Parameter-based Approach Research Articles

Evaluation in discourse on crime

The article presents a parameter-based approach to the phenomenon of evaluation in the written discourse and examines the texts of Lithuanian popular media about crimes that are not usually treated as belonging to evaluative genres but are interesting in the aspect of evaluation: journalists must adhere to the principles of ethics and the presumption of innocence and use a neutral language, but the subject of writing itself has a strong basis for a negative evaluation because of the common social practice to negatively assess crimes and offenders and thus it is difficult to remain neutral. Taking into account the models of evaluative parameters and some aspects of appraisal theory and using the method of discourse analysis, the texts of discourse on crime are shown as texts which often realize the following evaluative parameters: DANGER (most frequent), SPEED, QUANTITY/VALUE, QUALITY, SOCIAL PROPRIETY, EXPECTEDNESS. The fact that these parameters generalized from real data on a specific topic are different from the evaluative parameters of popular media on other topics confirms the notion that theoretical considerations of the phenomenon of evaluation and practical models of evaluative parameters depend not only on the genre of texts but also on the topic. The results of our research also show that the main contrasts in the texts under investigation is the opposition of law enforcement officer (positive evaluation) and offender (negative evaluation), in contrast to the more conventional opposition in the Western media of offender and victim.

Geometrical compensation of deterministic deviations for part finishing in bulk forming

The design and development of bulk forming processes build upon inefficient trial-and-error procedures, especially in industrial practice. Furthermore, manual redesign procedures to transform discrete measurement data or numerical meshes into parametric descriptions cause approximation errors and are not continuously automatable. To achieve the required final accuracy in the part finishing, various iterations consisting of numerical simulations, subsequent real tests and redesign steps have to be carried out. To address these issues, a data-driven numerical strategy to compensate for deterministic deviations of bulk-formed parts is deduced, adapting methods used for springback compensation in sheet metal forming. Due to a parameter-based approach, control points allow for a connection between material points of the part and the tool. As a consequence, a direct mapping between the die and the workpiece in the parametric space is possible. Thus, based on the required part shape the die can be directly adjusted, where any kind of geometrical input data can be provided to determine a systematic compensation. Utilizing the purely geometrical approach takes into account all of the systematic effects causing deterministic deviations. The scope of applications comprises closed-die finishing operations fulfilling the constraint of intimate contact between component and die. The proposed concept is presented and applied to real components. The deviation data of three manufactured industrial bulk forming parts is utilized for validation and verification.

Acoustic emission characteristics of fracture modes in masonry materials

Acoustic emission (AE) is a powerful technique for detection and analysis of the elastic waves produced by the failure mechanisms in construction materials such as masonry. In this study, the different fracture mechanisms are studied in relation to the properties of bricks and mortars. The fracture process is being evaluated using the combination of AE and Digital Image Correlations (DIC) techniques. The isolation of the AE signatures of different types of failure mechanisms is done by testing bricks in flexure and brickwork couplets in compression. AE data are analyzed with a simplified AE parameter-based approach aiming to characterize the fracture mode. This is one of the first times where the relation between the shear and the longitudinal strain field is correlated in masonry with AE. This offers new insight in the material's behavior especially in relation to complicated structural geometries where the dominant stress mode is not known a priori.

Replicate allocation to improve selection efficiency in the early stages of a potato breeding scheme

Field data and simulation were used to investigate replication within trials and the allocation of replicates across trial sites using partial replication as an approach to improve the efficiency of early-stage selection in a potato breeding programme. Analysis of potato trial data using linear mixed models, based on four-plant (clonal) plots planted as augmented partially-replicated (p-rep) designs, obtained genetic and environmental components of variation for a number of yield and tuber components. Heritabilities, trial-to-trial genetic correlations and performance repeatability of clonal selections in p-rep trials and in subsequent fully replicated trial stages were high, and selection was effective for the economically important traits of marketable tuber yield and tuber cooking quality. Simulations using a parameter-based approach, pertaining to the variance components estimated from the p-rep field trials, and the parametric bootstrapping of historic empirical data showed improved rates of genetic gain with p-rep testing over one and two locations compared with testing in fully replicated trials. This potato breeding study suggests that the evaluation and selection of a clonal field crop in fully replicated trials may not be optimal in the early stages of a breeding cycle and that p-rep designs offer a more efficient and practical alternative.

Tuning the granularity of parallelism for distributed graph processing

Popular distributed graph processing frameworks, such as Pregel and GraphLab, are based on the vertex-centric computation model, where users write their customized Compute function for each vertex to process the data iteratively. Vertices are evenly partitioned among the compute nodes, and the granularity of parallelism of the graph algorithm is normally tuned by adjusting the number of compute nodes. Vertex-centric model splits the computation into phases. Inside one specific phase, the computation proceeds as an embarrassingly parallel process, because no communication between compute nodes incurs. By default, current graph engine only handles one iteration of the algorithm in a phase. However, in this paper, we find that we can also tune the granularity of parallelism, by aggregating the computation of multiple iterations into one phase, which has a significant impact on the performance of the graph algorithm. In the ideal case, if all computations are handled in one phase, the whole algorithm turns into an embarrassingly parallel algorithm and the benefit of parallelism is maximized. Based on this observation, we propose two approaches, a function-based approach and a parameter-based approach, to automatically transform a Pregel algorithm into a new one with tunable granularity of parallelism. We study the cost of such transformation and the trade-off between the granularity of parallelism and the performance. We provide a new direction to tune the performance of parallel algorithms. Finally, the approaches are implemented in our graph processing system, N2, and we illustrate their performance using popular graph algorithms.

Process-integrated Compensation of Geometrical Deviations for Bulk Forming

In many cases the design and development of bulk forming processes bases on inefficient trial-and-error procedures consisting of various iterations of numerical and real tests. To address this issue, a new numerical strategy to compensate systematic deviations of bulk-formed parts is deduced. Due to a parameter-based approach, control points allow for a direct mapping between the die and the workpiece. Thus, based on the required part shape, it is possible to directly adjust the die, where any kind of geometrical input data can be provided to derive a systematic compensation. The purely geometrical approach takes into account the entirety of systematical effects regarding deviations in bulk forming. The proposed concept is shown theoretically and moreover validated as well as verified utilizing deviation data of three manufactured industrial bulk-forming parts.

A state parameter-based model for static recrystallization interacting with precipitation

In the present work, we develop a state parameter-based model for the treatment of simultaneous precipitation and recrystallization based on a single-parameter representation of the total dislocation density and a multi-particle multi-component framework for precipitation kinetics. In contrast to conventional approaches, the interaction of particles with recrystallization is described with a non-zero grain boundary mobility even for the case where the Zener pressure exceeds the driving pressure for recrystallization. The model successfully reproduces the experimentally observed particle-induced recrystallization stasis and subsequent continuation in micro-alloyed steel with a single consistent set of input parameters. In addition, as a state parameter-based approach, our model naturally supports introspection into the physical mechanisms governing the competing recrystallization and recovery processes.

Statistical Parameter-based Automatic Liver Tumor Segmentation from Abdominal CT Scans: A Potiential Radiomic Signature

Liver imaging using abdominal CT images has been widely studied in the recent years and is a challenging task. Processing CT image includes the automatic diagnosis of liver and lesions part. Because of the high intensity similarity between liver tissues and nearby organs of liver it is difficult to segment liver and tumor. Segmentation of extracted region as an imaging biomarker forms an essential component of “Radiomics”. This paper presents automatic liver tumor segmentation from abdominal CT scan images. A statistical parameter-based approach is used to distinguish liver tumor tissue from other abdominal organs. The existing segmentation methods such as region growing and intensity based thresholding methods are investigated. First, the CT images are preprocessed by filtering to remove noise from the image. Then the statistical mean-based thresholding is applied to extract the tumor. After applying median filtering, isodata threshold is used to turn the image into binary with tumors as black spots on white background. Finally postprocessing as filtering techniques like mean filter and median filter and morphological operations are performed to remove residues. This paper highlights liver tumor segmentation analysis which has the potential as a imaging biomarker for “Personalised cancer imaging”.

How products are evaluated? Evaluation in customer review texts

This study, drawing on insights from the Appraisal framework, the parameter-based approach to evaluation and corpus linguistics, investigates the evaluative language used in customer review texts. The primary goal of this investigation is to develop a framework of evaluation that can be used to account adequately for evaluative expressions in customer review texts, and the ultimate goal is to support the argument that the modelling and theorising of evaluation is context-specific. Based on the investigation into a corpus compiled of review texts retrieved from www.amazon.co.uk, this study proposes a data-driven, parameter-based and appraisal-informed framework of evaluation which comprises four parameters--Quality, Satisfactoriness, Recommendability and Worthiness. Since these parameters are not thought-up, but are generalised from real data, it is arguable that the proposed framework of evaluation is certainly valid and thus can be used to describe and analyse evaluative language used in this particular context. This in turn indicates that the description and theorising of evaluation is indeed highly dependent on the discourse type that is under examination.

Fluid dynamics of heart valves during atrial fibrillation: a lumped parameter-based approach

Atrial fibrillation (AF) consequences on the heart valve dynamics are usually studied along with a valvular disfunction or disease, since in medical monitoring, the two pathologies are often concomitant. Aim of the present work is to study, through a stochastic lumped-parameter approach, the basic fluid dynamics variations of heart valves, when only paroxysmal AF is present with respect to the normal sinus rhythm in absence of any valvular pathology. Among the most common parameters interpreting the valvular function, the most useful turns out to be the regurgitant volume. During AF, both atrial valves do not seem to worsen their performance, while the ventricular efficiency is remarkably reduced.

Weight and mechanical performance optimization of blended composite wing panels using lamination parameters

In this paper, a lamination parameter-based approach to weight optimization of composite aircraft wing structures is addressed. It is a bi-level procedure where at the top level lamination parameters and numbers of plies of the pre-defined angles (0, 90, 45 and −45°) are used as design variables, the material volume is treated as an objective function to be minimized subject to the buckling, strength and ply percentage constraints. At the bottom level the optimum stacking sequence is obtained subject to the requirements on blending and preservation of mechanical properties. To ensure composite blending, a multi-stage optimization is performed by a permutation genetic algorithm aiming at matching the lamination parameters passed from the top level optimization as well as satisfying the layup rules. Two new additional criteria, the 90° ply angle jump index and the stack homogeneity index, are introduced to control the uniformity of the three ply angles (0, 90, 45 and −45) spread throughout the stack as well as improve the stack quality and mechanical performance by encouraging 45° angle change between neighbouring groups of plies. The results of the application of this approach are compared to published results to demonstrate the potential of the developed technique.

Modeling and Analysis of Crosstalk Induced Effects in Multiwalled Carbon Nanotube Bundle Interconnects: An ABCD Parameter-Based Approach

In this paper, the crosstalk effects in both small and large diameter multiwalled carbon nanotube bundle interconnects (MWCNTs) for the future nanoscale integrated circuits are studied with the help of ABCD parameter matrix approach for global levels of interconnects at 22- and 14-nm technology nodes. Here, isolated MWCNTs are modeled using an equivalent single conductor transmission line. The simulation results show that the results are at par with the result of SPICE model. It is observed that performance wise, the large diameter MWCNT bundles are better than both small diameter MWCNT bundles and copper wire for both repeated and unrepeated interconnects. The same trend is observed with the number of inserted repeaters. For repeated wires, the optimized placement of repeaters offsets the delay advantage numbers of MWCNT bundles over copper wire. Technology scaling adversely impacts the delay advantage numbers of small diameter MWCNT bundles. As far as the worst-case crosstalk noise peak voltage is concerned, the large diameter MWCNT bundles also outperform both small diameter MWCNT bundles and copper wire for longer interconnects. However, for shorter interconnects, copper wire and small diameter bundles outclass the large diameter bundles due to their relatively larger time constant. We have compared our crosstalk analysis results with the earlier work to justify the validity of our proposed model and observed that the results with our model are in well conformity with the existing work. It is seen that even the tall Cu vias are not going to significantly affect the performance of MWCNT bundle interconnects. Twice the minimum width global level interconnects are the optimal choice to achieve the maximum delay advantage using MWCNT bundle interconnects in comparison with Cu-based interconnects. Finally, our analysis shows that from the performance and signal integrity perspective, the large diameter MWCNT bundles are a suitable alternative to both small diameter MWCNT bundles and copper interconnects for future integrated circuit technology generations.

Microstructure and Flow Stress Modelling During Plastic Deformation of an Aluminum Alloy Type A6061

The deformation behavior of an A6061 aluminum alloy in different heat treatment conditions of natural aging is simulated in a state parameter-based microstructure evolution approach. It is shown that at least two state parameters are required for modelling experimental flow curves at lower temperature accurately. In the present model, the evolution of dislocation densities inside subgrains and in subgrain boundaries are introduced as state parameters. The evolution of these parameters is modeled based on the individual mechanism of dislocation generation and storage and dynamic annihilation and recovery. We propose a convenient method to derive the adjustment parameters of the model from experimental data. The model predictions are validated by a series of compression tests carried out on a Gleeble 1500 thermo-mechanical simulator, where the A6061 alloy is tested for variable natural ageing times after quenching. The comparison between simulation and experiment shows good agreement and demonstrates the predictive capabilities of the state parameter-based approach.

Slow-equilibration approximation in studying kinetics of protein adsorption on capillary walls.

Adsorption of proteins on inner capillary walls affects the quality of capillary electrophoresis (CE) analyses. Coating the capillary surface with an anti-adhesive layer is a method typically used to suppress protein adsorption. The successful development of methods for prevention of protein adsorption requires quantitative characterization of the surface ability to adsorb and desorb a protein. It can be done by determining kinetic rate constants of adsorption, kad, and desorption, kdes. We have recently developed a pattern-based method for determination of kad and kdes for protein interaction with a capillary wall. The protein is moved through the capillary in a CE instrument by pressure and a temporal pattern of protein propagation through the detector is recorded. The experimental pattern is fitted with a numerical solution of the protein mass transfer to find kad and kdes. The fitting procedure is not "transparent" and can be complicated. In the present work, we obtained approximate analytical solutions of the protein mass transfer equations in the case of slow-equilibration during adsorption and desorption of the protein. These analytical solutions allow us to introduce a fitting-free parameter based method for determination of kad and kdes. It uses simple explicit expressions for kad and kdes in terms of experimental characteristics easily measured in capillaries. We tested the accuracy of the method by applying it to signals simulated with numerical solutions of protein mass-transfer equations. For the slow equilibration approximation the accuracy of kad and kdes was better than 12%.

Zoning methods for handwritten character recognition: A survey

This paper presents a survey on zoning methods for handwritten character recognition. Through the analysis of the relevant literature in the field, the most valuable zoning methods are presented in terms of both topologies and membership functions. Throughout the paper, diverse zoning topologies are presented based on both static and adaptive approaches. Concerning static approaches, uniform and non-uniform zoning strategies are discussed. When adaptive zonings are considered, manual and automatic strategies for optimal zoning design are illustrated as well as the most appropriate zoning representation techniques. In addition, the role of membership functions for zoning-based classification is highlighted and the diverse approaches to membership function selection are presented. Concerning global membership functions, the paper introduces order-based approaches as well as fuzzy approaches using border-based and ranked-based fuzzy membership values. Concerning local membership functions, the recent parameter-based approaches are described, in which the optimal membership-function is selected for each zone of the zoning method. Finally, a comparative analysis on the performance of zoning methods is presented and the most interesting approaches are focused on in terms of topology design and membership function selection. A list of selected references is provided as a useful tool for interested researchers working in the field.

Assessing Overconsolidation Ratios in Soil with Piezocone: Referencing Soil Index Properties

AbstractTo enhance the assessment of the overconsolidation ratio (OCR), this paper describes the importance of relating the soil type and soil index properties to the empirical correlations used to evaluate the preconsolidation stress and OCR using the piezocone and the importance to apply the normalized soil behavior approach. Data from a variety of sites is assembled using published and unpublished sources to develop empirical correlations for the normalized soil behavior or the stress history and normalized soil engineering parameter-based approach that vary with the plasticity index, liquid limit, median particle size, and organic content of the soil. Examples are presented to illustrate application of the correlations.

When can we trust our model predictions? Unearthing structural sensitivity in biological systems

It is well recognized that models in the life sciences can be sensitive to small variations in their model functions, a phenomenon known as ‘structural sensitivity’. Conventionally, modellers test for sensitivity by varying parameters for a specific formulation of the model functions, but models can show structural sensitivity to the choice of functional representations used: a particularly concerning problem when system processes are too complex, or insufficiently understood, to theoretically justify specific parameterizations. Here we propose a rigorous test for the detection of structural sensitivity in a system with respect to the local stability of equilibria, the main idea being to project infinite dimensional function space onto a finite dimensional space by considering the local properties of the model functions. As an illustrative example, we use our test to demonstrate structural sensitivity in the seminal Rosenzweig–MacArthur predator–prey model, and show that the conventional parameter-based approach can fail to do so. We also consider some implications that structural sensitivity has for ecological modelling: we argue that when the model exhibits structural sensitivity but experimental results remain consistent it may indicate that there is a problem with the model construction, and that in some cases trying to find an ‘optimal’ parameterization of a model function may simply be impossible when the model exhibits structural sensitivity. Finally, we suggest that the phenomenon of structural sensitivity in biological models may help explain the irregular oscillations often observed in real ecosystems.

A vertex similarity-based framework to discover and rank orphan disease-related genes

BackgroundA rare or orphan disease (OD) is any disease that affects a small percentage of the population. While opportunities now exist to accelerate progress toward understanding the basis for many more ODs, the prioritization of candidate genes is still a critical step for disease-gene identification. Several network-based frameworks have been developed to address this problem with varied results.ResultWe have developed a novel vertex similarity (VS) based parameter-free prioritizing framework to identify and rank orphan disease candidate genes. We validate our approach by using 1598 known orphan disease-causing genes (ODGs) representing 172 orphan diseases (ODs). We compare our approach with a state-of-art parameter-based approach (PageRank with Priors or PRP) and with another parameter-free method (Interconnectedness or ICN). Our results show that VS-based approach outperforms ICN and is comparable to PRP. We further apply VS-based ranking to identify and rank potential novel candidate genes for several ODs.ConclusionWe demonstrate that VS-based parameter-free ranking approach can be successfully used for disease candidate gene prioritization and can complement other network-based methods for candidate disease gene ranking. Importantly, our VS-ranked top candidate genes for the ODs match the known literature, suggesting several novel causal relationships for further investigation.

Two-peak approximation in kinetic capillary electrophoresis

Kinetic capillary electrophoresis (KCE) constitutes a toolset of homogeneous kinetic affinity methods for measuring rate constants of formation (k(+)) and dissociation (k(-)) of non-covalent biomolecular complexes, C, formed from two binding partners, A and B. A parameter-based approach of extracting k(+) and k(-) from KCE electropherograms relies on a small number of experimental parameters found from the electropherograms and used in explicit expressions for k(+) and k(-) derived from approximate solutions to mass transfer equations. Deriving the explicit expressions for k(+) and k(-) is challenging but it is justified as the parameter-based approach is the simplest way of finding k(+) and k(-) from KCE electropherograms. Here, we introduce a unique approximate analytical solution of mass transfer equations in KCE termed a "two-peak approximation" and a corresponding parameter-based method for finding k(+) and k(-). The two-peak approximation is applicable to any KCE method in which: (i) A* binds B to form C* (the asterisk denotes a detectable label on A), (ii) two peaks can be identified in a KCE electropherogram and (iii) the concentration of B remains constant. The last condition holds if B is present in access to A* and C* throughout the capillary. In the two-peak approximation, the labeling of A serves only for detection of A and C and, therefore, is not required if A (and thus C) can be observed with a label-free detection technique. We studied the proposed two-peak approximation, in particular, its accuracy, by using the simulated propagation patterns built with the earlier-developed exact solution of the mass-transfer equations for A* and C*. Our results prove that the obtained approximate solution of mass transfer equations is correct. They also show that the two-peak approximation facilitates finding k(+) and k(-) with a relative error of less than 10% if two peaks can be identified on a KCE electropherogram. Importantly, the condition of constant concentration of B is always satisfied in macroscopic approach to studying kinetics at equilibrium (MASKE) whether or not B is in excess to A* and C*, and, thus, the two-peak approximation is applicable to MASKE. It completes a toolset of fitting-free methods for processing MASKE data and makes MASKE a simple practical method for finding k(+) and k(-) of "fast", "slow", and "intermediate-rate" non-covalent interactions.

A quadripolar parameter-based approach of ideal gyrators structured on operational amplifier circuits

The paper approaches some aspects regarding performances characteristics of gyrators with different circuit topology. The gyrators behavior of a class of two-ports structured on operational amplifiers and resistors is studied. In order to verify the theoretical predictions the analytical quadripolar parameters are bridged with the experimental one numerical by the means of a Pspice simulation. The gyrator equations express the instantaneous behavior of switching power converters, averaged over one switching cycle. Any dc- dc switching power converter meet the requirements of closed-loop control of output voltage or current. There are many ways to design a physical system with gyrator behavior like. Some gyrators are based on various physical effects, like the Hall-effect, other gyrators are created using electronically devices, like operational amplifiers. All these synthesis operate time-continuously.