Advanced Measurement Approach Research Articles

A measurement method of in-bore projectile motion acceleration based on bottom pressure correction

Due to factors such as high temperatures, elevated pressures, and severe high-frequency shocks in the bore, there is considerable noise interference in acceleration test signals. This makes it challenging to accurately measure projectile motion acceleration using existing methods. To address this issue, we propose an advanced measurement approach that uses bottom pressure correction. Our model suggests a significant correlation between projectile motion acceleration and thrust. By utilizing the correlations between bottom pressure and motion acceleration in both temporal and frequency domains, we can improve the accuracy of acceleration measurements. Based on these insights, we have developed a novel testing system that synchronously measures bottom pressure and acceleration, using bottom pressure as a corrective mechanism for the measured acceleration signals. Empirical results show that the maximum relative error in peak motion acceleration is only 4.86%, demonstrating the effectiveness of our proposed method.

Opening up their values: how CEOs conservation and openness to change impact downsizing decisions

PurposeBased on the theory of basic human values, this study aims to examine the impact of CEO conservation (i.e. security, conformity and tradition) and openness to change (i.e. self-direction, stimulation and hedonism) values on one of the most conflictual decisions inside a firm: workforce downsizing.Design/methodology/approachThe hypothesis testing was done in the context of all workforce downsizing decisions made by German companies (and their CEOs) listed on the German Prime-Index between 2005 and 2019. A software-based psycholinguistic assessment of various sources of CEO communications was conducted to tap into their underlying values.FindingsTobit regression analysis confirms that CEO conservation and openness-to-change values impact the severity of workforce downsizing. Namely, the higher the CEO conservation values, the lower the downsizing severity (i.e. employees dismissed in relation to overall workforce). In contrast, the higher the CEO openness to change values, the higher the downsizing severity.Originality/valueAgainst prior research that has centered around political ideology as a proxy to understand the mechanisms through which values impact strategic decisions, the present study employs advanced measurement approaches to assess the general impact of CEO values on critical firm decisions. As such, the study contributes to upper echelons research by offering a new perspective on how CEO values impact critical firms' decisions.

Application of the radial basis function in solving an operational risk management model: investigating the probability of bank survival with risk reserves

Operational risk is one of the influential risks identified by banking practitioners, and as the international banking supervisor, the Basel Committee on Banking Supervision has paid special attention to it. There are various methods for measuring and managing this type of banking risk (eg, the advanced measurement approach). Using the radial basis function approach, we compute the probability of bank survival using a partial Volterra integrodifferential equation. Given the importance of operational risk in financial institutions, especially banks, we examine a mathematical model of this risk and solve it using numerical methods. Also, by considering the impact of the bank’s probability of survival on the amount of risk reserves, we investigate the effect of fluctuation in risk reserves on the probability of survival of an organization. To complete the investigation, we calculated the amount of risk storage required to achieve the desired probability of survival.

X-ray computed tomography for advanced geometrical measurements of metal powders and enhanced surface topography analyses of additively manufactured parts

Metal powder has a significant influence on the quality and performance of laser powder bed fusion (LPBF) processes and products. A key requirement for metal powder is to have shape and size distribution designed to have adequate flowability, packing behavior and laser absorption, as well as to fabricate parts with acceptable density, surface finish and mechanical properties. Accurate three-dimensional (3D) characterizations of powder particles are fundamental to enable relevant research, for example on powder reuse and material waste reduction in LPBF. This work studies advanced measurement approaches, based on X-ray computed tomography (CT), for the 3D geometrical characterization of powder particles. The work includes comparisons with conventional powder characterization methods, considering different materials and powder morphologies. Results show the potential of the CT-based approaches to provide accurate and complete 3D powder geometrical measurements, and to exploit the obtained results for the enhancement of surface topography analyses and LPBF development. • Accurate 3D characterizations of metal powder are fundamental to improve the LPBF process. • Comparison of characterization methods for different materials and morphologies. • X-ray computed tomography enables a complete 3D geometrical characterization of powder. • CT powder characterization is exploited to enhance surface topography analyses and LPBF development.

Advanced and Complex Energy Systems Monitoring and Control: A Review on Available Technologies and Their Application Criteria.

Complex energy monitoring and control systems have been widely studied as the related topics include different approaches, advanced sensors, and technologies applied to a strongly varying amount of application fields. This paper is a systematic review of what has been done regarding energy metering system issues about (i) sensors, (ii) the choice of their technology and their characterization depending on the application fields, (iii) advanced measurement approaches and methodologies, and (iv) the setup of energy Key Performance Indicators (KPIs). The paper provides models about KPI estimation, by highlighting design criteria of complex energy networks. The proposed study is carried out to give useful elements to build models and to simulate in detail energy systems for performance prediction purposes. Some examples of energy complex KPIs based on the integration of the Artificial Intelligence (AI) concept and on basic KPIs or variables are provided in order to define innovative formulation criteria depending on the application field. The proposed examples highlight how modeling a complex KPI as a function of basic variables or KPIs is possible, by means of graph models of architectures.

Capital Requirements to Cover Operational Risk in Financial Institutions of Emerging Markets. A Gaussian Copula Model

Context: Advanced Measurement Approach (AMA) has been the umbrella to identify the models used for modeling the capital to cover Operational Risk (Total Operational Value at Risk, OpVaR) in financial institutions in developed countries. The Loss Distribution Approach (LDA) has been the most popular model used by international banks for OpVaR calculation. However, the operational losses frequently have multivariate dependences that are not accounted for in the LDA. This paper applies a Gaussian copula to model the multivariate dependences in operational losses. Method: Two models were compared to estimate capital requirement for operational risk. Model (i) is the standard LDA model (BCBS 2004). Model (ii) incorporates a multivariate Gaussian copula into the LDA to model multivariate dependence between operational losses (severities). This research analyzes an operational loss data set, SAS® Operational Risk Global Data (SAS OpRisk Global Data), in order to model operational risk at financial institutions in emerging markets between 1990 and 2013. Results: The impact of Model (ii) was evaluated on the estimates of the total regulatory capital for operational risk and compared with the one predicted by (i). The results confirm the existence of diversification benefit up to 33%. Conclusions: Modeling explicitly the multivariate dependence between operational losses has a clear impact on capital requirement for institutions in emerging markets. The implementation of a Gaussian copula into the LDA model provides a sophisticated tool to estimate operational risk capital in emerging markets, as well as the possibility for diversification benefit. Acknowledgements: To SAS for providing the database used in this research.

Computational analysis of welding radial deformation of typical pressure cylindrical shell with ring stiffener

We report on the evaluation of the radial deformation caused by the welding process on a typical pressure cylindrical shell with ring stiffeners. Welding experiments on butt and fillet welding were conducted beforehand, and temperature-dependent material properties were considered. The out-of-plane welding distortion and residual stress were measured using a three-coordinate measuring machine and X-ray diffraction, respectively. Effective thermal elastic plastic FE analysis based on parallel computation technology was performed to examine the mechanical behaviors. Computed results were validated by comparison with experimental measurements. Welding inherent deformations of the examined butt and fillet joints were then evaluated by integrating computed plastic strains. The elastic FE analysis, with welding inherent deformation as mechanical loading, was employed to examine the dimensional variation of the considered pressure cylindrical shell. The influence of ring stiffener on welding radial deformation was also discussed. Moreover, the application of welding sequence modification and inverse deformation was numerically examined with the proposed elastic FE analysis to reduce the welding radial deformation and enhance the fabrication accuracy. • Thermal and mechanical behaviors of welding experiments were holistically examined with advanced measurement approach. • TEP FE analysis was employed to represent welding response, and computed results have good agreement with measurement. • Ring stiffener has significant influence on dimensional accuracy by elastic FE analysis with welding inherent deformation. • Welding sequence and inverse deformation have significant effect to prevent radial deformation of pressure cylindrical shell.

Quantifying Subcellular Growth Dynamics using Quantitative Phase Imaging

Unregulated growth has a drastic effect on the health of organisms. Unbalanced biomass production and degradation within cells can lead to diseases including diabetes, cancer, and organ hypertrophy. Understanding such growth dysregulations and the development of treatments requires understanding growth. Average growth of cell populations can be measured based on proliferation, while more advanced growth measurement approaches study single cells and can extract cell-to-cell heterogeneity information. We have developed a technique that extends further to measure localization of growth within single cells, using quantitative phase imaging (QPI) microscopy technique.QPI measures the phase shift of light as it passes through a sample, which is linearly proportional to cell biomass in the light path. As a result, QPI data show the changing biomass distribution within cells. Cell growth is commonly measured by QPI as the rate of change of biomass in whole cells over time. This approach has previously been shown to rapidly measure single cell growth and growth inhibition by drugs or therapies. Our work expands the scope of QPI further with an algorithm that utilizes the biomass distribution data to output a discretized subcellular growth map.Our approach is based on solution of a mass balance that considers biomass advection in subcellular regions. Observed changes in mass within each region of the cell can be caused by either advection of mass or biosynthesis/degradation. We can directly measure the change in biomass in each subcellular volume using QPI. We then measure the velocity of mass movement using particle image velocimetry on QPI images. Combining these two allows us to measure the amount of biosynthesis in each subcellular region. Our approach visualizes subcellular growth dynamics in real-time and quantify intracellular growth inhibition in response to drug treatments targeting cell growth mechanisms.

Measurement Optimization for Orientation Tracking Based on No Motion No Integration Technique

The main goal of this article is to fully explore the capability of the “No Motion No Integration” (NMNI) technique for the optimization of the Euler angles in orientation tracking. The gyroscope is the critical component in the inertial measurement unit for angle detection in Industry 4.0. An upgraded NMNI model is introduced to remove the drift of the gyroscope significantly for the advanced measurement approach for roll, pitch, and yaw. A model of threshold update is implemented into the NMNI algorithm to compensate for the increased offset of temperature. This preprocessing method is applied to the Madgwick filter and Mahony filter to acquire the optimal performance. The experiments were carried out by using a low-cost platform equipped with microelectromechanical system sensors. A pan-tilt unit with high accurate positioning was used to move the sensors and obtain a reference angle during both static and dynamic experiments. A substantial improvement was clearly demonstrated after the optimization process. The measurements of the Euler angles have minimized noise and tracks around the reference points properly. The results show strong competition from both fusion filters where the fused Mahony accomplishes more stable less variation in roll and pitch, but the fused Madgwick shows more precision in heading/yaw estimation.

ANALISA PENGUKURAN BEBAN MODAL RISIKO OPERASIONAL METODE BASIC INDICATOR APPROACH (BIA) DAN ADVANCE MEASUREMENT APPROACH (AMA) DI BANK EFG

This study aims to compare the magnitude of operational risk losses between the Basic Indicator Approach (BIA) method, and the loss distribution model in the Advanced Measurement Approach (AMA) approach so as to provide a more realistic picture for banks to determine the operational risk capital burden that must be provided based on the causes Operational risks are as follows Internal Process, Human and External Events. Measurement of operational risk capital burden by the AMA method is the determination of frequency of loss distribution, determination of severity of loss distribution, testing with goodness of fit test, then compilation of aggregated loss distribution, calculation of Operational Value at Risk (OpVar), testing the model with back testing and comparison of capital adequacy from the results of the calculation of the Basic Indicator Approach (BIA) and the Advance Measurement Approach (AMA). The results of research based on the BIA require an operational risk capital cost of Rp.291,652,000,000. The results of the research on the AMA approach use the frequency of loss distribution parameter for the internal causes of the process with a Geometric distribution of 0.17561, while for the human cause of 0.08511, for the cause of external events amounting to 0.83721. Determination of Frequency of Loss Distribution using Goodness of Fit for internal processes, people and external events. The results of the Operational Value at Risk (OpVar) with a geometric distribution pattern, then the maximum loss that can arise due to human factors is Rp.24,114,480,096, -, for internal process factors of Rp.6,010,929,367, whereas for external causes for Rp. 2,161,092,909. In total operational risk capital needs through the AMA method of Rp. 32,286,502,372.

RISIKO OPERASIONAL BANK DAN PERMODELANNYA

Managing bank’s operational risks becoming an important feature of sound risk management practice in modern financial markets. The most important types of operational risk involve breakdown in internal controls and corporate governance, which could lead to financial losses through fraud, error or failure to perform. Development of statistic has accelarated banks to create internal operational risk models in different ways. Although those models created in different ways, they surely use the pattern of risk management that is developed by Basel Committee on Banking Supervision. Basel Committee on Banking Supervision has proposed three increasingly sophisticated approaches of operational risk, i.e basic indicator approach, standardized approach and advanced measurement approach. Applying those approaches will help banks to eliminate the operational risk, that will lead them to a better intermediation process.

Should the Advanced Measurement Approach for Operational Risk be Discarded? Evidence from the Chinese Banking Industry

The Basel Committee on Banking Supervision (BCBS) states that in addition to the fact that it lacks simplicity, the Advanced Measurement Approach (AMA) must be discarded because the flexibility of AMAs does not narrow as envisioned prior. This paper discusses whether this judgment of the BCBS holds for the Chinese banking industry. We first review the development of operational risk data collection and AMAs in China over the past decade. Then, capital requirement results for Chinese banks based on these datasets and approaches are summarized and analyzed. It is shown that along with the accumulation of operational risk data and the refinement of AMAs, operational risk results for the Chinese banking industry have shown a clear trend of convergence that is exactly opposed to judgments of the BCBS. Therefore, the removal of the AMA from regulatory frameworks may not be reasonable.

Evaluating the AMA and the new standardized approach for operational risk capital

Seven desirable properties for a capital framework are proposed, and the advanced measurement approach (AMA) and the new standardized approach (NSA) for operational risk capital are evaluated relative to them. The AMA is vulnerable to gaming, complex, and lacks comparability. The NSA lacks risk sensitivity and is unlikely to be appropriately conservative for US banks.

The Cascade Bayesian Approach: Prior Transformation for a Controlled Integration of Internal Data, External Data and Scenarios

According to the last proposals of the Basel Committee on Banking Supervision, banks or insurance companies under the advanced measurement approach (AMA) must use four different sources of information to assess their operational risk capital requirement. The fourth includes ’business environment and internal control factors’, i.e., qualitative criteria, whereas the three main quantitative sources available to banks for building the loss distribution are internal loss data, external loss data and scenario analysis. This paper proposes an innovative methodology to bring together these three different sources in the loss distribution approach (LDA) framework through a Bayesian strategy. The integration of the different elements is performed in two different steps to ensure an internal data-driven model is obtained. In the first step, scenarios are used to inform the prior distributions and external data inform the likelihood component of the posterior function. In the second step, the initial posterior function is used as the prior distribution and the internal loss data inform the likelihood component of the second posterior function. This latter posterior function enables the estimation of the parameters of the severity distribution that are selected to represent the operational risk event types.

An integrated inverse adaptive neural fuzzy system with Monte-Carlo sampling method for operational risk management

Operational risk refers to deficiencies in processes, systems, people or external events, which may generate losses for an organization. The Basel Committee on Banking Supervision has defined different possibilities for the measurement of operational risk, although financial institutions are allowed to develop their own models to quantify operational risk. The advanced measurement approach, which is a risk-sensitive method for measuring operational risk, is the financial institutions preferred approach, among the available ones, in the expectation of having to hold less regulatory capital for covering operational risk with this approach than with alternative approaches. The advanced measurement approach includes the loss distribution approach as one way to assess operational risk. The loss distribution approach models loss distributions for business-line-risk combinations, with the regulatory capital being calculated as the 99,9% operational value at risk, a percentile of the distribution for the next year annual loss. One of the most important issues when estimating operational value at risk is related to the structure (type of distribution) and shape (long tail) of the loss distribution. The estimation of the loss distribution, in many cases, does not allow to integrate risk management and the evolution of risk; consequently, the assessment of the effects of risk impact management on loss distribution can take a long time. For this reason, this paper proposes a flexible integrated inverse adaptive fuzzy inference model, which is characterized by a Monte-Carlo behavior, that integrates the estimation of loss distribution and different risk profiles. This new model allows to see how the management of risk of an organization can evolve over time and it effects on the loss distribution used to estimate the operational value at risk. The experimental study results, reported in this paper, show the flexibility of the model in identifying (1) the structure and shape of the fuzzy input sets that represent the frequency and severity of risk; and (2) the risk profile of an organization. Therefore, the proposed model allows organizations or financial entities to assess the evolution of their risk impact management and its effect on loss distribution and operational value at risk in real time.

Evaluation the AMA and the New Standardized Approach for Operational Risk Capital

Seven desirable properties for a capital framework are proposed, and the Advanced Measurement Approach (AMA) and the new standardized approach (NSA) for operational risk capital are evaluated relative to them. The AMA is vulnerable to gaming, complex, and lacks comparability. The NSA lacks risk sensitivity and is unlikely to be appropriately conservative for US banks.

Forward-looking and incentive-compatible operational risk capital framework

The Advanced Measurement Approach (AMA) to operational risk capital is vulnerable to gaming, complex, and lacks comparability. The Standardized Measurement Approach (SMA) to operational risk capital lacks risk sensitivity and is unlikely to be appropriately conservative for US banks. An alternative framework is proposed that addresses the weaknesses of these approaches by relying on an incentive-compatible mechanism to elicit forward-looking projections of loss exposure.

Forward-Looking and Incentive-Compatible Operational Risk Capital Framework

The Advanced Measurement Approach (AMA) to operational risk capital is vulnerable to gaming, complex, and lacks comparability. The Standardized Measurement Approach (SMA) to operational risk capital lacks risk sensitivity and is unlikely to be appropriately conservative for US banks. An alternative framework is proposed that addresses the weaknesses of these approaches by relying on an incentive-compatible mechanism to elicit forward-looking projections of loss exposure.

Forward-Looking and Incentive-Compatible Operational Risk Capital Framework

The Advanced Measurement Approach (AMA) to operational risk capital is vulnerable to gaming, complex, and lacks comparability. The Standardized Measurement Approach (SMA) to operational risk capital lacks risk sensitivity and is unlikely to be appropriately conservative for US banks. An alternative framework is proposed that addresses the weaknesses of these approaches by relying on an incentive-compatible mechanism to elicit forward-looking projections of loss exposure.

Forward-looking and Incentive-compatible Operational Risk Capital Framework

The Advanced Measurement Approach (AMA) to operational risk capital is vulnerable to gaming, complex, and lacks comparability. The Standardized Measurement Approach (SMA) to operational risk capital lacks risk sensitivity and is unlikely to be appropriately conservative for US banks. An alternative framework is proposed that addresses the weaknesses of these approaches by relying on an incentive-compatible mechanism to elicit forward-looking projections of loss exposure.