include a number-controlled oscillator (NCO), which provides an estimate of the carrier phase, theta(sub c).
Soft computing approach to 3D lung nodule segmentation in CT.
Badura, P; Pietka, E
2014-10-01
This paper presents a novel, multilevel approach to the segmentation of various types of pulmonary nodules in computed tomography studies. It is based on two branches of computational intelligence: the fuzzy connectedness (FC) and the evolutionary computation. First, the image and auxiliary data are prepared for the 3D FC analysis during the first stage of an algorithm - the masks generation. Its main goal is to process some specific types of nodules connected to the pleura or vessels. It consists of some basic image processing operations as well as dedicated routines for the specific cases of nodules. The evolutionary computation is performed on the image and seed points in order to shorten the FC analysis and improve its accuracy. After the FC application, the remaining vessels are removed during the postprocessing stage. The method has been validated using the first dataset of studies acquired and described by the Lung Image Database Consortium (LIDC) and by its latest release - the LIDC-IDRI (Image Database Resource Initiative) database. Copyright © 2014 Elsevier Ltd. All rights reserved.
Density functional theory calculations of 95Mo NMR parameters in solid-state compounds.
Cuny, Jérôme; Furet, Eric; Gautier, Régis; Le Pollès, Laurent; Pickard, Chris J; d'Espinose de Lacaillerie, Jean-Baptiste
2009-12-21
The application of periodic density functional theory-based methods to the calculation of (95)Mo electric field gradient (EFG) and chemical shift (CS) tensors in solid-state molybdenum compounds is presented. Calculations of EFG tensors are performed using the projector augmented-wave (PAW) method. Comparison of the results with those obtained using the augmented plane wave + local orbitals (APW+lo) method and with available experimental values shows the reliability of the approach for (95)Mo EFG tensor calculation. CS tensors are calculated using the recently developed gauge-including projector augmented-wave (GIPAW) method. This work is the first application of the GIPAW method to a 4d transition-metal nucleus. The effects of ultra-soft pseudo-potential parameters, exchange-correlation functionals and structural parameters are precisely examined. Comparison with experimental results allows the validation of this computational formalism.
Shivdasani, Divya; Singh, Natasha; Pereira, Melvika; Zade, Anand
2017-01-01
Sarcomas are a heterogeneous group of rare tumors and arise either from soft tissue or from bone. Soft-tissue sarcomas (STSs) initially metastasize to the lungs. Metastases to extrapulmonary sites such as liver, brain, and soft tissue distant from primary tumor usually develop later. However, cases with isolated adrenal metastasis without disseminated disease have been reported in literature. We present a case of primary myxoid liposarcoma of the lower limb, in which staging 18 -F fluorodeoxyglucose positron emission tomography-computed tomography (FDG PET-CT) scan detected a suspicious FDG avid adrenal lesion which eventually on resection was diagnosed as asymptomatic pheochromocytoma. Pheochromocytomas have been reported to demonstrate FDG uptake mimicking metastasis. Hence, while interpreting FDG PET-CT scans in the context of STSs, both the extrapulmonary metastatic potential of aggressive histological subtypes of sarcoma and rare possibility of FDG avid coexistent benign tumor should be taken into consideration.
DeMaere, Matthew Z.
2016-01-01
Background Chromosome conformation capture, coupled with high throughput DNA sequencing in protocols like Hi-C and 3C-seq, has been proposed as a viable means of generating data to resolve the genomes of microorganisms living in naturally occuring environments. Metagenomic Hi-C and 3C-seq datasets have begun to emerge, but the feasibility of resolving genomes when closely related organisms (strain-level diversity) are present in the sample has not yet been systematically characterised. Methods We developed a computational simulation pipeline for metagenomic 3C and Hi-C sequencing to evaluate the accuracy of genomic reconstructions at, above, and below an operationally defined species boundary. We simulated datasets and measured accuracy over a wide range of parameters. Five clustering algorithms were evaluated (2 hard, 3 soft) using an adaptation of the extended B-cubed validation measure. Results When all genomes in a sample are below 95% sequence identity, all of the tested clustering algorithms performed well. When sequence data contains genomes above 95% identity (our operational definition of strain-level diversity), a naive soft-clustering extension of the Louvain method achieves the highest performance. Discussion Previously, only hard-clustering algorithms have been applied to metagenomic 3C and Hi-C data, yet none of these perform well when strain-level diversity exists in a metagenomic sample. Our simple extension of the Louvain method performed the best in these scenarios, however, accuracy remained well below the levels observed for samples without strain-level diversity. Strain resolution is also highly dependent on the amount of available 3C sequence data, suggesting that depth of sequencing must be carefully considered during experimental design. Finally, there appears to be great scope to improve the accuracy of strain resolution through further algorithm development. PMID:27843713
Ting, Samuel T; Ahmad, Rizwan; Jin, Ning; Craft, Jason; Serafim da Silveira, Juliana; Xue, Hui; Simonetti, Orlando P
2017-04-01
Sparsity-promoting regularizers can enable stable recovery of highly undersampled magnetic resonance imaging (MRI), promising to improve the clinical utility of challenging applications. However, lengthy computation time limits the clinical use of these methods, especially for dynamic MRI with its large corpus of spatiotemporal data. Here, we present a holistic framework that utilizes the balanced sparse model for compressive sensing and parallel computing to reduce the computation time of cardiac MRI recovery methods. We propose a fast, iterative soft-thresholding method to solve the resulting ℓ1-regularized least squares problem. In addition, our approach utilizes a parallel computing environment that is fully integrated with the MRI acquisition software. The methodology is applied to two formulations of the multichannel MRI problem: image-based recovery and k-space-based recovery. Using measured MRI data, we show that, for a 224 × 144 image series with 48 frames, the proposed k-space-based approach achieves a mean reconstruction time of 2.35 min, a 24-fold improvement compared a reconstruction time of 55.5 min for the nonlinear conjugate gradient method, and the proposed image-based approach achieves a mean reconstruction time of 13.8 s. Our approach can be utilized to achieve fast reconstruction of large MRI datasets, thereby increasing the clinical utility of reconstruction techniques based on compressed sensing. Magn Reson Med 77:1505-1515, 2017. © 2016 International Society for Magnetic Resonance in Medicine. © 2016 International Society for Magnetic Resonance in Medicine.
PRESAGE: Protecting Structured Address Generation against Soft Errors
DOE Office of Scientific and Technical Information (OSTI.GOV)
Sharma, Vishal C.; Gopalakrishnan, Ganesh; Krishnamoorthy, Sriram
Modern computer scaling trends in pursuit of larger component counts and power efficiency have, unfortunately, lead to less reliable hardware and consequently soft errors escaping into application data ("silent data corruptions"). Techniques to enhance system resilience hinge on the availability of efficient error detectors that have high detection rates, low false positive rates, and lower computational overhead. Unfortunately, efficient detectors to detect faults during address generation (to index large arrays) have not been widely researched. We present a novel lightweight compiler-driven technique called PRESAGE for detecting bit-flips affecting structured address computations. A key insight underlying PRESAGE is that any addressmore » computation scheme that flows an already incurred error is better than a scheme that corrupts one particular array access but otherwise (falsely) appears to compute perfectly. Enabling the flow of errors allows one to situate detectors at loop exit points, and helps turn silent corruptions into easily detectable error situations. Our experiments using PolyBench benchmark suite indicate that PRESAGE-based error detectors have a high error-detection rate while incurring low overheads.« less
PRESAGE: Protecting Structured Address Generation against Soft Errors
DOE Office of Scientific and Technical Information (OSTI.GOV)
Sharma, Vishal C.; Gopalakrishnan, Ganesh; Krishnamoorthy, Sriram
Modern computer scaling trends in pursuit of larger component counts and power efficiency have, unfortunately, lead to less reliable hardware and consequently soft errors escaping into application data ("silent data corruptions"). Techniques to enhance system resilience hinge on the availability of efficient error detectors that have high detection rates, low false positive rates, and lower computational overhead. Unfortunately, efficient detectors to detect faults during address generation have not been widely researched (especially in the context of indexing large arrays). We present a novel lightweight compiler-driven technique called PRESAGE for detecting bit-flips affecting structured address computations. A key insight underlying PRESAGEmore » is that any address computation scheme that propagates an already incurred error is better than a scheme that corrupts one particular array access but otherwise (falsely) appears to compute perfectly. Ensuring the propagation of errors allows one to place detectors at loop exit points and helps turn silent corruptions into easily detectable error situations. Our experiments using the PolyBench benchmark suite indicate that PRESAGE-based error detectors have a high error-detection rate while incurring low overheads.« less
Resnick, C M; Dang, R R; Glick, S J; Padwa, B L
2017-03-01
Three-dimensional (3D) soft tissue prediction is replacing two-dimensional analysis in planning for orthognathic surgery. The accuracy of different computational models to predict soft tissue changes in 3D, however, is unclear. A retrospective pilot study was implemented to assess the accuracy of Dolphin 3D software in making these predictions. Seven patients who had a single-segment Le Fort I osteotomy and had preoperative (T 0 ) and >6-month postoperative (T 1 ) cone beam computed tomography (CBCT) scans and 3D photographs were included. The actual skeletal change was determined by subtracting the T 0 from the T 1 CBCT. 3D photographs were overlaid onto the T 0 CBCT and virtual skeletal movements equivalent to the achieved repositioning were applied using Dolphin 3D planner. A 3D soft tissue prediction (T P ) was generated and differences between the T P and T 1 images (error) were measured at 14 points and at the nasolabial angle. A mean linear prediction error of 2.91±2.16mm was found. The mean error at the nasolabial angle was 8.1±5.6°. In conclusion, the ability to accurately predict 3D soft tissue changes after Le Fort I osteotomy using Dolphin 3D software is limited. Copyright © 2016 International Association of Oral and Maxillofacial Surgeons. Published by Elsevier Ltd. All rights reserved.
Strand Plasticity Governs Fatigue in Colloidal Gels
NASA Astrophysics Data System (ADS)
van Doorn, Jan Maarten; Verweij, Joanne E.; Sprakel, Joris; van der Gucht, Jasper
2018-05-01
The repeated loading of a solid leads to microstructural damage that ultimately results in catastrophic material failure. While posing a major threat to the stability of virtually all materials, the microscopic origins of fatigue, especially for soft solids, remain elusive. Here we explore fatigue in colloidal gels as prototypical inhomogeneous soft solids by combining experiments and computer simulations. Our results reveal how mechanical loading leads to irreversible strand stretching, which builds slack into the network that softens the solid at small strains and causes strain hardening at larger deformations. We thus find that microscopic plasticity governs fatigue at much larger scales. This gives rise to a new picture of fatigue in soft thermal solids and calls for new theoretical descriptions of soft gel mechanics in which local plasticity is taken into account.
Elastic anisotropy of Opalinus Clay under variable saturation and triaxial stress
NASA Astrophysics Data System (ADS)
Sarout, Joel; Esteban, Lionel; Delle Piane, Claudio; Maney, Bruce; Dewhurst, David N.
2014-09-01
A novel experimental method is introduced to estimate the Thomsen's elastic anisotropy parameters ɛ and δ of a transversely isotropic shale under variable stress and saturation conditions. The method consists in recording P-wave velocities along numerous paths on a cylindrical specimen using miniature ultrasonic transducers. Such an overdetermined set of measurements is specifically designed to reduce the uncertainty associated with the determination of Thomsen's δ parameter compared to the classical method for which a single off-axis measurement is used (usually at 45° to the specimen's axis). This method is applied to a specimen of Opalinus Clay recovered from the Mont-Terri Underground Research Laboratory in Switzerland. The specimen is first saturated with brine at low effective pressure and then subjected to an effective pressure cycle up to 40 MPa, followed by a triaxial loading up to failure. During saturation and deformation, the evolution of P-wave velocities along a maximum of 240 ray paths is monitored and Thomsen's parameters α, ɛ and δ are computed by fitting Thomsen's weak anisotropy model to the data. The values of ɛ and δ obtained at the highest confining pressures reached during the experiment are comparable with those predicted from X-ray diffraction texture analysis and modelling for Opalinus Clay reported in the literature. These models neglect the effect of soft-porosity on elastic properties, but become relevant when soft porosity is closed at high effective pressure.
Neurosurgery simulation using non-linear finite element modeling and haptic interaction
NASA Astrophysics Data System (ADS)
Lee, Huai-Ping; Audette, Michel; Joldes, Grand R.; Enquobahrie, Andinet
2012-02-01
Real-time surgical simulation is becoming an important component of surgical training. To meet the realtime requirement, however, the accuracy of the biomechancial modeling of soft tissue is often compromised due to computing resource constraints. Furthermore, haptic integration presents an additional challenge with its requirement for a high update rate. As a result, most real-time surgical simulation systems employ a linear elasticity model, simplified numerical methods such as the boundary element method or spring-particle systems, and coarse volumetric meshes. However, these systems are not clinically realistic. We present here an ongoing work aimed at developing an efficient and physically realistic neurosurgery simulator using a non-linear finite element method (FEM) with haptic interaction. Real-time finite element analysis is achieved by utilizing the total Lagrangian explicit dynamic (TLED) formulation and GPU acceleration of per-node and per-element operations. We employ a virtual coupling method for separating deformable body simulation and collision detection from haptic rendering, which needs to be updated at a much higher rate than the visual simulation. The system provides accurate biomechancial modeling of soft tissue while retaining a real-time performance with haptic interaction. However, our experiments showed that the stability of the simulator depends heavily on the material property of the tissue and the speed of colliding objects. Hence, additional efforts including dynamic relaxation are required to improve the stability of the system.
Zhang, Jiangheng; Chen, Yangxi; Zhou, Xiukun
2002-09-01
The characteristics of lip-mouth region including the soft and hard tissues in smiling position with frontal fixed position photographic computer-aided analysis were studied. The subjects were 80 persons (40 male and 40 females, age range: 17 to approximately 25 years) with acceptable faces and individual normal occlusions. The subjects were asked to take maximum smiling position to accept photographic measurement with computer-aided analysis. The maximum smile line could be divided into 3 categories: low smile line (16.25%), average smile line (68.75%), and high smile line (15%). The method adopting maximum smiling position to study the lip-month region is reproducible and comparable. This study would be helpful to provide a quantitative reference for clinical investigation, diagnosis, treatment and efficacy appraisal.
Soft hairy warped black hole entropy
NASA Astrophysics Data System (ADS)
Grumiller, Daniel; Hacker, Philip; Merbis, Wout
2018-02-01
We reconsider warped black hole solutions in topologically massive gravity and find novel boundary conditions that allow for soft hairy excitations on the horizon. To compute the associated symmetry algebra we develop a general framework to compute asymptotic symmetries in any Chern-Simons-like theory of gravity. We use this to show that the near horizon symmetry algebra consists of two u (1) current algebras and recover the surprisingly simple entropy formula S = 2 π( J 0 + + J 0 - ), where J 0 ± are zero mode charges of the current algebras. This provides the first example of a locally non-maximally symmetric configuration exhibiting this entropy law and thus non-trivial evidence for its universality.
Moore, Stephanie N.; Hawley, Gregory D.; Smith, Emily N.; Mignemi, Nicholas A.; Ihejirika, Rivka C.; Yuasa, Masato; Cates, Justin M. M.; Liu, Xulei; Schoenecker, Jonathan G.
2016-01-01
Introduction Soft tissue calcification, including both dystrophic calcification and heterotopic ossification, may occur following injury. These lesions have variable fates as they are either resorbed or persist. Persistent soft tissue calcification may result in chronic inflammation and/or loss of function of that soft tissue. The molecular mechanisms that result in the development and maturation of calcifications are uncertain. As a result, directed therapies that prevent or resorb soft tissue calcifications remain largely unsuccessful. Animal models of post-traumatic soft tissue calcification that allow for cost-effective, serial analysis of an individual animal over time are necessary to derive and test novel therapies. We have determined that a cardiotoxin-induced injury of the muscles in the posterior compartment of the lower extremity represents a useful model in which soft tissue calcification develops remote from adjacent bones, thereby allowing for serial analysis by plain radiography. The purpose of the study was to design and validate a method for quantifying soft tissue calcifications in mice longitudinally using plain radiographic techniques and an ordinal scoring system. Methods Muscle injury was induced by injecting cardiotoxin into the posterior compartment of the lower extremity in mice susceptible to developing soft tissue calcification. Seven days following injury, radiographs were obtained under anesthesia. Multiple researchers applied methods designed to standardize post-image processing of digital radiographs (N = 4) and quantify soft tissue calcification (N = 6) in these images using an ordinal scoring system. Inter- and intra-observer agreement for both post-image processing and the scoring system used was assessed using weighted kappa statistics. Soft tissue calcification quantifications by the ordinal scale were compared to mineral volume measurements (threshold 450.7mgHA/cm3) determined by μCT. Finally, sample-size calculations necessary to discriminate between a 25%, 50%, 75%, and 100% difference in STiCSS score 7 days following burn/CTX induced muscle injury were determined. Results Precision analysis demonstrated substantial to good agreement for both post-image processing (κ = 0.73 to 0.90) and scoring (κ = 0.88 to 0.93), with low inter- and intra-observer variability. Additionally, there was a strong correlation in quantification of soft tissue calcification between the ordinal system and by mineral volume quantification by μCT (Spearman r = 0.83 to 0.89). The ordinal scoring system reliably quantified soft tissue calcification in a burn/CTX-induced soft tissue calcification model compared to non-injured controls (Mann-Whitney rank test: P = 0.0002, ***). Sample size calculations revealed that 6 mice per group would be required to detect a 50% difference in STiCSS score with a power of 0.8. Finally, the STiCSS was demonstrated to reliably quantify soft tissue calcification [dystrophic calcification and heterotopic ossification] by radiographic analysis, independent of the histopathological state of the mineralization. Conclusions Radiographic analysis can discriminate muscle injury-induced soft tissue calcification from adjacent bone and follow its clinical course over time without requiring the sacrifice of the animal. While the STiCSS cannot identify the specific type of soft tissue calcification present, it is still a useful and valid method by which to quantify the degree of soft tissue calcification. This methodology allows for longitudinal measurements of soft tissue calcification in a single animal, which is relatively less expensive, less time-consuming, and exposes the animal to less radiation than in vivo μCT. Therefore, this high-throughput, longitudinal analytic method for quantifying soft tissue calcification is a viable alternative for the study of soft tissue calcification. PMID:27438007
Ground-Based Correction of Remote-Sensing Spectral Imagery
NASA Technical Reports Server (NTRS)
Alder-Golden, Steven M.; Rochford, Peter; Matthew, Michael; Berk, Alexander
2007-01-01
Software has been developed for an improved method of correcting for the atmospheric optical effects (primarily, effects of aerosols and water vapor) in spectral images of the surface of the Earth acquired by airborne and spaceborne remote-sensing instruments. In this method, the variables needed for the corrections are extracted from the readings of a radiometer located on the ground in the vicinity of the scene of interest. The software includes algorithms that analyze measurement data acquired from a shadow-band radiometer. These algorithms are based on a prior radiation transport software model, called MODTRAN, that has been developed through several versions up to what are now known as MODTRAN4 and MODTRAN5 . These components have been integrated with a user-friendly Interactive Data Language (IDL) front end and an advanced version of MODTRAN4. Software tools for handling general data formats, performing a Langley-type calibration, and generating an output file of retrieved atmospheric parameters for use in another atmospheric-correction computer program known as FLAASH have also been incorporated into the present soft-ware. Concomitantly with the soft-ware described thus far, there has been developed a version of FLAASH that utilizes the retrieved atmospheric parameters to process spectral image data.
[Imaging in rheumatoid arthritis of the elbow].
Lerch, K; Herold, T; Borisch, N; Grifka, J
2003-08-01
Early specific radiologic changes of rheumatoid arthritis can usually be detected in the hands and feet. Later stages of the disease process show a typical centripetal spread of the affected joints, i.e., shoulder, elbow, and knee. For prognostic assessment of cubital rheumatoid arthritis, conventional radiography still remains the gold standard. X-rays allow objective scoring and thus classification into standardized stages. A concentric destruction of the rheumatic joint as compared to deformity in the degenerative joint is the typical radiologic symptom to look for. For soft tissue assessment, ultrasound (US) should be the diagnostic tool of choice. Due to the thin surrounding soft tissue layer, as well as the advanced high-resolution technology, bony structures can also be well demonstrated in any plane. In the early arthritic stages, particularly the small changes, e.g., minimal erosions of the cortical area, are very well detectable by US. The use of "color" allows good evaluation of the synovial inflammatory status. Modern imaging methods such as computer- assisted tomography (CAT) scan and magnetic resonance imaging (MRI) are restricted to a few set indications and should not be chosen for routine examination. More invasive methods such as arthrography are no longer indicated for assessment of cubital rheumatoid arthritis.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Ding, Fei; Ji, Haoran; Wang, Chengshan
Distributed generators (DGs) including photovoltaic panels (PVs) have been integrated dramatically in active distribution networks (ADNs). Due to the strong volatility and uncertainty, the high penetration of PV generation immensely exacerbates the conditions of voltage violation in ADNs. However, the emerging flexible interconnection technology based on soft open points (SOPs) provides increased controllability and flexibility to the system operation. For fully exploiting the regulation ability of SOPs to address the problems caused by PV, this paper proposes a robust optimization method to achieve the robust optimal operation of SOPs in ADNs. A two-stage adjustable robust optimization model is built tomore » tackle the uncertainties of PV outputs, in which robust operation strategies of SOPs are generated to eliminate the voltage violations and reduce the power losses of ADNs. A column-and-constraint generation (C&CG) algorithm is developed to solve the proposed robust optimization model, which are formulated as second-order cone program (SOCP) to facilitate the accuracy and computation efficiency. Case studies on the modified IEEE 33-node system and comparisons with the deterministic optimization approach are conducted to verify the effectiveness and robustness of the proposed method.« less
Incidental Findings on Cone Beam Computed Tomography Studies outside of the Maxillofacial Skeleton
2016-01-01
Objective. To define the presence and prevalence of incidental findings in and around the base of skull from large field-of-view CBCT of the maxillofacial region and to determine their clinical importance. Methods. Four hundred consecutive large fields of view CBCT scans viewed from January 1, 2007, to January 1, 2014, were retrospectively evaluated for incidental findings of the cervical vertebrae and surrounding structures. Findings were categorized into cervical vertebrae, intracranial, soft tissue, airway, carotid artery, lymph node, and skull base findings. Results. A total of 653 incidental findings were identified in 309 of the 400 CBCT scans. The most prevalent incidental findings were soft tissue calcifications (29.71%), followed by intracranial calcifications (27.11%), cervical vertebrae (20.06%), airway (11.49%), external carotid artery calcification (10.41%), lymph node calcification (0.77%), subcutaneous tissue calcification and calcified tendonitis of the longus colli muscle (0.3%), and skull base finding (0.15%). A significant portion of the incidental findings (31.24%) required referral, 17.76% required monitoring, and 51% did not require either. Conclusion. A comprehensive review of the CBCT images beyond the region of interest, especially incidental findings in the base of skull, cervical vertebrae, pharyngeal airway, and soft tissue, is necessary to avoid overlooking clinically significant lesions. PMID:27462350
Soft Robots: Manipulation, Mobility, and Fast Actuation
NASA Astrophysics Data System (ADS)
Shepherd, Robert; Ilievski, Filip; Choi, Wonjae; Stokes, Adam; Morin, Stephen; Mazzeo, Aaron; Kramer, Rebecca; Majidi, Carmel; Wood, Rob; Whitesides, George
2012-02-01
Material innovation will be a key feature in the next generation of robots. A simple, pneumatically powered actuator composed of only soft-elastomers can perform the function of a complex arrangement of mechanical components and electric motors. This talk will focus on soft-lithography as a simple method to fabricate robots--composed of exclusively soft materials (elastomeric polymers). These robots have sophisticated capabilities: a gripper (with no electrical sensors) can manipulate delicate and irregularly shaped objects and a quadrupedal robot can walk to an obstacle (a gap smaller than its walking height) then shrink its body and squeeze through the gap using an undulatory gait. This talk will also introduce a new method of rapidly actuating soft robots. Using this new method, a robot can be caused to jump more than 30 times its height in under 200 milliseconds.
Computer-Generated, Three-Dimensional Character Animation.
ERIC Educational Resources Information Center
Van Baerle, Susan Lynn
This master's thesis begins by discussing the differences between 3-D computer animation of solid three-dimensional, or monolithic, objects, and the animation of characters, i.e., collections of movable parts with soft pliable surfaces. Principles from two-dimensional character animation that can be transferred to three-dimensional character…
NASA Technical Reports Server (NTRS)
1994-01-01
MathSoft Plus 5.0 is a calculation software package for electrical engineers and computer scientists who need advanced math functionality. It incorporates SmartMath, an expert system that determines a strategy for solving difficult mathematical problems. SmartMath was the result of the integration into Mathcad of CLIPS, a NASA-developed shell for creating expert systems. By using CLIPS, MathSoft, Inc. was able to save the time and money involved in writing the original program.
NASA Astrophysics Data System (ADS)
Winkelmann, J.; Haffner, B.; Weaire, D.; Mughal, A.; Hutzler, S.
2017-07-01
We present the computed phase diagram of columnar structures of soft spheres under pressure, of which the main feature is the appearance and disappearance of line slips, the shearing of adjacent spirals, as pressure is increased. A comparable experimental observation is made on a column of bubbles under forced drainage, clearly exhibiting the expected line slip.
Prevalence of Soft Tissue Calcifications in CBCT Images of Mandibular Region.
Khojastepour, Leila; Haghnegahdar, Abdolaziz; Sayar, Hamed
2017-06-01
Most of the soft tissue calcifications within the head and neck region might not be accompanied by clinical symptoms but may indicate some pathological conditions. The aim of this research was to determine the prevalence of soft tissue calcifications in cone beam computed tomography (CBCT) images of mandibular region. In this cross sectional study the CBCT images of 602 patients including 294 men and 308 women with mean age 41.38±15.18 years were evaluated regarding the presence, anatomical location; type (single or multiple) and size of soft tissue calcification in mandibular region. All CBCT images were acquired by NewTom VGi scanner. Odds ratio and chi-square tests were used for data analysis and p < 0.05 was considered to be statistically significant. 156 out of 602 patients had at least one soft tissue calcification in their mandibular region (25.9%. of studied population with mean age 51.7±18.03 years). Men showed significantly higher rate of soft tissue calcification than women (30.3% vs. 21.8%). Soft tissue calcification was predominantly seen at posterior region of the mandible (88%) and most of them were single (60.7%). The prevalence of soft tissue calcification increased with age. Most of the detected soft tissue calcifications were smaller than 3mm (90%). Soft tissue calcifications in mandibular area were a relatively common finding especially in posterior region and more likely to happen in men and in older age group.
NASA Astrophysics Data System (ADS)
Yoshizawa, Masasumi; Nakamura, Yuuta; Ishiguro, Masataka; Moriya, Tadashi
2007-07-01
In this paper, we describe a method of compensating the attenuation of the ultrasound caused by soft tissue in the transducer vibration method for the measurement of the acoustic impedance of in vivo bone. In the in vivo measurement, the acoustic impedance of bone is measured through soft tissue; therefore, the amplitude of the ultrasound reflected from the bone is attenuated. This attenuation causes an error of the order of -20 to -30% when the acoustic impedance is determined from the measured signals. To compensate the attenuation, the attenuation coefficient and length of the soft tissue are measured by the transducer vibration method. In the experiment using a phantom, this method allows the measurement of the acoustic impedance typically with an error as small as -8 to 10%.
Revealing bending and force in a soft body through a plant root inspired approach
Lucarotti, Chiara; Totaro, Massimo; Sadeghi, Ali; Mazzolai, Barbara; Beccai, Lucia
2015-01-01
An emerging challenge in soft robotics research is to reveal mechanical solicitations in a soft body. Nature provides amazing clues to develop unconventional components that are capable of compliant interactions with the environment and living beings, avoiding mechanical and algorithmic complexity of robotic design. We inspire from plant-root mechanoperception and develop a strategy able to reveal bending and applied force in a soft body with only two sensing elements of the same kind, and a null computational effort. The stretching processes that lead to opposite tissue deformations on the two sides of the root wall are emulated with two tactile sensing elements, made of soft and stretchable materials, which conform to reversible changes in the shape of the body they are built in and follow its deformations. Comparing the two sensory responses, we can discriminate the concave and the convex side of the bent body. Hence, we propose a new strategy to reveal in a soft body the maximum bending angle (or the maximum deflection) and the externally applied force according to the body's mechanical configuration. PMID:25739743
Kido, S; Kuriyama, K; Hosomi, N; Inoue, E; Kuroda, C; Horai, T
2000-02-01
This study endeavored to clarify the usefulness of single-exposure dual-energy subtraction computed radiography (CR) of the chest and the ability of soft-copy images to detect low-contrast simulated pulmonary nodules. Conventional and bone-subtracted CR images of 25 chest phantom image sets with a low-contrast nylon nodule and 25 without a nodule were interpreted by 12 observers (6 radiologists, 6 chest physicians) who rated each on a continuous confidence scale and marked the position of the nodule if one was present. Hard-copy images were 7 x 7-inch laser-printed CR films, and soft-copy images were displayed on a 21-inch noninterlaced color CRT monitor with an optimized dynamic range. Soft-copy images were adjusted to the same size as hard-copy images and were viewed under darkened illumination in the reading room. No significant differences were found between hard- and soft-copy images. In conclusion, the soft-copy images were found to be useful in detecting low-contrast simulated pulmonary nodules.
Torsional Ultrasound Sensor Optimization for Soft Tissue Characterization
Melchor, Juan; Muñoz, Rafael; Rus, Guillermo
2017-01-01
Torsion mechanical waves have the capability to characterize shear stiffness moduli of soft tissue. Under this hypothesis, a computational methodology is proposed to design and optimize a piezoelectrics-based transmitter and receiver to generate and measure the response of torsional ultrasonic waves. The procedure employed is divided into two steps: (i) a finite element method (FEM) is developed to obtain a transmitted and received waveform as well as a resonance frequency of a previous geometry validated with a semi-analytical simplified model and (ii) a probabilistic optimality criteria of the design based on inverse problem from the estimation of robust probability of detection (RPOD) to maximize the detection of the pathology defined in terms of changes of shear stiffness. This study collects different options of design in two separated models, in transmission and contact, respectively. The main contribution of this work describes a framework to establish such as forward, inverse and optimization procedures to choose a set of appropriate parameters of a transducer. This methodological framework may be generalizable for other different applications. PMID:28617353
Necrotizing fasciitis: microbiological characteristics and predictors of postoperative outcome
2009-01-01
Objective Necrotizing fasciitis is a life threatening soft-tissue infection with a high morbidity and mortality. Prompt treatment based on extensive surgical debridement and antibiotic therapies are the therapeutic principles. Methods The medical records of patients with necrotizing fasciitis (n = 26) from 1996 to 2005 were retrospectively analyzed. Results The localization of necrotizing fasciitis was most commonly the trunk (42.3%). Type I polymicrobial infection was the dominating infection. The involvement of anaerobic bacteria was associated with an increase in the number of surgical revisions (p = 0.005). Length of postoperative intensive care unit stay, duration of postoperative ventilation and mortality were significantly increased in the ASA IV-V group. Computed tomography displayed only a limited significance as diagnostic tool for initial diagnosis. Conclusions In severe cases the combination of necrotic skin and soft tissue gas facilitates the correct diagnosis, which should than be followed by immediate - and most often - repeated debridement. If anaerobes are isolated an early and aggressive second look is necessary. PMID:19258208
The Evolution of Image-Free Robotic Assistance in Unicompartmental Knee Arthroplasty.
Lonner, Jess H; Moretti, Vincent M
2016-01-01
Semiautonomous robotic technology has been introduced to optimize accuracy of bone preparation, implant positioning, and soft tissue balance in unicompartmental knee arthroplasty (UKA), with the expectation that there will be a resultant improvement in implant durability and survivorship. Currently, roughly one-fifth of UKAs in the US are being performed with robotic assistance, and it is anticipated that there will be substantial growth in market penetration of robotics over the next decade. First-generation robotic technology improved substantially implant position compared to conventional methods; however, high capital costs, uncertainty regarding the value of advanced technologies, and the need for preoperative computed tomography (CT) scans were barriers to broader adoption. Newer image-free semiautonomous robotic technology optimizes both implant position and soft tissue balance, without the need for preoperative CT scans and with pricing and portability that make it suitable for use in an ambulatory surgery center setting, where approximately 40% of these systems are currently being utilized. This article will review the robotic experience for UKA, including rationale, system descriptions, and outcomes.
Sunaguchi, Naoki; Yuasa, Tetsuya; Hirano, Shin-Ichi; Gupta, Rajiv; Ando, Masami
2015-01-01
X-ray phase-contrast tomography can significantly increase the contrast-resolution of conventional attenuation-contrast imaging, especially for soft-tissue structures that have very similar attenuation. Just as in attenuation-based tomography, phase contrast tomography requires a linear dependence of aggregate beam direction on the incremental direction alteration caused by individual voxels along the path of the X-ray beam. Dense objects such as calcifications in biological specimens violate this condition. There are extensive beam deflection artefacts in the vicinity of such structures because they result in large distortion of wave front due to the large difference of refractive index; for such large changes in beam direction, the transmittance of the silicon analyzer crystal saturates and is no longer linearly dependent on the angle of refraction. This paper describes a method by which these effects can be overcome and excellent soft-tissue contrast of phase tomography can be preserved in the vicinity of such artefact-producing structures.
77 FR 38770 - Notice of Consortium on “nSoft Consortium”
Federal Register 2010, 2011, 2012, 2013, 2014
2012-06-29
... DEPARTMENT OF COMMERCE National Institute of Standards and Technology Notice of Consortium on ``n...: NIST will form the ``nSoft Consortium'' to advance and transfer neutron based measurement methods for soft materials manufacturing. The goals of nSoft are to develop neutron- based measurements that...
NASA Astrophysics Data System (ADS)
Manzoni, Francesco; Ryde, Ulf
2018-03-01
We have calculated relative binding affinities for eight tetrafluorophenyl-triazole-thiogalactoside inhibitors of galectin-3 with the alchemical free-energy perturbation approach. We obtain a mean absolute deviation from experimental estimates of only 2-3 kJ/mol and a correlation coefficient (R 2) of 0.5-0.8 for seven relative affinities spanning a range of up to 11 kJ/mol. We also studied the effect of using different methods to calculate the charges of the inhibitor and different sizes of the perturbed group (the atoms that are described by soft-core potentials and are allowed to have differing coordinates). However, the various approaches gave rather similar results and it is not possible to point out one approach as consistently and significantly better than the others. Instead, we suggest that such small and reasonable variations in the computational method can be used to check how stable the calculated results are and to obtain a more accurate estimate of the uncertainty than if performing only one calculation with a single computational setup.
Extraskeletal Ewing sarcoma of the abdominal wall
Farhat, L. Ben; Ghariani, B.; Rabeh, A.; Dali, N.; Said, W.; Hendaoui, L.
2008-01-01
Abstract Ewing sarcoma is most commonly a bone tumour which has usually extended into the soft tissues at the time of diagnosis. Exceptionally, this tumour can have an extraskeletal origin. Clinical or imaging findings are non-specific and diagnosis is based on histology. We report a case of an extraskeletal Ewing sarcoma developed in the soft tissues of the abdominal wall in a 35-year-old woman who presented a painful abdominal wall tumefaction. Ultrasongraphy and computed tomography showed a large, well-defined soft tissue mass developed in the left anterolateral muscle group of the abdominal wall. Surgical biopsy was performed and an extraskeletal Ewing sarcoma was identified histologically. PMID:18818133
Virtual screening for development of new effective compounds against Staphylococcus aureus.
Diniz, Roseane Costa; Soares, Lucas Weba; da Silva, Luis Claudio Nascimento
2018-03-26
Staphylococcus aureus is a notorious pathogenic bacterium causing a wide range of diseases from soft-tissue contamination, to more serious and deep-seated infections. This species is highlighted by its ability to express several kinds of virulence factors and to acquire genes related to drug resistance. Target this number of factors to design any drug is not an easy task. In this review we discuss the importance of computational methods to impulse the development of new drugs against S. aureus. The application of docking methods to screen large library of natural or synthetic compounds and to provide insights into action mechanisms is demonstrated. Particularly, highlighted the studies that validated in silico results with biochemical and microbiological assays. We also comment the computer-aided design of new molecules using some known inhibitors. The confirmation of in silico results with biochemical and microbiological assays allowed the identification of lead molecules that could be used for drug design such as rhodomyrtone, quinuclidine, berberine (and their derivative compounds). The fast development in the computational methods is essential to improve our ability to discovery new drugs, as well as to expand understanding about drug-target interactions. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.
NASA Astrophysics Data System (ADS)
Wu, T. Y.; Lin, S. F.
2013-10-01
Automatic suspected lesion extraction is an important application in computer-aided diagnosis (CAD). In this paper, we propose a method to automatically extract the suspected parotid regions for clinical evaluation in head and neck CT images. The suspected lesion tissues in low contrast tissue regions can be localized with feature-based segmentation (FBS) based on local texture features, and can be delineated with accuracy by modified active contour models (ACM). At first, stationary wavelet transform (SWT) is introduced. The derived wavelet coefficients are applied to derive the local features for FBS, and to generate enhanced energy maps for ACM computation. Geometric shape features (GSFs) are proposed to analyze each soft tissue region segmented by FBS; the regions with higher similarity GSFs with the lesions are extracted and the information is also applied as the initial conditions for fine delineation computation. Consequently, the suspected lesions can be automatically localized and accurately delineated for aiding clinical diagnosis. The performance of the proposed method is evaluated by comparing with the results outlined by clinical experts. The experiments on 20 pathological CT data sets show that the true-positive (TP) rate on recognizing parotid lesions is about 94%, and the dimension accuracy of delineation results can also approach over 93%.
Reduced rank regression via adaptive nuclear norm penalization
Chen, Kun; Dong, Hongbo; Chan, Kung-Sik
2014-01-01
Summary We propose an adaptive nuclear norm penalization approach for low-rank matrix approximation, and use it to develop a new reduced rank estimation method for high-dimensional multivariate regression. The adaptive nuclear norm is defined as the weighted sum of the singular values of the matrix, and it is generally non-convex under the natural restriction that the weight decreases with the singular value. However, we show that the proposed non-convex penalized regression method has a global optimal solution obtained from an adaptively soft-thresholded singular value decomposition. The method is computationally efficient, and the resulting solution path is continuous. The rank consistency of and prediction/estimation performance bounds for the estimator are established for a high-dimensional asymptotic regime. Simulation studies and an application in genetics demonstrate its efficacy. PMID:25045172
Computer algorithm for coding gain
NASA Technical Reports Server (NTRS)
Dodd, E. E.
1974-01-01
Development of a computer algorithm for coding gain for use in an automated communications link design system. Using an empirical formula which defines coding gain as used in space communications engineering, an algorithm is constructed on the basis of available performance data for nonsystematic convolutional encoding with soft-decision (eight-level) Viterbi decoding.
Soft Tissue Alterations in Esthetic Postextraction Sites: A 3-Dimensional Analysis.
Chappuis, V; Engel, O; Shahim, K; Reyes, M; Katsaros, C; Buser, D
2015-09-01
Dimensional alterations of the facial soft and bone tissues following tooth extraction in the esthetic zone play an essential role to achieve successful outcomes in implant therapy. This prospective study is the first to investigate the interplay between the soft tissue dimensions and the underlying bone anatomy during an 8-wk healing period. The analysis is based on sequential 3-dimensional digital surface model superimpositions of the soft and bone tissues using digital impressions and cone beam computed tomography during an 8-wk healing period. Soft tissue thickness in thin and thick bone phenotypes at extraction was similar, averaging 0.7 mm and 0.8 mm, respectively. Interestingly, thin bone phenotypes revealed a 7-fold increase in soft tissue thickness after an 8-wk healing period, whereas in thick bone phenotypes, the soft tissue dimensions remained unchanged. The observed spontaneous soft tissue thickening in thin bone phenotypes resulted in a vertical soft tissue loss of only 1.6 mm, which concealed the underlying vertical bone resorption of 7.5 mm. Because of spontaneous soft tissue thickening, no significant differences were detected in the total tissue loss between thin and thick bone phenotypes at 2, 4, 6, and 8 wk. More than 51% of these dimensional alterations occurred within 2 wk of healing. Even though the observed spontaneous soft tissue thickening in thin bone phenotypes following tooth extraction conceals the pronounced underlying bone resorption pattern by masking the true bone deficiency, spontaneous soft tissue thickening offers advantages for subsequent bone regeneration and implant therapies in sites with high esthetic demand (Clinicaltrials.gov NCT02403700). © International & American Associations for Dental Research.
Li, Z; Liu, Y S; Ye, H Q; Liu, Y S; Hu, W J; Zhou, Y S
2017-02-18
To explore a new method of whole-process digital esthetic prosthodontic rehabilitation combined with periodontic surgery for complicated anterior teeth esthetic defects accompanied by soft tissue morphology, to provide an alternative choice for solving this problem under the guidance of three-dimensional (3D) printing digital dental model and surgical guide, thus completing periodontic surgery and digital esthetic rehabilitation of anterior teeth. In this study, 12 patients with complicated esthetic problems accompanied by soft tissue morphology in their anterior teeth were included. The dentition and facial images were obtained by intra-oral scanning and three-dimensional (3D) facial scanning and then calibrated. Two esthetic designs and prosthodontic outcome predictions were created by computer aided design /computer aided manufacturing (CAD/CAM) software combined with digital photography, including consideration of white esthetics and comprehensive consideration of pink-white esthetics. The predictive design of prostheses and the facial appearances of the two designs were evaluated by the patients. If the patients chose the design of comprehensive consideration of pink-white esthetics, they would choose whether they would receive periodontic surgery before esthetic rehabilitation. The dentition design cast of those who chose periodontic surgery would be 3D printed for the guide of periodontic surgery accordingly. In light of the two digital designs based on intra-oral scanning, facing scanning and digital photography, the satisfaction rate of the patients was significantly higher for the comprehensive consideration of pink-white esthetic design (P<0.05) and more patients tended to choose priodontic surgery before esthetic rehabilitation. The 3D printed digital dental model and surgical guide provided significant instructions for periodontic surgery, and achieved success transfer from digital design to clinical application. The prostheses were fabricated by CAD/CAM, thus realizing the whole-process digital esthetic rehabilitation. The new method for esthetic rehabilitation of complicated anterior teeth esthetic defects accompanied by soft tissue morphology, including patient-involved digital esthetic analysis, design, esthetic outcome prediction, 3D printing surgical guide for periodontic surgery and digital fabrication is a practical technology. This method is useful for improvement of clinical communication efficiency between doctor-patient, doctor-technician and doctors from different departments, and is conducive to multidisciplinary treatment of this complicated anterior teeth esthetic problem.
Soft x-ray holographic tomography for biological specimens
NASA Astrophysics Data System (ADS)
Gao, Hongyi; Chen, Jianwen; Xie, Honglan; Li, Ruxin; Xu, Zhizhan; Jiang, Shiping; Zhang, Yuxuan
2003-10-01
In this paper, we present some experimental results on X -ray holography, holographic tomography, and a new holographic tomography method called pre-amplified holographic tomography is proposed. Due to the shorter wavelength and the larger penetration depths, X-rays provide the potential of higher resolution in imaging techniques, and have the ability to image intact, living, hydrated cells w ithout slicing, dehydration, chemical fixation or stain. Recently, using X-ray source in National Synchrotron Radiation Laboratory in Hefei, we have successfully performed some soft X-ray holography experiments on biological specimen. The specimens used in the experiments was the garlic clove epidermis, we got their X-ray hologram, and then reconstructed them by computer programs, the feature of the cell walls, the nuclei and some cytoplasm were clearly resolved. However, there still exist some problems in realization of practical 3D microscopic imaging due to the near-unity refractive index of the matter. There is no X-ray optics having a sufficient high numerical aperture to achieve a depth resolution that is comparable to the transverse resolution. On the other hand, computer tomography needs a record of hundreds of views of the test object at different angles for high resolution. This is because the number of views required for a densely packed object is equal to the object radius divided by the desired depth resolution. Clearly, it is impractical for a radiation-sensitive biological specimen. Moreover, the X-ray diffraction effect makes projection data blur, this badly degrades the resolution of the reconstructed image. In order to observe 3D structure of the biological specimens, McNulty proposed a new method for 3D imaging called "holographic tomography (HT)" in which several holograms of the specimen are recorded from various illumination directions and combined in the reconstruction step. This permits the specimens to be sampled over a wide range of spatial frequencies to improve the depth resolution. In NSRL, we performed soft X-ray holographic tomography experiments. The specimen was the spider filaments and PM M A as recording medium. By 3D CT reconstruction of the projection data, three dimensional density distribution of the specimen was obtained. Also, we developed a new X-ray holographic tomography m ethod called pre-amplified holographic tomography. The method permits a digital real-time 3D reconstruction with high-resolution and a simple and compact experimental setup as well.
NASA Astrophysics Data System (ADS)
Li, Guo-Yang; Zheng, Yang; Liu, Yanlin; Destrade, Michel; Cao, Yanping
2016-11-01
A body force concentrated at a point and moving at a high speed can induce shear-wave Mach cones in dusty-plasma crystals or soft materials, as observed experimentally and named the elastic Cherenkov effect (ECE). The ECE in soft materials forms the basis of the supersonic shear imaging (SSI) technique, an ultrasound-based dynamic elastography method applied in clinics in recent years. Previous studies on the ECE in soft materials have focused on isotropic material models. In this paper, we investigate the existence and key features of the ECE in anisotropic soft media, by using both theoretical analysis and finite element (FE) simulations, and we apply the results to the non-invasive and non-destructive characterization of biological soft tissues. We also theoretically study the characteristics of the shear waves induced in a deformed hyperelastic anisotropic soft material by a source moving with high speed, considering that contact between the ultrasound probe and the soft tissue may lead to finite deformation. On the basis of our theoretical analysis and numerical simulations, we propose an inverse approach to infer both the anisotropic and hyperelastic parameters of incompressible transversely isotropic (TI) soft materials. Finally, we investigate the properties of the solutions to the inverse problem by deriving the condition numbers in analytical form and performing numerical experiments. In Part II of the paper, both ex vivo and in vivo experiments are conducted to demonstrate the applicability of the inverse method in practical use.
Glass transition of soft colloids
NASA Astrophysics Data System (ADS)
Philippe, Adrian-Marie; Truzzolillo, Domenico; Galvan-Myoshi, Julian; Dieudonné-George, Philippe; Trappe, Véronique; Berthier, Ludovic; Cipelletti, Luca
2018-04-01
We explore the glassy dynamics of soft colloids using microgels and charged particles interacting by steric and screened Coulomb interactions, respectively. In the supercooled regime, the structural relaxation time τα of both systems grows steeply with volume fraction, reminiscent of the behavior of colloidal hard spheres. Computer simulations confirm that the growth of τα on approaching the glass transition is independent of particle softness. By contrast, softness becomes relevant at very large packing fractions when the system falls out of equilibrium. In this nonequilibrium regime, τα depends surprisingly weakly on packing fraction, and time correlation functions exhibit a compressed exponential decay consistent with stress-driven relaxation. The transition to this novel regime coincides with the onset of an anomalous decrease in local order with increasing density typical of ultrasoft systems. We propose that these peculiar dynamics results from the combination of the nonequilibrium aging dynamics expected in the glassy state and the tendency of colloids interacting through soft potentials to refluidize at high packing fractions.
ERIC Educational Resources Information Center
Okopi, Fidel Onjefu; Odeyemi, Olajumoke Janet; Adesina, Adewale
2015-01-01
The study has identified the areas of strengths and weaknesses in the current use of Computer Based Learning (CBL) tools in Open and Distance Learning (ODL) institutions in Nigeria. To achieve these objectives, the following research questions were proposed: (i) What are the computer-based learning tools (soft and hard ware) that are actually in…
Achieving Systemic Information Operations for Australian Defence
1999-10-01
is Checkland’s Soft Systems Methodology and some emphasis is placed on this methodology in the present document. Other soft methodologies also exist...Warfare 2 2 Proposed Development Method 5 3 Soft Systems Methodology 8 DSTO-TN-0235 DSTO-TN-0235 1 Introduction Widespread concern...that will be adopted will be one chosen from the burgeoning field of soft systems theory, for example Checkland’s Soft Systems Methodology (SSM)[8
Wang, Yue; Gregory, Cherry; Minor, Mark A
2018-06-01
Molded silicone rubbers are common in manufacturing of soft robotic parts, but they are often prone to tears, punctures, and tensile failures when strained. In this article, we present a fabric compositing method for improving the mechanical properties of soft robotic parts by creating a fabric/rubber composite that increases the strength and durability of the molded rubber. Comprehensive ASTM material tests evaluating the strength, tear resistance, and puncture resistance are conducted on multiple composites embedded with different fabrics, including polyester, nylon, silk, cotton, rayon, and several blended fabrics. Results show that strong fabrics increase the strength and durability of the composite, valuable in pneumatic soft robotic applications, while elastic fabrics maintain elasticity and enhance tear strength, suitable for robotic skins or soft strain sensors. Two case studies then validate the proposed benefits of the fabric compositing for soft robotic pressure vessel applications and soft strain sensor applications. Evaluations of the fabric/rubber composite samples and devices indicate that such methods are effective for improving mechanical properties of soft robotic parts, resulting in parts that can have customized stiffness, strength, and vastly improved durability.
Zhang, Xue; Xiao, Yang; Zeng, Jie; Qiu, Weibao; Qian, Ming; Wang, Congzhi; Zheng, Rongqin; Zheng, Hairong
2014-01-01
To develop and evaluate a computer-assisted method of quantifying five-point elasticity scoring system based on ultrasound real-time elastography (RTE), for classifying benign and malignant breast lesions, with pathologic results as the reference standard. Conventional ultrasonography (US) and RTE images of 145 breast lesions (67 malignant, 78 benign) were performed in this study. Each lesion was automatically contoured on the B-mode image by the level set method and mapped on the RTE image. The relative elasticity value of each pixel was reconstructed and classified into hard or soft by the fuzzy c-means clustering method. According to the hardness degree inside lesion and its surrounding tissue, the elasticity score of the RTE image was computed in an automatic way. Visual assessments of the radiologists were used for comparing the diagnostic performance. Histopathologic examination was used as the reference standard. The Student's t test and receiver operating characteristic (ROC) curve analysis were performed for statistical analysis. Considering score 4 or higher as test positive for malignancy, the diagnostic accuracy, sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) were 93.8% (136/145), 92.5% (62/67), 94.9% (74/78), 93.9% (62/66), and 93.7% (74/79) for the computer-assisted scheme, and 89.7% (130/145), 85.1% (57/67), 93.6% (73/78), 92.0% (57/62), and 88.0% (73/83) for manual assessment. Area under ROC curve (Az value) for the proposed method was higher than the Az value for visual assessment (0.96 vs. 0.93). Computer-assisted quantification of classical five-point scoring system can significantly eliminate the interobserver variability and thereby improve the diagnostic confidence of classifying the breast lesions to avoid unnecessary biopsy. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.
NASA Astrophysics Data System (ADS)
Zverev, V. V.; Izmozherov, I. M.; Filippov, B. N.
2018-02-01
Three-dimensional computer simulation of dynamic processes in a moving domain boundary separating domains in a soft magnetic uniaxial film with planar anisotropy is performed by numerical solution of Landau-Lifshitz-Gilbert equations. The developed visualization methods are used to establish the connection between the motion of surface vortices and antivortices, singular (Bloch) points, and core lines of intrafilm vortex structures. A relation between the character of magnetization dynamics and the film thickness is found. The analytical models of spatial vortex structures for imitation of topological properties of the structures observed in micromagnetic simulation are constructed.
Integration of Digital Dental Casts in Cone-Beam Computed Tomography Scans
Rangel, Frits A.; Maal, Thomas J. J.; Bergé, Stefaan J.; Kuijpers-Jagtman, Anne Marie
2012-01-01
Cone-beam computed tomography (CBCT) is widely used in maxillofacial surgery. The CBCT image of the dental arches, however, is of insufficient quality to use in digital planning of orthognathic surgery. Several authors have described methods to integrate digital dental casts into CBCT scans, but all reported methods have drawbacks. The aim of this feasibility study is to present a new simplified method to integrate digital dental casts into CBCT scans. In a patient scheduled for orthognathic surgery, titanium markers were glued to the gingiva. Next, a CBCT scan and dental impressions were made. During the impression-taking procedure, the titanium markers were transferred to the impression. The impressions were scanned, and all CBCT datasets were exported in DICOM format. The two datasets were matched, and the dentition derived from the scanned impressions was transferred to the CBCT of the patient. After matching the two datasets, the average distance between the corresponding markers was 0.1 mm. This novel method allows for the integration of digital dental casts into CBCT scans, overcoming problems such as unwanted extra radiation exposure, distortion of soft tissues due to the use of bite jigs, and time-consuming digital data handling. PMID:23050159
Revising the lower statistical limit of x-ray grating-based phase-contrast computed tomography.
Marschner, Mathias; Birnbacher, Lorenz; Willner, Marian; Chabior, Michael; Herzen, Julia; Noël, Peter B; Pfeiffer, Franz
2017-01-01
Phase-contrast x-ray computed tomography (PCCT) is currently investigated as an interesting extension of conventional CT, providing high soft-tissue contrast even if examining weakly absorbing specimen. Until now, the potential for dose reduction was thought to be limited compared to attenuation CT, since meaningful phase retrieval fails for scans with very low photon counts when using the conventional phase retrieval method via phase stepping. In this work, we examine the statistical behaviour of the reverse projection method, an alternative phase retrieval approach and compare the results to the conventional phase retrieval technique. We investigate the noise levels in the projections as well as the image quality and quantitative accuracy of the reconstructed tomographic volumes. The results of our study show that this method performs better in a low-dose scenario than the conventional phase retrieval approach, resulting in lower noise levels, enhanced image quality and more accurate quantitative values. Overall, we demonstrate that the lower statistical limit of the phase stepping procedure as proposed by recent literature does not apply to this alternative phase retrieval technique. However, further development is necessary to overcome experimental challenges posed by this method which would enable mainstream or even clinical application of PCCT.
Soft electron processor for surface sterilization of food material
NASA Astrophysics Data System (ADS)
Baba, Takashi; Kaneko, Hiromi; Taniguchi, Shuichi
2004-09-01
As frozen or chilled foods have become popular nowadays, it has become very important to provide raw materials with lower level microbial contamination to food processing companies. Consequently, the sterilization of food material is one of the major topics for food processing. Dried materials like grains, beans and spices, etc., are not typically deeply contaminated by microorganisms, which reside on the surfaces of materials, so it is very useful to take low energetic, lower than 300 keV, electrons with small penetration power (Soft-Electrons), as a sterilization method for such materials. Soft-Electrons is researched and named by Dr. Hayashi et al. This is a non-thermal method, so one can keep foods hygienic without serious deterioration. It is also a physical method, so is free from residues of chemicals in foods. Recently, Nissin-High Voltage Co., Ltd. have developed and manufactured equipment for commercial use of Soft-Electrons (Soft Electron Processor), which can process 500 kg/h of grains. This report introduces the Soft Electron Processor and shows the results of sterilization of wheat and brown rice by the equipment.
Soft Skills: An Important Asset Acquired from Organizing Regional Student Group Activities
de Ridder, Jeroen; Meysman, Pieter; Oluwagbemi, Olugbenga; Abeel, Thomas
2014-01-01
Contributing to a student organization, such as the International Society for Computational Biology Student Council (ISCB-SC) and its Regional Student Group (RSG) program, takes time and energy. Both are scarce commodities, especially when you are trying to find your place in the world of computational biology as a graduate student. It comes as no surprise that organizing ISCB-SC-related activities sometimes interferes with day-to-day research and shakes up your priority list. However, we unanimously agree that the rewards, both in the short as well as the long term, make the time spent on these extracurricular activities more than worth it. In this article, we will explain what makes this so worthwhile: soft skills. PMID:24992198
Soft skills: an important asset acquired from organizing regional student group activities.
de Ridder, Jeroen; Meysman, Pieter; Oluwagbemi, Olugbenga; Abeel, Thomas
2014-07-01
Contributing to a student organization, such as the International Society for Computational Biology Student Council (ISCB-SC) and its Regional Student Group (RSG) program, takes time and energy. Both are scarce commodities, especially when you are trying to find your place in the world of computational biology as a graduate student. It comes as no surprise that organizing ISCB-SC-related activities sometimes interferes with day-to-day research and shakes up your priority list. However, we unanimously agree that the rewards, both in the short as well as the long term, make the time spent on these extracurricular activities more than worth it. In this article, we will explain what makes this so worthwhile: soft skills.
A soft-contact model for computing safety margins in human prehension.
Singh, Tarkeshwar; Ambike, Satyajit
2017-10-01
The soft human digit tip forms contact with grasped objects over a finite area and applies a moment about an axis normal to the area. These moments are important for ensuring stability during precision grasping. However, the contribution of these moments to grasp stability is rarely investigated in prehension studies. The more popular hard-contact model assumes that the digits exert a force vector but no free moment on the grasped object. Many sensorimotor studies use this model and show that humans estimate friction coefficients to scale the normal force to grasp objects stably, i.e. the smoother the surface, the tighter the grasp. The difference between the applied normal force and the minimal normal force needed to prevent slipping is called safety margin and this index is widely used as a measure of grasp planning. Here, we define and quantify safety margin using a more realistic contact model that allows digits to apply both forces and moments. Specifically, we adapt a soft-contact model from robotics and demonstrate that the safety margin thus computed is a more accurate and robust index of grasp planning than its hard-contact variant. Previously, we have used the soft-contact model to propose two indices of grasp planning that show how humans account for the shape and inertial properties of an object. A soft-contact based safety margin offers complementary insights by quantifying how humans may account for surface properties of the object and skin tissue during grasp planning and execution. Copyright © 2017 Elsevier B.V. All rights reserved.
Image quality of mixed convolution kernel in thoracic computed tomography.
Neubauer, Jakob; Spira, Eva Maria; Strube, Juliane; Langer, Mathias; Voss, Christian; Kotter, Elmar
2016-11-01
The mixed convolution kernel alters his properties geographically according to the depicted organ structure, especially for the lung. Therefore, we compared the image quality of the mixed convolution kernel to standard soft and hard kernel reconstructions for different organ structures in thoracic computed tomography (CT) images.Our Ethics Committee approved this prospective study. In total, 31 patients who underwent contrast-enhanced thoracic CT studies were included after informed consent. Axial reconstructions were performed with hard, soft, and mixed convolution kernel. Three independent and blinded observers rated the image quality according to the European Guidelines for Quality Criteria of Thoracic CT for 13 organ structures. The observers rated the depiction of the structures in all reconstructions on a 5-point Likert scale. Statistical analysis was performed with the Friedman Test and post hoc analysis with the Wilcoxon rank-sum test.Compared to the soft convolution kernel, the mixed convolution kernel was rated with a higher image quality for lung parenchyma, segmental bronchi, and the border between the pleura and the thoracic wall (P < 0.03). Compared to the hard convolution kernel, the mixed convolution kernel was rated with a higher image quality for aorta, anterior mediastinal structures, paratracheal soft tissue, hilar lymph nodes, esophagus, pleuromediastinal border, large and medium sized pulmonary vessels and abdomen (P < 0.004) but a lower image quality for trachea, segmental bronchi, lung parenchyma, and skeleton (P < 0.001).The mixed convolution kernel cannot fully substitute the standard CT reconstructions. Hard and soft convolution kernel reconstructions still seem to be mandatory for thoracic CT.
Fiore, Andrew M; Swan, James W
2018-01-28
Brownian Dynamics simulations are an important tool for modeling the dynamics of soft matter. However, accurate and rapid computations of the hydrodynamic interactions between suspended, microscopic components in a soft material are a significant computational challenge. Here, we present a new method for Brownian dynamics simulations of suspended colloidal scale particles such as colloids, polymers, surfactants, and proteins subject to a particular and important class of hydrodynamic constraints. The total computational cost of the algorithm is practically linear with the number of particles modeled and can be further optimized when the characteristic mass fractal dimension of the suspended particles is known. Specifically, we consider the so-called "stresslet" constraint for which suspended particles resist local deformation. This acts to produce a symmetric force dipole in the fluid and imparts rigidity to the particles. The presented method is an extension of the recently reported positively split formulation for Ewald summation of the Rotne-Prager-Yamakawa mobility tensor to higher order terms in the hydrodynamic scattering series accounting for force dipoles [A. M. Fiore et al., J. Chem. Phys. 146(12), 124116 (2017)]. The hydrodynamic mobility tensor, which is proportional to the covariance of particle Brownian displacements, is constructed as an Ewald sum in a novel way which guarantees that the real-space and wave-space contributions to the sum are independently symmetric and positive-definite for all possible particle configurations. This property of the Ewald sum is leveraged to rapidly sample the Brownian displacements from a superposition of statistically independent processes with the wave-space and real-space contributions as respective covariances. The cost of computing the Brownian displacements in this way is comparable to the cost of computing the deterministic displacements. The addition of a stresslet constraint to the over-damped particle equations of motion leads to a stochastic differential algebraic equation (SDAE) of index 1, which is integrated forward in time using a mid-point integration scheme that implicitly produces stochastic displacements consistent with the fluctuation-dissipation theorem for the constrained system. Calculations for hard sphere dispersions are illustrated and used to explore the performance of the algorithm. An open source, high-performance implementation on graphics processing units capable of dynamic simulations of millions of particles and integrated with the software package HOOMD-blue is used for benchmarking and made freely available in the supplementary material.
O'Connor, P J; Davies, A G; Fowler, R C; Lintott, D J; Bury, R F; Parkin, G J; Martinez, D; Saifuddin, A; Cowen, A R
1998-04-01
To assess diagnostic performance and reader preference when reporting results from digital hard-copy and two soft-copy formats of skeletal digital radiography. The data comprised hand radiographs of patients undergoing renal dialysis. Normal hand radiographs obtained in trauma patients were assessed as control images. One hundred fifteen images acquired with a photostimulable-phosphor computed radiography system were analyzed. Image selection and initial assessment were by consensus of two experienced radiologists, who graded the radiographic changes of hyperparathyroidism with the Ritz scoring system. The images were then presented to four readers in three formats: hard-copy output and soft-copy presentations at 2K2 and 1K2 resolutions. These readers scored pathologic change and image preference. The results were analyzed with the receiver operating characteristic technique. There was a significant improvement in diagnostic performance for both soft-copy formats relative to the hard-copy format (P < .001). No significant difference in diagnostic performance was found between the two soft-copy formats. There was a significant preference for both soft-copy formats relative to the hard-copy format (P < .01), with the 2K2 soft-copy images preferred to the 1K2 images (P < .01). Soft-copy reporting can provide superior diagnostic performance even for images viewed at a modest (1K2) resolution. The lack of difference between the two soft-copy formats has important economic implications with respect to departmental hardware requirements.
Sawall, Mathias; Kubis, Christoph; Börner, Armin; Selent, Detlef; Neymeyr, Klaus
2015-09-03
Modern computerized spectroscopic instrumentation can result in high volumes of spectroscopic data. Such accurate measurements rise special computational challenges for multivariate curve resolution techniques since pure component factorizations are often solved via constrained minimization problems. The computational costs for these calculations rapidly grow with an increased time or frequency resolution of the spectral measurements. The key idea of this paper is to define for the given high-dimensional spectroscopic data a sequence of coarsened subproblems with reduced resolutions. The multiresolution algorithm first computes a pure component factorization for the coarsest problem with the lowest resolution. Then the factorization results are used as initial values for the next problem with a higher resolution. Good initial values result in a fast solution on the next refined level. This procedure is repeated and finally a factorization is determined for the highest level of resolution. The described multiresolution approach allows a considerable convergence acceleration. The computational procedure is analyzed and is tested for experimental spectroscopic data from the rhodium-catalyzed hydroformylation together with various soft and hard models. Copyright © 2015 Elsevier B.V. All rights reserved.
Yang, Yi; Tang, Xiangyang
2014-10-01
Under the existing theoretical framework of x-ray phase contrast imaging methods implemented with Talbot interferometry, the dark-field contrast refers to the reduction in interference fringe visibility due to small-angle x-ray scattering of the subpixel microstructures of an object to be imaged. This study investigates how an object's subpixel microstructures can also affect the phase of the intensity oscillations. Instead of assuming that the object's subpixel microstructures distribute in space randomly, the authors' theoretical derivation starts by assuming that an object's attenuation projection and phase shift vary at a characteristic size that is not smaller than the period of analyzer grating G₂ and a characteristic length dc. Based on the paraxial Fresnel-Kirchhoff theory, the analytic formulae to characterize the zeroth- and first-order Fourier coefficients of the x-ray irradiance recorded at each detector cell are derived. Then the concept of complex dark-field contrast is introduced to quantify the influence of the object's microstructures on both the interference fringe visibility and the phase of intensity oscillations. A method based on the phase-attenuation duality that holds for soft tissues and high x-ray energies is proposed to retrieve the imaginary part of the complex dark-field contrast for imaging. Through computer simulation study with a specially designed numerical phantom, they evaluate and validate the derived analytic formulae and the proposed retrieval method. Both theoretical analysis and computer simulation study show that the effect of an object's subpixel microstructures on x-ray phase contrast imaging method implemented with Talbot interferometry can be fully characterized by a complex dark-field contrast. The imaginary part of complex dark-field contrast quantifies the influence of the object's subpixel microstructures on the phase of intensity oscillations. Furthermore, at relatively high energies, for soft tissues it can be retrieved for imaging with a method based on the phase-attenuation duality. The analytic formulae derived in this work to characterize the complex dark-field contrast in x-ray phase contrast imaging method implemented with Talbot interferometry are of significance, which may initiate more activities in the research and development of x-ray differential phase contrast imaging for extensive biomedical applications.
Drees, R.; Forrest, L. J.; Chappell, R.
2009-01-01
Objectives Canine intranasal neoplasia is commonly evaluated using computed tomography to indicate the diagnosis, to determine disease extent, to guide histological sampling location and to plan treatment. With the expanding use of magnetic resonance imaging in veterinary medicine, this modality has been recently applied for the same purpose. The aim of this study was to compare the features of canine intranasal neoplasia using computed tomography and magnetic resonance imaging. Methods Twenty-one dogs with confirmed intranasal neoplasia underwent both computed tomography and magnetic resonance imaging. The images were reviewed retrospectively for the bony and soft tissue features of intranasal neoplasia. Results Overall computed tomography and magnetic resonance imaging performed very similarly. However, lysis of bones bordering the nasal cavity and mucosal thickening was found on computed tomography images more often than on magnetic resonance images. Small amounts of fluid in the nasal cavity were more often seen on magnetic resonance images. However, fluid in the frontal sinuses was seen equally well with both modalities. Clinical Significance We conclude that computed tomography is satisfactory for evaluation of canine intranasal neoplasia, and no clinically relevant benefit is gained using magnetic resonance imaging for intranasal neoplasia without extent into the cranial cavity. PMID:19508490
Martins, Luciana Flaquer; Vigorito, Julio Wilson
2013-01-01
To determine the characteristics of facial soft tissues at rest and wide smile, and their possible relation to the facial type. We analyzed a sample of forty-eight young female adults, aged between 19.10 and 40 years old, with a mean age of 30.9 years, who had balanced profile and passive lip seal. Cone beam computed tomographies were performed at rest and wide smile postures on the entire sample which was divided into three groups according to individual facial types. Soft tissue features analysis of the lips, nose, zygoma and chin were done in sagittal, axial and frontal axis tomographic views. No differences were observed in any of the facial type variables for the static analysis of facial structures at both rest and wide smile postures. Dynamic analysis showed that brachifacial types are more sensitive to movement, presenting greater sagittal lip contraction. However, the lip movement produced by this type of face results in a narrow smile, with smaller tooth exposure area when compared with other facial types. Findings pointed out that the position of the upper lip should be ahead of the lower lip, and the latter, ahead of the pogonion. It was also found that the facial type does not impact the positioning of these structures. Additionally, the use of cone beam computed tomography may be a valuable method to study craniofacial features.
NASA Astrophysics Data System (ADS)
Fotin, Sergei V.; Yin, Yin; Haldankar, Hrishikesh; Hoffmeister, Jeffrey W.; Periaswamy, Senthil
2016-03-01
Computer-aided detection (CAD) has been used in screening mammography for many years and is likely to be utilized for digital breast tomosynthesis (DBT). Higher detection performance is desirable as it may have an impact on radiologist's decisions and clinical outcomes. Recently the algorithms based on deep convolutional architectures have been shown to achieve state of the art performance in object classification and detection. Similarly, we trained a deep convolutional neural network directly on patches sampled from two-dimensional mammography and reconstructed DBT volumes and compared its performance to a conventional CAD algorithm that is based on computation and classification of hand-engineered features. The detection performance was evaluated on the independent test set of 344 DBT reconstructions (GE SenoClaire 3D, iterative reconstruction algorithm) containing 328 suspicious and 115 malignant soft tissue densities including masses and architectural distortions. Detection sensitivity was measured on a region of interest (ROI) basis at the rate of five detection marks per volume. Moving from conventional to deep learning approach resulted in increase of ROI sensitivity from 0:832 +/- 0:040 to 0:893 +/- 0:033 for suspicious ROIs; and from 0:852 +/- 0:065 to 0:930 +/- 0:046 for malignant ROIs. These results indicate the high utility of deep feature learning in the analysis of DBT data and high potential of the method for broader medical image analysis tasks.
Soft Decision Analyzer and Method
NASA Technical Reports Server (NTRS)
Zucha, Joan P. (Inventor); Schlesinger, Adam M. (Inventor); Lansdowne, Chatwin (Inventor); Steele, Glen F. (Inventor)
2015-01-01
A soft decision analyzer system is operable to interconnect soft decision communication equipment and analyze the operation thereof to detect symbol wise alignment between a test data stream and a reference data stream in a variety of operating conditions.
Soft Decision Analyzer and Method
NASA Technical Reports Server (NTRS)
Zucha, Joan P. (Inventor); Schlesinger, Adam M. (Inventor); Lansdowne, Chatwin (Inventor); Steele, Glen F. (Inventor)
2016-01-01
A soft decision analyzer system is operable to interconnect soft decision communication equipment and analyze the operation thereof to detect symbol wise alignment between a test data stream and a reference data stream in a variety of operating conditions.
Sonnante, Gabriella; Montemurro, Cinzia; Morgese, Anita; Sabetta, Wilma; Blanco, Antonio; Pasqualone, Antonella
2009-11-11
Italian industrial pasta and durum wheat typical breads must be prepared using exclusively durum wheat semolina. Previously, a microsatellite sequence specific of the wheat D-genome had been chosen for traceability of soft wheat in semolina and bread samples, using qualitative and quantitative Sybr green-based real-time experiments. In this work, we describe an improved method based on the same soft wheat genomic region by means of a quantitative real-time PCR using a dual-labeled probe. Standard curves based on dilutions of 100% soft wheat flour, pasta, or bread were constructed. Durum wheat semolina, pasta, and bread samples were prepared with increasing amounts of soft wheat to verify the accuracy of the method. Results show that reliable quantifications were obtained especially for the samples containing a lower amount of soft wheat DNA, fulfilling the need to verify labeling of pasta and typical durum wheat breads.
Determination of synthetic food dyes in commercial soft drinks by TLC and ion-pair HPLC.
de Andrade, Francisca Ivani; Florindo Guedes, Maria Izabel; Pinto Vieira, Ícaro Gusmão; Pereira Mendes, Francisca Noélia; Salmito Rodrigues, Paula Alves; Costa Maia, Carla Soraya; Marques Ávila, Maria Marlene; de Matos Ribeiro, Luzara
2014-08-15
Synthetic food colourings were analyzed on commercial carbonated orange and grape soft drinks produced in Ceará State, Brazil. Tartrazine (E102), Amaranth (E123), Sunset Yellow (E110) and Brilliant Blue (E133) were extracted from soft drinks using C18 SPE and identified by thin layer chromatography (TLC), this method was used to confirm the composition of food colouring in soft drinks stated on label. The concentration of food colouring in soft drink was determined by ion-pair high performance liquid chromatography with photodiode array detection. The results obtained with the samples confirm that the identification and quantification methods are recommended for quality control of the synthetic colours in soft drinks, as well as to determine whether the levels and lables complies with the recommendations of food dyes legislation. Copyright © 2014 Elsevier Ltd. All rights reserved.
Zheng, Jieru; Kang, Youn K; Therien, Michael J; Beratan, David N
2005-08-17
Donor-acceptor interactions were investigated in a series of unusually rigid, cofacially compressed pi-stacked porphyrin-bridge-quinone systems. The two-state generalized Mulliken-Hush (GMH) approach was used to compute the coupling matrix elements. The theoretical coupling values evaluated with the GMH method were obtained from configuration interaction calculations using the INDO/S method. The results of this analysis are consistent with the comparatively soft distance dependences observed for both the charge separation and charge recombination reactions. Theoretical studies of model structures indicate that the phenyl units dominate the mediation of the donor-acceptor coupling and that the relatively weak exponential decay of rate with distance arises from the compression of this pi-electron stack.
Wearable Intrinsically Soft, Stretchable, Flexible Devices for Memories and Computing.
Rajan, Krishna; Garofalo, Erik; Chiolerio, Alessandro
2018-01-27
A recent trend in the development of high mass consumption electron devices is towards electronic textiles (e-textiles), smart wearable devices, smart clothes, and flexible or printable electronics. Intrinsically soft, stretchable, flexible, Wearable Memories and Computing devices (WMCs) bring us closer to sci-fi scenarios, where future electronic systems are totally integrated in our everyday outfits and help us in achieving a higher comfort level, interacting for us with other digital devices such as smartphones and domotics, or with analog devices, such as our brain/peripheral nervous system. WMC will enable each of us to contribute to open and big data systems as individual nodes, providing real-time information about physical and environmental parameters (including air pollution monitoring, sound and light pollution, chemical or radioactive fallout alert, network availability, and so on). Furthermore, WMC could be directly connected to human brain and enable extremely fast operation and unprecedented interface complexity, directly mapping the continuous states available to biological systems. This review focuses on recent advances in nanotechnology and materials science and pays particular attention to any result and promising technology to enable intrinsically soft, stretchable, flexible WMC.
An Efficient Soft Set-Based Approach for Conflict Analysis
Sutoyo, Edi; Mungad, Mungad; Hamid, Suraya; Herawan, Tutut
2016-01-01
Conflict analysis has been used as an important tool in economic, business, governmental and political dispute, games, management negotiations, military operations and etc. There are many mathematical formal models have been proposed to handle conflict situations and one of the most popular is rough set theory. With the ability to handle vagueness from the conflict data set, rough set theory has been successfully used. However, computational time is still an issue when determining the certainty, coverage, and strength of conflict situations. In this paper, we present an alternative approach to handle conflict situations, based on some ideas using soft set theory. The novelty of the proposed approach is that, unlike in rough set theory that uses decision rules, it is based on the concept of co-occurrence of parameters in soft set theory. We illustrate the proposed approach by means of a tutorial example of voting analysis in conflict situations. Furthermore, we elaborate the proposed approach on real world dataset of political conflict in Indonesian Parliament. We show that, the proposed approach achieves lower computational time as compared to rough set theory of up to 3.9%. PMID:26928627
An Efficient Soft Set-Based Approach for Conflict Analysis.
Sutoyo, Edi; Mungad, Mungad; Hamid, Suraya; Herawan, Tutut
2016-01-01
Conflict analysis has been used as an important tool in economic, business, governmental and political dispute, games, management negotiations, military operations and etc. There are many mathematical formal models have been proposed to handle conflict situations and one of the most popular is rough set theory. With the ability to handle vagueness from the conflict data set, rough set theory has been successfully used. However, computational time is still an issue when determining the certainty, coverage, and strength of conflict situations. In this paper, we present an alternative approach to handle conflict situations, based on some ideas using soft set theory. The novelty of the proposed approach is that, unlike in rough set theory that uses decision rules, it is based on the concept of co-occurrence of parameters in soft set theory. We illustrate the proposed approach by means of a tutorial example of voting analysis in conflict situations. Furthermore, we elaborate the proposed approach on real world dataset of political conflict in Indonesian Parliament. We show that, the proposed approach achieves lower computational time as compared to rough set theory of up to 3.9%.
Wearable Intrinsically Soft, Stretchable, Flexible Devices for Memories and Computing
Rajan, Krishna; Garofalo, Erik
2018-01-01
A recent trend in the development of high mass consumption electron devices is towards electronic textiles (e-textiles), smart wearable devices, smart clothes, and flexible or printable electronics. Intrinsically soft, stretchable, flexible, Wearable Memories and Computing devices (WMCs) bring us closer to sci-fi scenarios, where future electronic systems are totally integrated in our everyday outfits and help us in achieving a higher comfort level, interacting for us with other digital devices such as smartphones and domotics, or with analog devices, such as our brain/peripheral nervous system. WMC will enable each of us to contribute to open and big data systems as individual nodes, providing real-time information about physical and environmental parameters (including air pollution monitoring, sound and light pollution, chemical or radioactive fallout alert, network availability, and so on). Furthermore, WMC could be directly connected to human brain and enable extremely fast operation and unprecedented interface complexity, directly mapping the continuous states available to biological systems. This review focuses on recent advances in nanotechnology and materials science and pays particular attention to any result and promising technology to enable intrinsically soft, stretchable, flexible WMC. PMID:29382050
NASA Astrophysics Data System (ADS)
Park, Harold
2016-04-01
Dielectric elastomers are a class of soft, active materials that have recently gained significant interest due to the fact that they can be electrostatically actuated into undergoing extremely large deformations. An ongoing challenge has been the development of robust and accurate computational models for elastomers, particularly those that can capture electromechanical instabilities that limit the performance of elastomers such as creasing, wrinkling, and snap-through. I discuss in this work a recently developed finite element model for elastomers that is dynamic, nonlinear, and fully electromechanically coupled. The model also significantly alleviates volumetric locking due that arises due to the incompressible nature of the elastomers, and incorporates viscoelasticity within a finite deformation framework. Numerical examples are shown that demonstrate the performance of the proposed method in capturing electromechanical instabilities (snap-through, creasing, cratering, wrinkling) that have been observed experimentally.
Quantitative morphology in canine cutaneous soft tissue sarcomas.
Simeonov, R; Ananiev, J; Gulubova, M
2015-12-01
Stained cytological specimens from 24 dogs with spontaneous soft tissue sarcomas [fibrosarcoma (n = 8), liposarcoma (n = 8) and haemangiopericytoma (n = 8)], and 24 dogs with reactive connective tissue lesions [granulation tissue (n = 12) and dermal fibrosis (n = 12)] were analysed by computer-assisted nuclear morphometry. The studied morphometric parameters were: mean nuclear area (MNA; µm(2)), mean nuclear perimeter (MNP; µm), mean nuclear diameter (MND mean; µm), minimum nuclear diameter (Dmin; µm) and maximum nuclear diameter (Dmax; µm). The study aimed to evaluate (1) possibility for quantitative differentiation of soft tissue sarcomas from reactive connective tissue lesions and (2) by using cytomorphometry, to differentiate the various histopathological soft tissue sarcomas subtypes in dogs. The mean values of all nuclear cytomorphometric parameters (except for Dmax) were statistically significantly higher in reactive connective tissue processes than in soft tissue sarcomas. At the same time, however, there were no considerable differences among the different sarcoma subtypes. The results demonstrated that the quantitative differentiation of reactive connective tissue processes from soft tissue sarcomas in dogs is possible, but the same was not true for the different canine soft tissue sarcoma subtypes. Further investigations on this topic are necessary for thorough explication of the role of quantitative morphology in the diagnostics of mesenchymal neoplasms and tumour-like fibrous lesions in dogs. © 2014 John Wiley & Sons Ltd.
Neurological soft signs discriminate schizophrenia from bipolar disorder.
Rigucci, Silvia; Dimitri-Valente, Giorgia; Mandarelli, Gabriele; Manfredi, Giovanni; Comparelli, Anna; De Filippis, Sergio; Gherardelli, Simona; Bersani, Giuseppe; Girardi, Paolo; Ferracuti, Stefano
2014-03-01
Although neurological soft signs have been consistently described in patients with schizophrenia, their diagnostic specificity is not well clarified. To test the hypothesis that neurological soft signs are specifically related to schizophrenia, we examined 305 subjects (patients with schizophrenia-spectrum disorder, n=167; patients with bipolar I disorder, n=88; controls, n=50). Neurological soft signs were assessed using the Neurological Evaluation Scale (NES). Multiple logistic regression analysis was used to compute the diagnostic predictive power of neurological soft signs. Patients in the schizophrenia-spectrum disorder group were found to have significantly greater neurological impairment (NES total score=23.9, standard deviation [SD] 11.2) than those in the bipolar disorder group (NES total score=18.2, SD 7.6; p<0.001). Neurological functioning was closely associated with psychopathology (all p<0.001). The NES total score reliably distinguished patients with schizophrenia spectrum disorders from those with bipolar disorder in 68.7% of the cases (p<0.001). Moreover, a particular set of neurological soft signs showed specificity for the schizophrenia-spectrum disorder diagnostic group. Our findings suggest that schizophrenia and bipolar disorder can be distinguished in terms of neurological impairment. Furthermore, we recommend the utility of neurological soft signs as a useful, quantifiable, sensitive, and inexpensive tool for the diagnostic work-up of schizophrenia.
Molecular dynamics simulations in hybrid particle-continuum schemes: Pitfalls and caveats
NASA Astrophysics Data System (ADS)
Stalter, S.; Yelash, L.; Emamy, N.; Statt, A.; Hanke, M.; Lukáčová-Medvid'ová, M.; Virnau, P.
2018-03-01
Heterogeneous multiscale methods (HMM) combine molecular accuracy of particle-based simulations with the computational efficiency of continuum descriptions to model flow in soft matter liquids. In these schemes, molecular simulations typically pose a computational bottleneck, which we investigate in detail in this study. We find that it is preferable to simulate many small systems as opposed to a few large systems, and that a choice of a simple isokinetic thermostat is typically sufficient while thermostats such as Lowe-Andersen allow for simulations at elevated viscosity. We discuss suitable choices for time steps and finite-size effects which arise in the limit of very small simulation boxes. We also argue that if colloidal systems are considered as opposed to atomistic systems, the gap between microscopic and macroscopic simulations regarding time and length scales is significantly smaller. We propose a novel reduced-order technique for the coupling to the macroscopic solver, which allows us to approximate a non-linear stress-strain relation efficiently and thus further reduce computational effort of microscopic simulations.
A Framework for Debugging Geoscience Projects in a High Performance Computing Environment
NASA Astrophysics Data System (ADS)
Baxter, C.; Matott, L.
2012-12-01
High performance computing (HPC) infrastructure has become ubiquitous in today's world with the emergence of commercial cloud computing and academic supercomputing centers. Teams of geoscientists, hydrologists and engineers can take advantage of this infrastructure to undertake large research projects - for example, linking one or more site-specific environmental models with soft computing algorithms, such as heuristic global search procedures, to perform parameter estimation and predictive uncertainty analysis, and/or design least-cost remediation systems. However, the size, complexity and distributed nature of these projects can make identifying failures in the associated numerical experiments using conventional ad-hoc approaches both time- consuming and ineffective. To address these problems a multi-tiered debugging framework has been developed. The framework allows for quickly isolating and remedying a number of potential experimental failures, including: failures in the HPC scheduler; bugs in the soft computing code; bugs in the modeling code; and permissions and access control errors. The utility of the framework is demonstrated via application to a series of over 200,000 numerical experiments involving a suite of 5 heuristic global search algorithms and 15 mathematical test functions serving as cheap analogues for the simulation-based optimization of pump-and-treat subsurface remediation systems.
Iliac screw fixation using computer-assisted computer tomographic image guidance: technical note.
Shin, John H; Hoh, Daniel J; Kalfas, Iain H
2012-03-01
Iliac screw fixation is a powerful tool used by spine surgeons to achieve fusion across the lumbosacral junction for a number of indications, including deformity, tumor, and pseudarthrosis. Complications associated with screw placement are related to blind trajectory selection and excessive soft tissue dissection. To describe the technique of iliac screw fixation using computed tomographic (CT)-based image guidance. Intraoperative registration and verification of anatomic landmarks are performed with the use of a preoperatively acquired CT of the lumbosacral spine. With the navigation probe, the ideal starting point for screw placement is selected while visualizing the intended trajectory and target on a computer screen. Once the starting point is selected and marked with a burr, a drill guide is docked within this point and the navigation probe re-inserted, confirming the trajectory. The probe is then removed and the high-speed drill reinserted within the drill guide. Drilling is performed to a depth measured on the computer screen and a screw is placed. Confirmation of accurate placement of iliac screws can be performed with standard radiographs. CT-guided navigation allows for 3-dimensional visualization of the pelvis and minimizes complications associated with soft-tissue dissection and breach of the ilium during screw placement.
Campus-Wide Computing: Early Results Using Legion at the University of Virginia
2006-01-01
Bernard et al., “Primitives for Distributed Computing in a Heterogeneous Local Area Network Environ- ment”, IEEE Trans on Soft. Eng. vol. 15, no. 12...1994. [16] F. Ferstl, “CODINE Technical Overview,” Genias, April, 1993. [17] R. F. Freund and D. S. Cornwell , “Superconcurrency: A form of distributed
DOE Office of Scientific and Technical Information (OSTI.GOV)
Nudelfuden, A.; Solanki, R.; Moos, H.W.
1985-03-15
Soft x-ray (20--304--A) astigmatic line shapes were measured in order to evaluate the spatial imaging properties of a Rowland mounted concave grating in grazing incidence. The practicability of coarse 1-D spatial imaging in the soft x-ray region is demonstrated. Spatial resolution equivalent to approx.4 cm at a source distance of 2 m can be achieved with practical parameters (e.g., sensitivity and time resolution) for a fusion diagnostic spectrograph. The results are compared to computer-generated ray tracings and found to be in good agreement. The ray tracing program which models the grazing incidence optics is discussed.
A case of hemangiopericytoma of the soft palate with articulate disorder and dysphagia
Michi, Yasuyuki; Suzuki, Miho; Kurohara, Kazuto; Harada, Kiyoshi
2013-01-01
We report a case of hemangiopericytoma of the soft palate of 60-year-old patient, who noticed a mass of the soft palate and experienced difficulty in speaking. We found a pediculate, hard, elastic mass measuring 38 mm (cross-sectional diameter). Computed tomography (CT) scans and dynamic magnetic resonance imaging (MRI) confirmed irregularly shaped mass and revealed a heterogeneous internal composition, consistent with vascular tumors. We excised the tumor under general anesthesia. Histopathological diagnosis was based on positive immunoreactivity of CD99 and vimentin and weak, positive staining of CD34. Three and half years following tumor excision, there is no recurrence or metastasis. PMID:23703709
Scalable fabric tactile sensor arrays for soft bodies
NASA Astrophysics Data System (ADS)
Day, Nathan; Penaloza, Jimmy; Santos, Veronica J.; Killpack, Marc D.
2018-06-01
Soft robots have the potential to transform the way robots interact with their environment. This is due to their low inertia and inherent ability to more safely interact with the world without damaging themselves or the people around them. However, existing sensing for soft robots has at least partially limited their ability to control interactions with their environment. Tactile sensors could enable soft robots to sense interaction, but most tactile sensors are made from rigid substrates and are not well suited to applications for soft robots which can deform. In addition, the benefit of being able to cheaply manufacture soft robots may be lost if the tactile sensors that cover them are expensive and their resolution does not scale well for manufacturability. This paper discusses the development of a method to make affordable, high-resolution, tactile sensor arrays (manufactured in rows and columns) that can be used for sensorizing soft robots and other soft bodies. However, the construction results in a sensor array that exhibits significant amounts of cross-talk when two taxels in the same row are compressed. Using the same fabric-based tactile sensor array construction design, two different methods for cross-talk compensation are presented. The first uses a mathematical model to calculate a change in resistance of each taxel directly. The second method introduces additional simple circuit components that enable us to isolate each taxel electrically and relate voltage to force directly. Fabric sensor arrays are demonstrated for two different soft-bodied applications: an inflatable single link robot and a human wrist.
Moore, Stephanie N; Hawley, Gregory D; Smith, Emily N; Mignemi, Nicholas A; Ihejirika, Rivka C; Yuasa, Masato; Cates, Justin M M; Liu, Xulei; Schoenecker, Jonathan G
2016-01-01
Soft tissue calcification, including both dystrophic calcification and heterotopic ossification, may occur following injury. These lesions have variable fates as they are either resorbed or persist. Persistent soft tissue calcification may result in chronic inflammation and/or loss of function of that soft tissue. The molecular mechanisms that result in the development and maturation of calcifications are uncertain. As a result, directed therapies that prevent or resorb soft tissue calcifications remain largely unsuccessful. Animal models of post-traumatic soft tissue calcification that allow for cost-effective, serial analysis of an individual animal over time are necessary to derive and test novel therapies. We have determined that a cardiotoxin-induced injury of the muscles in the posterior compartment of the lower extremity represents a useful model in which soft tissue calcification develops remote from adjacent bones, thereby allowing for serial analysis by plain radiography. The purpose of the study was to design and validate a method for quantifying soft tissue calcifications in mice longitudinally using plain radiographic techniques and an ordinal scoring system. Muscle injury was induced by injecting cardiotoxin into the posterior compartment of the lower extremity in mice susceptible to developing soft tissue calcification. Seven days following injury, radiographs were obtained under anesthesia. Multiple researchers applied methods designed to standardize post-image processing of digital radiographs (N = 4) and quantify soft tissue calcification (N = 6) in these images using an ordinal scoring system. Inter- and intra-observer agreement for both post-image processing and the scoring system used was assessed using weighted kappa statistics. Soft tissue calcification quantifications by the ordinal scale were compared to mineral volume measurements (threshold 450.7mgHA/cm3) determined by μCT. Finally, sample-size calculations necessary to discriminate between a 25%, 50%, 75%, and 100% difference in STiCSS score 7 days following burn/CTX induced muscle injury were determined. Precision analysis demonstrated substantial to good agreement for both post-image processing (κ = 0.73 to 0.90) and scoring (κ = 0.88 to 0.93), with low inter- and intra-observer variability. Additionally, there was a strong correlation in quantification of soft tissue calcification between the ordinal system and by mineral volume quantification by μCT (Spearman r = 0.83 to 0.89). The ordinal scoring system reliably quantified soft tissue calcification in a burn/CTX-induced soft tissue calcification model compared to non-injured controls (Mann-Whitney rank test: P = 0.0002, ***). Sample size calculations revealed that 6 mice per group would be required to detect a 50% difference in STiCSS score with a power of 0.8. Finally, the STiCSS was demonstrated to reliably quantify soft tissue calcification [dystrophic calcification and heterotopic ossification] by radiographic analysis, independent of the histopathological state of the mineralization. Radiographic analysis can discriminate muscle injury-induced soft tissue calcification from adjacent bone and follow its clinical course over time without requiring the sacrifice of the animal. While the STiCSS cannot identify the specific type of soft tissue calcification present, it is still a useful and valid method by which to quantify the degree of soft tissue calcification. This methodology allows for longitudinal measurements of soft tissue calcification in a single animal, which is relatively less expensive, less time-consuming, and exposes the animal to less radiation than in vivo μCT. Therefore, this high-throughput, longitudinal analytic method for quantifying soft tissue calcification is a viable alternative for the study of soft tissue calcification.
eXascale PRogramming Environment and System Software (XPRESS)
DOE Office of Scientific and Technical Information (OSTI.GOV)
Chapman, Barbara; Gabriel, Edgar
Exascale systems, with a thousand times the compute capacity of today’s leading edge petascale computers, are expected to emerge during the next decade. Their software systems will need to facilitate the exploitation of exceptional amounts of concurrency in applications, and ensure that jobs continue to run despite the occurrence of system failures and other kinds of hard and soft errors. Adapting computations at runtime to cope with changes in the execution environment, as well as to improve power and performance characteristics, is likely to become the norm. As a result, considerable innovation is required to develop system support to meetmore » the needs of future computing platforms. The XPRESS project aims to develop and prototype a revolutionary software system for extreme-scale computing for both exascale and strongscaled problems. The XPRESS collaborative research project will advance the state-of-the-art in high performance computing and enable exascale computing for current and future DOE mission-critical applications and supporting systems. The goals of the XPRESS research project are to: A. enable exascale performance capability for DOE applications, both current and future, B. develop and deliver a practical computing system software X-stack, OpenX, for future practical DOE exascale computing systems, and C. provide programming methods and environments for effective means of expressing application and system software for portable exascale system execution.« less
Kalman Filtering with Inequality Constraints for Turbofan Engine Health Estimation
NASA Technical Reports Server (NTRS)
Simon, Dan; Simon, Donald L.
2003-01-01
Kalman filters are often used to estimate the state variables of a dynamic system. However, in the application of Kalman filters some known signal information is often either ignored or dealt with heuristically. For instance, state variable constraints (which may be based on physical considerations) are often neglected because they do not fit easily into the structure of the Kalman filter. This paper develops two analytic methods of incorporating state variable inequality constraints in the Kalman filter. The first method is a general technique of using hard constraints to enforce inequalities on the state variable estimates. The resultant filter is a combination of a standard Kalman filter and a quadratic programming problem. The second method uses soft constraints to estimate state variables that are known to vary slowly with time. (Soft constraints are constraints that are required to be approximately satisfied rather than exactly satisfied.) The incorporation of state variable constraints increases the computational effort of the filter but significantly improves its estimation accuracy. The improvement is proven theoretically and shown via simulation results. The use of the algorithm is demonstrated on a linearized simulation of a turbofan engine to estimate health parameters. The turbofan engine model contains 16 state variables, 12 measurements, and 8 component health parameters. It is shown that the new algorithms provide improved performance in this example over unconstrained Kalman filtering.
Bartlett, Michael D; Fassler, Andrew; Kazem, Navid; Markvicka, Eric J; Mandal, Pratiti; Majidi, Carmel
2016-05-01
An all-soft-matter composite consisting of liquid metal microdroplets embedded in a soft elastomer matrix is presented by C. Majidi and co-workers on page 3726. This composite exhibits a high dielectric constant while maintaining exceptional elasticity and compliance. The image shows the composite's microstructure captured by 3D X-ray imaging using a nano-computed tomographic scanner. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
Controlled wavelet domain sparsity for x-ray tomography
NASA Astrophysics Data System (ADS)
Purisha, Zenith; Rimpeläinen, Juho; Bubba, Tatiana; Siltanen, Samuli
2018-01-01
Tomographic reconstruction is an ill-posed inverse problem that calls for regularization. One possibility is to require sparsity of the unknown in an orthonormal wavelet basis. This, in turn, can be achieved by variational regularization, where the penalty term is the sum of the absolute values of the wavelet coefficients. The primal-dual fixed point algorithm showed that the minimizer of the variational regularization functional can be computed iteratively using a soft-thresholding operation. Choosing the soft-thresholding parameter \
On an LAS-integrated soft PLC system based on WorldFIP fieldbus.
Liang, Geng; Li, Zhijun; Li, Wen; Bai, Yan
2012-01-01
Communication efficiency is lowered and real-time performance is not good enough in discrete control based on traditional WorldFIP field intelligent nodes in case that the scale of control in field is large. A soft PLC system based on WorldFIP fieldbus was designed and implemented. Link Activity Scheduler (LAS) was integrated into the system and field intelligent I/O modules acted as networked basic nodes. Discrete control logic was implemented with the LAS-integrated soft PLC system. The proposed system was composed of configuration and supervisory sub-systems and running sub-systems. The configuration and supervisory sub-system was implemented with a personal computer or an industrial personal computer; running subsystems were designed and implemented based on embedded hardware and software systems. Communication and schedule in the running subsystem was implemented with an embedded sub-module; discrete control and system self-diagnosis were implemented with another embedded sub-module. Structure of the proposed system was presented. Methodology for the design of the sub-systems was expounded. Experiments were carried out to evaluate the performance of the proposed system both in discrete and process control by investigating the effect of network data transmission delay induced by the soft PLC in WorldFIP network and CPU workload on resulting control performances. The experimental observations indicated that the proposed system is practically applicable. Copyright © 2011 ISA. Published by Elsevier Ltd. All rights reserved.
Fogliata, Antonella; Scorsetti, Marta; Navarria, Piera; Catalano, Maddalena; Clivio, Alessandro; Cozzi, Luca; Lobefalo, Francesca; Nicolini, Giorgia; Palumbo, Valentina; Pellegrini, Chiara; Reggiori, Giacomo; Roggio, Antonella; Vanetti, Eugenio; Alongi, Filippo; Pentimalli, Sara; Mancosu, Pietro
2013-04-01
To appraise the potential of volumetric modulated arc therapy (VMAT, RapidArc) and proton beams to simultaneously achieve target coverage and enhanced sparing of bone tissue in the treatment of soft-tissue sarcoma with adequate target coverage. Ten patients presenting with soft-tissue sarcoma of the leg were collected for the study. Dose was prescribed to 66.5 Gy in 25 fractions to the planning target volume (PTV) while significant maximum dose to the bone was constrained to 50 Gy. Plans were optimised according to the RapidArc technique with 6 MV photon beams or for intensity modulated protons. RapidArc photon plans were computed with: 1) AAA; 2) Acuros XB as dose to medium; and 3) Acuros XB as dose to water. All plans acceptably met the criteria of target coverage (V95% >90-95%) and bone sparing (D(1 cm3) <50 Gy). Significantly higher PTV dose homogeneity was found for proton plans. Near-to-maximum dose to bone was similar for RapidArc and protons, while volume receiving medium/low dose levels was minimised with protons. Similar results were obtained for the remaining normal tissue. Dose distributions calculated with the dose to water option resulted ~5% higher than corresponding ones computed as dose to medium. High plan quality was demonstrated for both VMAT and proton techniques when applied to soft-tissue sarcoma.
Soft Robotics: New Perspectives for Robot Bodyware and Control
Laschi, Cecilia; Cianchetti, Matteo
2014-01-01
The remarkable advances of robotics in the last 50 years, which represent an incredible wealth of knowledge, are based on the fundamental assumption that robots are chains of rigid links. The use of soft materials in robotics, driven not only by new scientific paradigms (biomimetics, morphological computation, and others), but also by many applications (biomedical, service, rescue robots, and many more), is going to overcome these basic assumptions and makes the well-known theories and techniques poorly applicable, opening new perspectives for robot design and control. The current examples of soft robots represent a variety of solutions for actuation and control. Though very first steps, they have the potential for a radical technological change. Soft robotics is not just a new direction of technological development, but a novel approach to robotics, unhinging its fundamentals, with the potential to produce a new generation of robots, in the support of humans in our natural environments. PMID:25022259
Hard sphere perturbation theory for fluids with soft-repulsive-core potentials
NASA Astrophysics Data System (ADS)
Ben-Amotz, Dor; Stell, George
2004-03-01
The thermodynamic properties of fluids with very soft repulsive-core potentials, resembling those of some liquid metals, are predicted with unprecedented accuracy using a new first-order thermodynamic perturbation theory. This theory is an extension of Mansoori-Canfield/Rasaiah-Stell (MCRS) perturbation theory, obtained by including a configuration integral correction recently identified by Mon, who evaluated it by computer simulation. In this work we derive an analytic expression for Mon's correction in terms of the radial distribution function of the soft-core fluid, g0(r), approximated using Lado's self-consistent extension of Weeks-Chandler-Andersen (WCA) theory. Comparisons with WCA and MCRS predictions show that our new extended-MCRS theory outperforms other first-order theories when applied to fluids with very soft inverse-power potentials (n⩽6), and predicts free energies that are within 0.3kT of simulation results up to the fluid freezing point.
Investigation of contact pressure and influence function model for soft wheel polishing.
Rao, Zhimin; Guo, Bing; Zhao, Qingliang
2015-09-20
The tool influence function (TIF) is critical for calculating the dwell-time map to improve form accuracy. We present the TIF for the process of computer-controlled polishing with a soft polishing wheel. In this paper, the static TIF was developed based on the Preston equation. The pressure distribution was verified by the real removal spot section profiles. According to the experiment measurements, the pressure distribution simulated by Hertz contact theory was much larger than the real contact pressure. The simulated pressure distribution, which was modeled by the Winkler elastic foundation for a soft polishing wheel, matched the real contact pressure. A series of experiments was conducted to obtain the removal spot statistical properties for validating the relationship between material removal and processing time and contact pressure and relative velocity, along with calculating the fitted parameters to establish the TIF. The developed TIF predicted the removal character for the studied soft wheel polishing.
A combination of Raspberry Pi and SoftEther VPN for controlling research devices via the Internet.
Kuroda, Toshikazu
2017-11-01
Remote control over devices for experiments may increase the efficiency of operant research and expand the area where behavior can be studied. This article introduces a combination of Raspberry Pi ® (Pi) and SoftEther VPN ® that allows for such remote control via the Internet. The Pi is a small Linux computer with a great degree of flexibility for customization. Test results indicate that a Pi-based interface meets the requirement for conducting operant research. SoftEther VPN ® allows for establishing an extensive private network on the Internet using a single private Wi-Fi router. Step-by-step instructions are provided in the present article for setting up the Pi along with SoftEther VPN ® . Their potential for improving the way of conducting research is discussed. © 2017 Society for the Experimental Analysis of Behavior.
Bamboo leaf ash as the stabilizer for soft soil treatment
NASA Astrophysics Data System (ADS)
Rahman, A. S. A.; Jais, I. B. M.; Sidek, N.; Ahmad, J.; Rosli, M. I. F.
2018-04-01
Soft soil is a type of soil that have the size of particle less than 0.063mm. The strength of the soft soil does not fulfil the requirement for construction. The present of soft soil at the construction site always give a lot of problems and issues to geotechnical sector. Soil settlement is one of the problems that related to soft soil. The determination of the soft soil physical characteristics will provide a detail description on its characteristic. Soft soil need to be treated in order to gain the standard strength for construction. One of the method to strengthen the soft soil is by using pozzolanic material as a treatment method for soft soil. Furthermore bamboo leaf ash is one of the newly founded materials that contain pozzolanic material. Any material that consist of Silicon Dioxide (SiO2) as the main component and followed by Aluminium Oxide (Al2O3) and Iron Oxide (Fe2O3) are consider as pozzolanic material. Bamboo leaf ash is mix with the cement as the treatment material. Bamboo leaf ash will react with the cement to produce additional cement binder. Thus, it will increase the soil strength and will ease the geotechnical sector to achieve high quality of construction product.
Using a cloud to replenish parched groundwater modeling efforts.
Hunt, Randall J; Luchette, Joseph; Schreuder, Willem A; Rumbaugh, James O; Doherty, John; Tonkin, Matthew J; Rumbaugh, Douglas B
2010-01-01
Groundwater models can be improved by introduction of additional parameter flexibility and simultaneous use of soft-knowledge. However, these sophisticated approaches have high computational requirements. Cloud computing provides unprecedented access to computing power via the Internet to facilitate the use of these techniques. A modeler can create, launch, and terminate "virtual" computers as needed, paying by the hour, and save machine images for future use. Such cost-effective and flexible computing power empowers groundwater modelers to routinely perform model calibration and uncertainty analysis in ways not previously possible.
Using a cloud to replenish parched groundwater modeling efforts
Hunt, Randall J.; Luchette, Joseph; Schreuder, Willem A.; Rumbaugh, James O.; Doherty, John; Tonkin, Matthew J.; Rumbaugh, Douglas B.
2010-01-01
Groundwater models can be improved by introduction of additional parameter flexibility and simultaneous use of soft-knowledge. However, these sophisticated approaches have high computational requirements. Cloud computing provides unprecedented access to computing power via the Internet to facilitate the use of these techniques. A modeler can create, launch, and terminate “virtual” computers as needed, paying by the hour, and save machine images for future use. Such cost-effective and flexible computing power empowers groundwater modelers to routinely perform model calibration and uncertainty analysis in ways not previously possible.
Okahashi, Nobuyuki; Kohno, Susumu; Kitajima, Shunsuke; Matsuda, Fumio; Takahashi, Chiaki; Shimizu, Hiroshi
2015-12-01
Studying metabolic directions and flow rates in cultured mammalian cells can provide key information for understanding metabolic function in the fields of cancer research, drug discovery, stem cell biology, and antibody production. In this work, metabolic engineering methodologies including medium component analysis, (13)C-labeling experiments, and computer-aided simulation analysis were applied to characterize the metabolic phenotype of soft tissue sarcoma cells derived from p53-null mice. Cells were cultured in medium containing [1-(13)C] glutamine to assess the level of reductive glutamine metabolism via the reverse reaction of isocitrate dehydrogenase (IDH). The specific uptake and production rates of glucose, organic acids, and the 20 amino acids were determined by time-course analysis of cultured media. Gas chromatography-mass spectrometry analysis of the (13)C-labeling of citrate, succinate, fumarate, malate, and aspartate confirmed an isotopically steady state of the cultured cells. After removing the effect of naturally occurring isotopes, the direction of the IDH reaction was determined by computer-aided analysis. The results validated that metabolic engineering methodologies are applicable to soft tissue sarcoma cells derived from p53-null mice, and also demonstrated that reductive glutamine metabolism is active in p53-null soft tissue sarcoma cells under normoxia. Copyright © 2015 The Society for Biotechnology, Japan. Published by Elsevier B.V. All rights reserved.
Effects of Soft Drinks on Resting State EEG and Brain-Computer Interface Performance.
Meng, Jianjun; Mundahl, John; Streitz, Taylor; Maile, Kaitlin; Gulachek, Nicholas; He, Jeffrey; He, Bin
2017-01-01
Motor imagery-based (MI based) brain-computer interface (BCI) using electroencephalography (EEG) allows users to directly control a computer or external device by modulating and decoding the brain waves. A variety of factors could potentially affect the performance of BCI such as the health status of subjects or the environment. In this study, we investigated the effects of soft drinks and regular coffee on EEG signals under resting state and on the performance of MI based BCI. Twenty-six healthy human subjects participated in three or four BCI sessions with a resting period in each session. During each session, the subjects drank an unlabeled soft drink with either sugar (Caffeine Free Coca-Cola), caffeine (Diet Coke), neither ingredient (Caffeine Free Diet Coke), or a regular coffee if there was a fourth session. The resting state spectral power in each condition was compared; the analysis showed that power in alpha and beta band after caffeine consumption were decreased substantially compared to control and sugar condition. Although the attenuation of powers in the frequency range used for the online BCI control signal was shown, group averaged BCI online performance after consuming caffeine was similar to those of other conditions. This work, for the first time, shows the effect of caffeine, sugar intake on the online BCI performance and resting state brain signal.
NASA Astrophysics Data System (ADS)
Zhang, Lixin; Lin, Min; Wan, Baikun; Zhou, Yu; Wang, Yizhong
2005-01-01
In this paper, a new method of body fat and its distribution testing is proposed based on CT image processing. As it is more sensitive to slight differences in attenuation than standard radiography, CT depicts the soft tissues with better clarity. And body fat has a distinct grayness range compared with its neighboring tissues in a CT image. An effective multi-thresholds image segmentation method based on potential function clustering is used to deal with multiple peaks in the grayness histogram of a CT image. The CT images of abdomens of 14 volunteers with different fatness are processed with the proposed method. Not only can the result of total fat area be got, but also the differentiation of subcutaneous fat from intra-abdominal fat has been identified. The results show the adaptability and stability of the proposed method, which will be a useful tool for diagnosing obesity.
Modeling Complex Biological Flows in Multi-Scale Systems using the APDEC Framework
DOE Office of Scientific and Technical Information (OSTI.GOV)
Trebotich, D
We have developed advanced numerical algorithms to model biological fluids in multiscale flow environments using the software framework developed under the SciDAC APDEC ISIC. The foundation of our computational effort is an approach for modeling DNA-laden fluids as ''bead-rod'' polymers whose dynamics are fully coupled to an incompressible viscous solvent. The method is capable of modeling short range forces and interactions between particles using soft potentials and rigid constraints. Our methods are based on higher-order finite difference methods in complex geometry with adaptivity, leveraging algorithms and solvers in the APDEC Framework. Our Cartesian grid embedded boundary approach to incompressible viscousmore » flow in irregular geometries has also been interfaced to a fast and accurate level-sets method within the APDEC Framework for extracting surfaces from volume renderings of medical image data and used to simulate cardio-vascular and pulmonary flows in critical anatomies.« less
Modeling complex biological flows in multi-scale systems using the APDEC framework
NASA Astrophysics Data System (ADS)
Trebotich, David
2006-09-01
We have developed advanced numerical algorithms to model biological fluids in multiscale flow environments using the software framework developed under the SciDAC APDEC ISIC. The foundation of our computational effort is an approach for modeling DNA laden fluids as ''bead-rod'' polymers whose dynamics are fully coupled to an incompressible viscous solvent. The method is capable of modeling short range forces and interactions between particles using soft potentials and rigid constraints. Our methods are based on higher-order finite difference methods in complex geometry with adaptivity, leveraging algorithms and solvers in the APDEC Framework. Our Cartesian grid embedded boundary approach to incompressible viscous flow in irregular geometries has also been interfaced to a fast and accurate level-sets method within the APDEC Framework for extracting surfaces from volume renderings of medical image data and used to simulate cardio-vascular and pulmonary flows in critical anatomies.
Wang, Shang; Li, Jiasong; Manapuram, Ravi Kiran; Menodiado, Floredes M; Ingram, Davis R; Twa, Michael D; Lazar, Alexander J; Lev, Dina C; Pollock, Raphael E; Larin, Kirill V
2012-12-15
We report on an optical noncontact method for the detection of soft-tissue tumors based on the measurement of their elasticity. A focused air-puff system is used to excite surface waves (SWs) on soft tissues with transient static pressure. A high-speed phase-sensitive optical coherence tomography system is used to measure the SWs as they propagate from the point of excitation. To evaluate the stiffness of soft tissues, the Young's modulus is quantified based on the group velocity of SWs. Pilot experiments were performed on ex vivo human myxoma and normal fat. Results demonstrate the feasibility of the proposed method to measure elasticity and differentiate soft-tissue tumors from normal tissues.
A case report on the remodelling technique for the earlobe using a soft splint.
Vaiude, Partha N; Anthony, Edwin T; Syed, Mobin; Ilyas, Syed
2008-01-01
Correcting earlobe deformities often presents an aesthetic challenge to the surgeon. The described technique presents a simple, accurate and cost effective method of remodelling soft tissue defects of the earlobe using a soft splint.