Quantification Process Research Articles

Locality-Aware CTA Clustering for Modern GPUs

Cache is designed to exploit locality; however, the role of on-chip L1 data caches on modern GPUs is often awkward. The locality among global memory requests from different SMs (Streaming Multiprocessors) is predominantly harvested by the commonly-shared L2 with long access latency; while the in-core locality, which is crucial for performance delivery, is handled explicitly by user-controlled scratchpad memory. In this work, we disclose another type of data locality that has been long ignored but with performance boosting potential --- the inter-CTA locality. Exploiting such locality is rather challenging due to unclear hardware feasibility, unknown and inaccessible underlying CTA scheduler, and small in-core cache capacity. To address these issues, we first conduct a thorough empirical exploration on various modern GPUs and demonstrate that inter-CTA locality can be harvested, both spatially and temporally, on L1 or L1/Tex unified cache. Through further quantification process, we prove the significance and commonality of such locality among GPU applications, and discuss whether such reuse is exploitable. By leveraging these insights, we propose the concept of CTA-Clustering and its associated software-based techniques to reshape the default CTA scheduling in order to group the CTAs with potential reuse together on the same SM. Our techniques require no hardware modification and can be directly deployed on existing GPUs. In addition, we incorporate these techniques into an integrated framework for automatic inter-CTA locality optimization. We evaluate our techniques using a wide range of popular GPU applications on all modern generations of NVIDIA GPU architectures. The results show that our proposed techniques significantly improve cache performance through reducing L2 cache transactions by 55%, 65%, 29%, 28% on average for Fermi, Kepler, Maxwell and Pascal, respectively, leading to an average of 1.46x, 1.48x, 1.45x, 1.41x (up to 3.8x, 3.6x, 3.1x, 3.3x) performance speedups for applications with algorithm-related inter-CTA reuse.

Resilience frameworks instantiated to vehicular traffic applications

Ground transportation systems are critical to the economy, safety, and quality of life of any community. Thus, engineers and policy-makers need to make sure that these systems are resilient to the impact of natural and man-made hazards. One of the current obstacles for achieving more resilient ground transportation systems is the lack of a resilience-measuring framework for traffic applications. This research addresses this gap by exploring the adaptation of two infrastructure resilience measuring models to traffic-based applications. The implications of the two adaptations when measuring the resilience of ground transportation systems were analyzed. Moreover, a pilot study conducted for a small urban network illustrates the quantification process and the results obtained when using the two frameworks. These results show that vehicular traffic has unique characteristics which make a continuous deterministic model more suitable to traffic applications than a probabilistic one.

A New Resilience Measure for Supply Chain Networks

Currently, supply chain networks can span the whole world, and any disruption of these networks may cause economic losses, decreases in sales and unsustainable supplies. Resilience, the ability of the system to withstand disruption and return to a normal state quickly, has become a new challenge during the supply chain network design. This paper defines a new resilience measure as the ratio of the integral of the normalized system performance within its maximum allowable recovery time after the disruption to the integral of the performance in the normal state. Using the maximum allowable recovery time of the system as the time interval under consideration, this measure allows the resilience of different systems to be compared on the same relative scale, and be used under both scenarios that the system can or cannot restore in the given time. Two specific resilience measures, the resilience based on the amount of product delivered and the resilience based on the average delivery distance, are provided for supply chain networks. To estimate the resilience of a given supply chain network, a resilience simulation method is proposed based on the Monte Carlo method. A four-layered hierarchial mobile phone supply chain network is used to illustrate the resilience quantification process and show how network structure affects the resilience of supply chain networks.

The Seductions of Quantification: Measuring Human Rights, Gender Violence, and Sex Trafficking by Sally Engle Merry

Reviewed by: The Seductions of Quantification: Measuring Human Rights, Gender Violence, and Sex Trafficking by Sally Engle Merry David Cingranelli (bio) Sally Engle Merry, The Seductions of Quantification: Measuring Human Rights, Gender Violence, and Sex Trafficking (University of Chicago Press 2016), ISBN 978-0-226-26128-7, 249 pages. Sally Engle Merry’s The Seductions of Quantification: Measuring Human Rights, Gender Violence, and Sex Trafficking describes and critiques the process of producing and analyzing numerical indicators of human rights, gender violence, and sex trafficking. She believes that the [End Page 239] process of quantification is highly political and ideological, and that quantitative measurement systems constitute a form of power, incorporating theories about social change in their design. She emphasizes that measurement systems are developed by powerful organizations, and the organizational value biases behind those systems are rarely explicit. Quantification itself contributes to a “myth of objectivity,” meaning that the truth of most things can be found in numbers. One of the main problems with quantification, she contends, is that the production of quantified measurements is not as open and transparent as it should be. If it were clearer, we would be able to see that it is shaped by “ideology, inertia, social and political influence, inadequate data, and the pragmatic compromises that poor data require.”1 In several chapters, she provides examples showing that what is measured and how it is measured usually depends upon the preferences of powerful organizations. As a result of this bias and other problems detailed in her book, she concludes that “[n]ot all that should be counted is counted, nor does counting itself necessarily provide an accurate picture of a situation or its explanation.”2 In the interest of full disclosure, the reader should know that I have spent most of my professional life quantifying cross-national variations in government respect for a variety of human rights such as freedom of religion, freedom of speech, and press. So I personally have contributed and continue to contribute to the “seduction of quantification” the author describes. Therefore, I began my reading of this work with a great interest in her subject and a bias against her argument. I also read this book with great respect for the views of this particular author. She is an acknowledged expert on evaluating the performance of respect for human rights and other aspects of good governance. She has written several previous books and articles on related subjects, and this book is filled with interesting examples drawn from her personal experiences. She discusses her active participation helping intergovernmental and nongovernmental organizations develop creative ways to evaluate progress in human rights, including reducing gender violence and sex trafficking. Overall, I agree with the author’s diagnosis of the problems presented by quantification, and with her assessment that there is a trend towards producing more numerical scores designed to capture complex human rights and governance concepts. She accurately describes the strong trend towards greater use and increasingly uncritical and naïve use of those scores by scholars and policy makers. She does a good job of explaining the reasons for this trend, or, as she refers to it in her title, the reasons for “the seductions of quantification.” I also found her book to be very readable despite the fact that the discussion sometimes addresses technical subjects and provides detailed accounts of the politics behind the development of numerical indicators. Her book is well organized and well written. It is composed at a level appropriate for advanced undergraduate college students. I will probably assign the first two chapters and the conclusion to the book as required [End Page 240] reading for my undergraduate seminar on measuring human rights. The book contains an excellent, up-to-date review of the relevant literature. It is a must read for scholars, policy makers, and policy analysts who produce or use these types of quantitative indicators and for policy makers who want to learn more about the pitfalls of evidence-based governance. Less sophisticated readers (those not directly involved in the knowledge production and consumption process) probably will not fully appreciate the nuances of this account. In the remainder of this essay, I provide a brief description...

Feature Based Classification and Segmentation of Mitral Regurgitation Echocardiography Images Quantification Using PISA Method

Echocardiography is the enormously admired scientific specification for the evaluation of valvular regurgitation and gives significant knowledge on the bareness of mitral regurgitation (MR). MR is a general heart disease which does not cause indications till its final phase. A technique is advanced for jet area separation and quantification in MR assessment in arithmetical expressions. Previous to this separation method count preprocessing and some attributes are mined from the record to arrangement method. From the cataloguing method, support vector machine (SVM) classifier developed to confidential echocardiogram images. Entire abnormal images to the modified region growing (MRG) separation method to segment jet area of MR. This segmented jet area in MR quantification process passed out with the support of proximal isovelocity surface area (PISA). This procedure is based on mass diverse limitations like blood flow rate, regurgitant fraction, EROA, etc. From the outcomes, this projected effort associated with the current method fuzzy with PISA quantification process, the projected work attained accuracy rate 99.05% in the study of jet area segmenting and quantification method.

Machine Learning for Fully Automatic 3D Atria Segmentation and Reconstruction from Gadolinium Enhanced MRIs

Introduction: Atrial fibrillation (AF) is the most common arrhythmia, and current treatment is suboptimal. Accurate representation of 3D atrial anatomy and its underlying structure from medical images (CT/MRI) provides an effective patient-specific approach for clinical diagnosis of atrial scar and targeted treatment for patients with AF. We propose an algorithm to automatically segment the atria to visualise its geometry in 3D. Methods: A gadolinium-enhanced (GE)-MRI dataset (N = 60), with a spatial resolution of 0.625 × 0.625 × 1.25 mm3 for patients with AF (provided by the University of Utah), was used to develop a deep convolutional neural network to recognise features specific to atrial and non-atrial tissue. The network contained a dual pathway for both local and global feature detection. The network was fully convolutional and made pixel-wise binary classifications. The MRI image slices were standardised and fed into the algorithm. The algorithm was trained with 50 patient datasets on one GPU (384 cores) and then made to perform slice-by-slice predictions on the remaining 10 patients datasets to evaluate the performance accuracy. Results: The overall accuracy for the 10 validation datasets was 54 ± 12.6%. Predictions for each patient took roughly 15 minutes. The outputs showed clear detail of the atrial wall thickness but were heavily influenced by the imaging quality of the initial MRI scans. Conclusions: We have demonstrated a deep neural network to perform fully automatic 3D atria reconstruction on medical images. Potentially, future similar studies will automate the process of quantification of atrial structure in patients with AF and thereby guide AF treatment effectively.

Edge Enhancement Investigations by Means of Experiments and Simulations

Standard neutron imaging procedures are based on the “shadow” of the transmitted radiation, attenuated by the sample material. Under certain conditions significant deviations from pure transmission can be found in the form of enhancement or depression at the edges of the samples. These effects can limit the quantification process in the related regions. Otherwise, an enhancement and improvement of visibility can be achieved e.g. in defect analysis. In systematic studies we investigated the dependency of these effects on the specific material (mainly for common metals), such as the sample-to-detector distance, the beam collimation, the material thickness and the neutron energy. The beam lines ICON and BOA at PSI and ANTARES at TU München were used for these experiments due to their capability for neutron imaging with highest possible spatial resolution (6.5 to 13.5 micro-meter pixel size, respectively) and their cold beam spectrum. Next to the experimental data we used a McStas tool for the description of refraction and reflection features at edges for comparison. Even if minor contributions by coherent in-line propagation phase contrast are underlined, the major effect can be described by refraction of the neutrons at the sample-void interface. Ways to suppress and to magnify the edge effects can be derived from these findings.

Image-Based High Content Screening: Automating the Quantification Process for DNA Damage-Induced Foci.

Visual inspection of cellular activities based on conventional fluorescence microscope is a fundamental tool to study the role of DNA damage response (DDR). In the context of drug discovery where the capture of thousands of images is required across parallel experiments, this presents a challenge to data collection and analysis. Manual scoring is laborious and often reliant on trained personnel to intuit biological meaning through visual reasoning. On the other hand, high content screening combines the automation of microscopy image acquisition and analysis in a single platform to quantify cellular events of interests. The data generated is rapid and accurate, lessening the bias of human interpretation. Herein, this chapter will describe an image-based high content screen approach and the data analysis of Ataxia-Telangiectasia Mutated (ATM) DNA damage-induced foci.

Probabilistic Approach to Evaluate Acceptable Toll Rates in Road Concessions

Countries worldwide make substantial efforts to keep the condition of their road infrastructure at an acceptable level under budgetary constraints. One possible model that enables the delivery of road projects under limited budgets is a public–private partnership (PPP). Because of several technical, financial, legal, and economic issues that need to be addressed, PPP agreements are relatively complex. In addition, defining long-term rights and obligations between the public sector and the private concessionaire requires an in-depth risk analysis because of the considerable number of risks usually encountered in PPP projects, such as a toll road concession. The objective of this paper is to present a method for an ex ante assessment of the acceptable toll rate for different stakeholders based on a probabilistic analysis of construction costs, operations and maintenance costs, and traffic volumes. The financial constraints included in the analysis are the debt service coverage ratio and return on equity. The resulting toll rates are determined from the simulated probability distributions of the input parameters. Such rates are then compared with the socially acceptable toll rate. The application of the proposed method to a case study of a toll road concession in Greece for which publicly available data were obtained indicates that the method presented is able to capture some uncertainties and improve the project’s risk quantification process. It is recommended that the proposed method be tested on other projects for further validation and eventual upgrading of the model for use as a tool in risk management in toll road concessions.

A FUZZY MODEL FOR THE QUANTIFICATION OF COST OF QUALITY BASED ON THE AGGREGATION OF INFORMATION

In this work a methodology will be developed, which it will substantially improve the quantification process of certain elements of Cost of Quality which companies cannot estimate through objective criteria. The methodological proposal for the quantification of these costs is based on the foundations of fuzzy logic. In particular an aggregation technique based on ordered weighted averaging is used establishing a new and original weighting factor: the level of Quality Management. This work presents an innovative development of the different tools that fuzzy logic provides for their use in the management and measurement of quality.

Application of Digital Image Processing to Detect Short-Circuit Turns in Power Transformers Using Frequency Response Analysis

Although a frequency response analysis (FRA) technique has been extensively used to detect mechanical deformation within power transformers, interpretation of FRA signature still needs a high level of expertise to identify and quantify faults as there is no FRA interpretation code widely accepted yet. All commercial frequency response analyzers can measure the magnitude and phase angle of the impedance, admittance, or transfer function of each phase in a wide frequency range; however, only magnitude is currently used for fault identification and quantification. This paper presents a novel approach for FRA signature interpretation by incorporating the FRA magnitude and phase plots into one polar plot that captures more features of the measured signal than the magnitude plot. Digital image processing-based techniques are employed to automate the fault identification and quantification process. To investigate the impact of transformer rating and size on the proposed technique, two transformers of different ratings and physical geometrical dimensions are simulated using 3-D finite-element analysis to emulate transformer real operation. Short-circuit of various fault levels is simulated at various locations within the high-voltage and low-voltage windings of the two transformer models and the obtained FRA polar plot signature for each case study is analyzed and compared with the healthy signature. Also, practical measurement is conducted to validate the simulation results. Results show that fault level along with fault location can be easily identified using the proposed polar plot signature along with the developed digital image processing technique.

Feature Learning applied to the Estimation of Tensile Strength at Break in Polymeric Material Design.

Several feature extraction approaches for QSPR modelling in Cheminformatics are discussed in this paper. In particular, this work is focused on the use of these strategies for predicting mechanical properties, which are relevant for the design of polymeric materials. The methodology analysed in this study employs a feature learning method that uses a quantification process of 2D structural characterization of materials with the autoencoder method. Alternative QSPR models inferred for tensile strength at break (a well-known mechanical property of polymers) are presented. These alternative models are contrasted to QSPR models obtained by feature selection technique by using accuracy measures and a visual analytic tool. The results show evidence about the benefits of combining feature learning approaches with feature selection methods for the design of QSPR models.

Quantitative phase-field crystal modeling of solid-liquid interfaces for FCC metals

This work deals with the quantification and application of the modified two-mode phase-field crystal model (M2PFC; Asadi and Asle Zaeem, 2015) for face-centered cubic (FCC) metals at their melting point. The connection of M2PFC model to the classical density functional theory is explained in this article. M2PFC model in its dimensionless form contains three parameters (two independent and one dependent) which are determined using an iterative procedure based on the molecular dynamics and experimental data. The quantification process and computer simulations are performed for Ni and Al as two case studies. The quantitative M2PFC models are used in series of numerical simulations to determine the two-phase FCC-liquid coexisting and the bulk properties at the melting points of Ni and Al. The calculated and predicted properties are the expansion in melting, elastic constants, solid-liquid interface free energy, and surface anisotropy, which are also compared with their available experimental or computational counterparts in the literature.

건설 VE 평가 신뢰도 향상 방안에 관한 연구

VE 평가에서 가치는 비용, 성능의 요소로서 구성이 되며, 이러한 요소들의 적절한 가치를 달성하기 위하여 정성적인 접근보다는 구체적인 수치로써 정량적으로 분석하는 특징을 가지고 있다. 현재 많은 국내 VE 평가에서 비용부분은 정량화하여 산정하고 있지만 기능부분은 정량화를 위한 체계적인 절차가 존재하지 않는다. 또한, VE 평가는 실무 성향이 강한 특성과 함께 과도한 정량화 및 객관화가 창의적인 의견 도출을 저하시킬 수 있다는 문제점들로 인해 과학적인 분석 방법론의 실제 적용에 한계가 존재하고 있다. 이에 본 연구에서는 실무적인 관점에서 VE 평가의 본질을 저해하지 않으며, VE 프로세스의 단순화와 객관화를 동시에 만족시킬 수 있는 VE 프로세스 단계별 개선 평가 방법론을 제시한다. The VE evaluation process, in which the value is composed of the cost and the function, should have a characteristic of quantitative analysis based on specific figures rather than qualitative approach. However, most of the VE evaluation performed domestically have a problem of having no systematic process of quantification of the function, even though the cost is estimated and analyzed quantitatively. Moreover, in addition to the tendency of strong practical experience, the VE evaluation has the problem of limited application of practical scientific analysis caused by declining the suggestion of creative opinions by over quantification or over objectification. This paper presents the suggestions for improvement of VE evaluation processes, which satisfies the aspects of simplification and objectification, without hindering the essence of the evaluation in the practical business point of view.

Exploring the Benefits of Early Contractor Involvement (ECI) and the Mechanism for Automated 5D BIM Quantification Process in Offsite Modular Construction

The UK Construction Industry through its Government Construction Strategy has recently been mandated to implement Level 2 Building Information Modelling (BIM) on public sector projects. This move, along with other initiatives is key to driving a requirement for 25% cost reduction (establishing the most cost-effective means) on. Other key deliverables within the strategy include reduction in overall project time, early contractor involvement, improved sustainability and enhanced product quality. Collaboration and integrated project delivery is central to the level 2 implementation strategy yet the key protocols or standards relative to cost within BIM processes is not well defined. As offsite construction becomes more prolific within the UK construction sector, this construction approach coupled with BIM, particularly 5D automated quantification process, and early contractor involvement provides significant opportunities for the sector to meet government targets. Early contractor involvement is supported by both the industry and the successive Governments as a credible means to avoid and manage project risks, encourage innovation and value add, making cost and project time predictable, and improving outcomes. The contractor is seen as an expert in construction and could be counter intuitive to exclude such valuable expertise from the pre-construction phase especially with the BIM intent of äóÖbuild it twiceäó», once virtually and once physically. In particular when offsite construction is used, the contractoräó»s construction expertise should be leveraged for the virtual build in BIM-designed projects to ensure a fully streamlined process. Building in a layer of automated costing through 5D BIM will bring about a more robust method of quantification and can help to deliver the 25% reduction in overall cost of a project. Using a literature review and a case study, this paper will look into the benefits of Early Contractor Involvement (ECI) and the impact of 5D BIM on the offsite construction process.

Electrochemical sensor based on reduced graphene oxide modified with palladium nanoparticles for determination of desipramine in urine samples

A nanostructured material based on palladium nanoparticles supported over reduced graphene has been synthesized, characterised and applied on the sensitivity analysis of antidepressant in urine samples. The morphology, structure, and electrochemical performance of the sensors were characterised by field emission gun scanning electron microscopy, X-ray diffraction, and cyclic voltammetry. The antidepressant quantification process was based on the reversible electrode oxidation of the electrochemically produced desipramine dimer, that appeared as oxidation process at +0.11V. Differential pulse voltammetry in phosphate buffer solution at pH 7.0 allowed the development of a method to determine desipramine levels in the range of 0.3–2.5μmolL−1, with limit of detection (LOD) estimated at 1.04nmolL−1(0.31μgL−1). The system was suitable on the detection of desipramine in urine samples.

Quantitative Cross-linking/Mass Spectrometry Using Isotope-labeled Cross-linkers and MaxQuant

The conceptually simple step from cross-linking/mass spectrometry (CLMS) to quantitative cross-linking/mass spectrometry (QCLMS) is compounded by technical challenges. Currently, quantitative proteomics software is tightly integrated with the protein identification workflow. This prevents automatically quantifying other m/z features in a targeted manner including those associated with cross-linked peptides. Here we present a new release of MaxQuant that permits starting the quantification process from an m/z feature list. Comparing the automated quantification to a carefully manually curated test set of cross-linked peptides obtained by cross-linking C3 and C3b with BS3 and isotope-labeled BS3-d4 revealed a number of observations: (1) Fully automated process using MaxQuant can quantify cross-links in our reference data set with 68% recall rate and 88% accuracy. (2) Hidden quantification errors can be converted into exposed failures by label-swap replica, which makes label-swap replica an essential part of QCLMS. (3) Cross-links that failed during automated quantification can be recovered by semi-automated re-quantification. The integrated workflow of MaxQuant and semi-automated assessment provides the maximum of quantified cross-links. In contrast, work on larger data sets or by less experienced users will benefit from full automation in MaxQuant.

136 COMPOSITIONALITY/NON-COMPOSITIONALITY OF IDIOMS: NON-NATIVE SPEAKERS’ CONSTRAINTS TO COMPREHENSION

<p>Informed by Jackendoff’s (1997) Representational Modularity (RM) Hypothesis which states that, similar to how people make sense of categories, they also systematically make sense of language. This study seeks to discover the way non-native speakers of English negotiate meaning when faced with idiomatic expressions that are modified either by a process of passivization or by a process of quantification; and whether idiom comprehension influence judgments of appropriateness of use of the modified expressions. Employing a researcher-made questionnaire that underwent content validity and reliability tests, the instrument was administered to four college freshman classes from four different higher education institutions. Findings reveal that a significant difference was found between group performance in the passivization and quantification tests through a one-sample test. However, an absence of a statistical relationship between the scores in the test and the participants’ judgment of appropriateness of use (spoken, written, spoken and written) was revealed by the statistical analysis.</p>

The material practices of quantification: Measuring ‘deprivation’ in the Amsterdam Neighbourhood Policy

The use of indicators and indexes in social policy, as part of evidence-based policy, is understood by governmentality scholars as ‘techniques of governance’. However, we know very little about how the process of quantification is enacted in the material practices that constitute social policy itself. In this article we focus on a particular quantified object: the ‘Normal Amsterdam Level’ (NAP), used in an Amsterdam Neighbourhood Policy programme. We follow the NAP from its birth, to its life and its afterlife. We show that the qualification ‘deprived’ calls forth a whole set of problematic arrangements which are lost in a process of quantification. We understand the NAP as a generative device that actively assembles and arranges the world. These assemblages are rendered ‘hard’ through semiotic, statistical and visual techniques that produce facts about targeted neighbourhoods in relation to a city-wide average, thus serving as evidence and legitimisation for policy interventions.

Quantitative assessment of chemical artefacts produced by propionylation of histones prior to mass spectrometry analysis.

Histone PTMs play a crucial role in regulating chromatin structure and function, with impact on gene expression. MS is nowadays widely applied to study histone PTMs systematically. Because histones are rich in arginine and lysine, classical shot-gun approaches based on trypsin digestion are typically not employed for histone modifications mapping. Instead, different protocols of chemical derivatization of lysines in combination with trypsin have been implemented to obtain "Arg-C like" digestion products that are more suitable for LC-MS/MS analysis. Although widespread, these strategies have been recently described to cause various side reactions that result in chemical modifications prone to be misinterpreted as native histone marks. These artefacts can also interfere with the quantification process, causing errors in histone PTMs profiling. The work of Paternoster V. etal. is a quantitative assessment of methyl-esterification and other side reactions occurring on histones after chemical derivatization of lysines with propionic anhydride [Proteomics 2016, 16, 2059-2063]. The authors estimate the effect of different solvents, incubation times, and pH on the extent of these side reactions. The results collected indicate that the replacement of methanol with isopropanol or ACN not only blocks methyl-esterification, but also significantly reduces other undesired unspecific reactions. Carefully titrating the pH after propionic anhydride addition is another way to keep methyl-esterification under control. Overall, the authors describe a set of experimental conditions that allow reducing the generation of various artefacts during histone propionylation.