varunr14/newsummary huggingface dataset:
Incompressible smoothed particle hydrodynamics generally requires particle distribution smoothing to give stable and accurate simulations with noise free pressures . The diffusion based smoothing algorithm of Lind et al . 1499 1523 has proved effective for a range of impulsive flows and propagating waves . Here we apply this to body water slam and wave body impact problems and discover that temporal pressure noise can occur for these applications . This is due to the free surface treatment as a discontinuous boundary . Treating this as a continuous very thin boundary within the pressure solver is shown to effectively cure this problem . The particle smoothing algorithm is further generalised so that a non dimensional diffusion coefficient is applied which suits a given time step and particle spacing . We model the particular problems of cylinder and wedge slam into still water . We also model wave body impact by setting up undisturbed wave propagation within a periodic domain several wavelengths long and inserting the body . In this case the loads become cyclic after one wave period and are in good agreement with experiment . This approach is more efficient than the conventional wave flume approach with a wavemaker which requires many wavelengths and a beach absorber . Results are accurate and virtually noise free spatially and temporally . Convergence is demonstrated . Although these test cases are two dimensional with simple geometries the approach is quite general and may be readily extended to three dimensions . 


Summary: We conduct truly incompressible SPH simulations for free surface flows. We further develop a stabilising particle shifting algorithm. An improved free surface boundary treatment is presented. Slamming cases and a novel efficient wave structure interaction technique are presented. Accuracy is good pressures are virtually noise free.
The Lagrange Multiplier and penalty methods are commonly used to enforce incompressibility and compressibility in models of cardiac mechanics . In this paper we show how both formulations may be equivalently thought of as a weakly penalized system derived from the statically condensed Perturbed Lagrangian formulation which may be directly discretized maintaining the simplicity of penalty formulations with the convergence characteristics of LM techniques . A modified Shamanskii Newton Raphson scheme is introduced to enhance the nonlinear convergence of the weakly penalized system and exploiting its equivalence modifications are developed for the penalty form . Focusing on accuracy we proceed to study the convergence behavior of these approaches using different interpolation schemes for both a simple test problem and more complex models of cardiac mechanics . Our results illustrate the well known influence of locking phenomena on the penalty approach and its effect on accuracy for whole cycle mechanics . Additionally we verify that direct discretization of the weakly penalized form produces similar convergence behavior to mixed formulations while avoiding the use of an additional variable . Combining a simple structure which allows the solution of computationally challenging problems with good convergence characteristics the weakly penalized form provides an accurate and efficient alternative to incompressibility and compressibility in cardiac mechanics . 


Summary: A finite element displacement formulation stemming from the Perturbed Lagrangian. The efficiency is enhanced with a Shamanskii Newton Raphson scheme. Comparison with Perturbed Lagrangian Lagrange Multiplier and penalty methods. Presence of locking in the penalty method for whole cycle cardiac mechanics. The presented form combines good convergence behavior with a simplified structure.
Discrete element methods can be based on either penalties or impulses to resolve collisions . A generic impulse based method the energy tracking method is described to resolve collisions between multiple non convex bodies in three dimensions . As opposed to the standard sequential impulse method and simultaneous impulse method which also apply impulses to avoid penetration the energy tracking method changes the relative velocity between two colliding bodies iteratively yet simultaneously . Its main novelty is that impulses are applied gradually at multi point contacts and energy changes at the contact points are tracked to ensure conservation . Three main steps are involved in the propagation of the impulses during the single and multi contact resolution compression restitution related energy loss and separation . Numerical tests show that the energy tracking method captures the energy conservation property of perfectly elastic single and multi point collisions . ETM exhibits improved angular velocity estimation as compared to SMM and SQM as demonstrated by two numerical examples that model multi point contact between box shaped objects . Angles of repose estimated for multi object pack repositioning of spheres cubes and crosses are in good agreement with the reported experimental values . 


Summary: DEM can be based on penalties or impulses to resolve collisions. The impulse based energy tracking method ETM resolves multiple collisions consistently. ETM models multiple collisions iteratively yet simultaneously while tracking the system energy. ETM does not rely on penalties and does not require computation of penetration of bodies. The method is validated in the context of energy conservation and meso scale angles of repose.
This article presents a novel approach to collision detection based on distance fields . A novel interpolation ensures stability of the distances in the vicinity of complex geometries . An assumed gradient formulation is introduced leading to a continuous distance function . The gap function is re expressed allowing penalty and Lagrange multiplier formulations . The article introduces a node to element integration for first order elements but also discusses signed distances partial updates intermediate surfaces mortar methods and higher order elements . The algorithm is fast simple and robust for complex geometries and self contact . The computed tractions conserve linear and angular momentum even in infeasible contact . Numerical examples illustrate the new algorithm in three dimensions . 


Summary: Presents asynchronous variational integrators in the context of finite elements with continuous strain fields. Illustrates an enhanced interpretation of the current space time front. Provides a strategy for estimating the critical time step size using CAG elements nodal integration or SFEM.
A graph grammar is a formal tool for providing rigorous but intuitive ways to define visual languages . Based on an existing graph grammar this paper proposes new context sensitive graph grammar formalism called the Extension of Edge based Graph Grammar or E EGG . The E EGG introduces new mechanisms into grammatical specifications productions operations and so on in order to conveniently treat the bidirectional transformation between the Business Process Modeling Notation and the Business Process Execution Language . Besides formal definitions of the E EGG are provided steps and algorithms to achieve the bidirectional transformation and to check the correctness of BPMN models structure are presented . Finally a case study on transformation from BPMN models to BPEL codes is provided to show how the parsing algorithm of the E EGG works . 


Summary: We propose a new context sensitive graph grammar formalism called E EGG in short. E EGG introduces new mechanisms to tackle bidirectional transformation between BPMN and BPEL. Steps to achieve transformation and check correctness of BPMN structure are presented. Corresponding algorithms are further designed and analyzed. A case study on transformation from BPMN to BPEL is discussed.
With reference to a network consisting of sensor nodes connected by wireless links we approach the problem of the distribution of the cryptographic keys . We present a solution based on communication channels connecting sequences of adjacent nodes . All the nodes in a channel share the same key . This result is obtained by propagating the key connecting the first two nodes to all the other nodes in the channel . The key propagation mechanism is also used for key replacement as is required for instance in group communication to support forms of forward and backward secrecy when a node leaves a group or a new node is added to an existing group . 


Summary: In a sensor network communication channels connecting sequences of adjacent nodes are created by key propagation. All the nodes in a communication channel share the same key. The key connecting the start node and the first subsequent node is propagated to all the other nodes in the channel. Communication channels are bidirectional they can be used to transmit a message from to any node in the channel.
Cellular Automata are of interest in several research areas and there are many available serial implementations of CA . However there are relatively few studies analyzing in detail High Performance Computing implementations of CA which allow research on large systems . Here we present a parallel implementation of a CA with distributed memory based on MPI . As a first step to insure fast performance we study several possible serial implementations of the CA . The simulations are performed in three infrastructures comparing two different microarchitectures . The parallel code is tested with both Strong and Weak scaling and we obtain parallel efficiencies of 75 85 for 64 cores comparable to efficiencies for other mature parallel codes in similar architectures . We report communication time and multiple hardware counters which reveal that performance losses are related to cache references with misses branches and memory access . 


Summary: We present a free open source code for Cellular Automata CA using MPI. Weak and strong scaling tests are carried out in 3 different architectures. Performance of our code compares well with performance of other mature HPC codes. Hardware counters are used to help identifying performance issues.
In underwater acoustic sensor networks long baseline localization for autonomous underwater vehicles AUVs requires distance estimation that always encounters severe problems a Time synchronization is hard to achieve in underwater environment which baffles ranging methods based on the synchronized time. b Long propagation delay of acoustic signals and the impact of AUVs mobility make it rash to use the round trip ranging RTR technology. c Sound speed uncertainty enlarges the inaccuracy of distance estimation. This work addresses those problems above and proposes an AUVs self localization algorithm with accurate sound travel time solution SL STTS which is time synchronization free and ranging optimization based. Simulation results show that under the measurement noise of time and angles the root mean square error of SL STTS is decreased by about 8 79 compared with the counterparts. In addition the average distance estimation error of SL STTS is declined by 42 compared with RTR. 


Summary: RTR causes large ranging error. AOA and AUV s orientation are processed to produce accurate OWTT. Mathematical expectation of underwater sound speed reasonably catches its uncertainty. LMA serves as an effective ranging optimizer to localize the AUV. The strategy is sensitive to time measurement noise and less affected by angle measurement noise.
Non Uniform Rational B splines and T splines can have some drawbacks when modelling damage and fracture . The use of Powell Sabin B splines which are based on triangles can by pass these drawbacks . Herein smeared as well as discrete approaches to fracture in quasi brittle materials using Powell Sabin B splines are considered . For the smeared formulation an implicit fourth order gradient damage model is adopted . Since quadratic Powell Sabin B splines employ continuous basis functions throughout the domain they are well suited for solving the fourth order partial differential equation that emerges in this higher order damage model . Moreover they can be generated from an arbitrary triangulation without user intervention . Since Powell Sabin B splines are generated from a classical triangulation they are not necessarily boundary fitting and in that case they are not isogeometric in the strict sense . For discrete fracture approaches the degree of continuity of T splines is reduced to at the crack tip . Hence stresses need to be evaluated and weighted at the integration points in the vicinity of the crack tip in order to decide when the critical stress is reached . In practice stress fields are highly irregular around crack tips . Furthermore aligning a T spline mesh with the new crack segment can be difficult . Powell Sabin B splines also remedy these drawbacks as they are continuous at the crack tip and stresses can be directly computed which vastly increases the accuracy and simplifies the implementation . Moreover re meshing is more straightforward using Powell Sabin B splines . A current limitation is that in three dimensions there is no procedure for constructing Powell Sabin B splines on arbitrary tetrahedral meshes . 


Summary: A Powell Sabin B splines formulation for higher order gradient damage models. A discrete crack model exploiting Powell Sabin B splines based on the cohesive zone concept. A remeshing strategy for Powell Sabin B splines with discrete cracks.
This paper proposes a face recognition system based on a steerable pyramid transform SPT and local binary pattern LBP for e Health secured login. In an e Health framework patients are sometimes unable to identify themselves by traditional login modalities such as username and password. Automatic face recognition can replace the conventional login modalities if the recognition system is robust. In the proposed system SPT can decompose a face image into several subbands of different scales and orientations and LBP can encode the subbands in binary texture pattern. Therefore SPT LBP scheme represents a face image in a robust way that includes multiple information sources from different scales and orientations. The proposed system is evaluated on the facial recognition technology FERET database. According to the results the proposed system achieves 99.28 recognition in fb set 80.17 in dup I set and 79.54 in dup II set. 


Summary: Face recognition system using steerable pyramid transform and local binary pattern is proposed. Zero norm minimization and local learning based algorithms are used for feature selection. 99.28 accuracy was obtained in FERET database with fb set.
An assessment approach to assess the likelihood of rock burst in coal mines by integrating the Multi Agent System with data fusion techniques is proposed in this paper . We discuss an optimal algorithm for multi sensor data fusion to improve the accuracy and reliability of the source data . Some model based situation quantization methods are described and a rock burst situation quantitative assessment model incorporating improved Dempster Shafer theory is presented . The Auto Regressive Moving Average and Holt Winters models are used to address indefinability and inaccuracy of the prediction . A case study demonstrates that the proposed situation assessment model is capable of producing relatively accurate forecasts and thereby it can provide coal mine decision makers with an overview of the development of rock bursts . 


Summary: The target of this research is assessment situation of rock burst in coal mine. Generally speaking an assessment approach for the rock burst situation by integrating the Multi Agent System with data fusion techniques is proposed. To improve the accuracy and reliability of source data an optimal algorithm for multi sensor data fusion is discussed. Some intelligent model based situation quantization methods is described and rock burst situation quantitative assessment model is discussed by improved Dempster Shafer theory. The Auto Regressive and Moving Average Model and Holt Winters model are used to deal with indefinability and inaccuracy in the process of predicting rock burst. Case study results shows the proposed rock burst situation assessment model can give a relatively accurate forecast and can help coal mine decision makers to grasp an overview of the development trend of the rock burst.
Sparse Imputation is a relatively new method that reconstructs missing spectral components of noisy speech signal with the help of the sparse based representation approaches . In this method the redundancy of signal in the frequency domain helps to rebuild noisy spectral components from the remained reliable ones . On the other hand different parts of speech signal despite time intervals between them can be inherently similar to each other . In this paper a major modification over the SI method is proposed that in addition to data redundancy property of speech signal in small regions takes the advantages of its self similarity nature over long intervals . By identifying mostly similar frames using a method based on the marginal classification the Joint Sparsity method is applied and a method dubbed as the Joint Sparse Imputation is presented . The experiments conducted on AURORA 2 data set show that the proposed method significantly improves the recognition results in different noisy conditions compared to the original SI method . 


Summary: The self similarity nature of speech is used to improve the Sparse Imputation method. The similar frames of speech utterance are identified using marginal classification. The Joint Sparsity method is used to reconstruct noisy component of similar frames together.
This study developed an air supply station for air powered scooters. The station comprised mechanical and electrical systems. The key components of the mechanical system were a high power air compressor low pressure cylinder pneumatic boosting cylinder high pressure accumulator and target tank. The electrical system comprised pressure sensors air flow sensors and control circuits which were equipped adequately for the air charge. An air powered scooter was used to evaluate the design specifications and charging performance of the station and the scooter was tested on a chassis dynamometer to assess performance during a modified standard driving cycle. The experimental results confirmed that the air supply station can produce high pressure air for air powered vehicles. The station design can guide the development of similar technology by companies in the transportation and green energy industries. Future research will conduct a theoretical analysis by modeling and simulating the performance of the air station and air scooter. 


Summary: An air supply station with mechanical and electrical systems was built. Two operation modes were designed for charging air bottles. An air powered scooter was used to evaluate the design specifications and charging performance. Results confirm that the station produced high pressure air for vehicles. Theoretical analysis and performance simulation will be conducted in the future.
This work investigates the digit serial polynomial basis multipliers performing multiplication in multiple binary extension fields . Designing such versatile multipliers encounters a number of difficulties . First of all the element sizes of the supported fields are different from each other and thus the elements are represented with different number of bits for each field . To deal with different sized elements designs with left or right justified operands are investigated . Secondly each field multiplication involves modular reduction with a different irreducible polynomial and thus the complexity can increase rapidly with the number of supported fields . To prevent this two methods are studied Using sparse irreducible polynomials and unifying the modular reduction computation of the fields by choosing the irreducible polynomials suitably . Our work shows that multiple fields can be supported at the cost of an increase in area and an increase in time . 


Summary: We propose versatile multiplier architectures supporting multiple binary extension fields. We analyze the increase in the cost due to supporting multiple fields. We study a multiplier design supporting five binary fields recommended by NIST for elliptic curves.
Biometric based personal authentication is receiving a widespread interest in the area of research due to its high applicability in a wide range of security applications . Among these hand based biometric systems are considered to be more successful in terms of accuracy and computational complexity . In hand based biometrics finger knuckle surface is considered as one of the emerging potential biometric traits for personal authentication . This is due to its stable and unique inherent patterns present in the outer surface of the finger back knuckle region . Further this finger knuckle has a high potentiality towards discriminating individuals with high accuracy . In this paper we present a review of various system models that are implemented for personal authentication using finger knuckle biometrics . Furthermore the challenges that could arise during the implementation of the large scale real time biometric system with finger knuckle print are explored . 


Summary: Describes the role of finger knuckle surface in biometric authentication. Enumerates various available open datasets for finger knuckle biometric trait. Presents different view point in the classification of various finger knuckle feature recognition methods. Elaborates on finger knuckle surface preprocessing feature extraction classification and fusion methodologies. Addresses significant issues that are mandatory for deploying finger knuckle biometric system.
This paper proposes a robust particle filter to deal with incomplete sensor data to predict the user s routes and represents users movements using a dynamic Bayesian network model that patterns the user s spatiotemporal routine . The proposed particle filter includes robust particle generation to supplement any incorrect and incomplete sensor information efficient switching weight functions to reduce computation complexity while considering uncertainty and resampling to enhance the accuracy of the particles by solving the degeneracy problem . The robust particle filter enhances the accuracy and efficiency with which a user s routes and destinations are determined . 


Summary: We propose DBN based route models and prediction of users routes using robust particle filtering. We use a DBN to infer the next locations or destinations based on the observed spatio temporal data. The robust particle filter handles uncertainty and constraints to enhance accuracy and efficiency.
In view of the fact that objects with different natures usually respond differently to the same external stimulus this paper proposes a no reference image quality assessment based on gradient histogram response . GHR is the gradient histogram variation of an image object under a local transform . In the metric through preprocessing a test image is transformed to a noise image and a blur image which are taken as two image objects . Each image object is exerted with a local transform as an object input and its GHR as an object output is extracted in multiscale space . The two GHRs compose a global feature vector and are mapped to an image quality score . Experiments show that GHR outperforms state of the art no reference metrics statistically in the condition that test images are degraded by different types of distortions . Especially the metric is feasible for the quality assessment of the images degraded by mixed distortions though the types of these images are not included in the training database . 


Summary: A NR image quality assessment based on gradient histogram response GHR is proposed. A test image is preprocessed to produce a noise image object and a blur image object. GHR is the gradient histogram variation of an image object under a local transform. GHR performs well for the images degraded by different distortions or mixed distortions.