Actual Drift Research Articles

Firms’ financing and debt maturity choices: An empirical analysis from the perspective of asset value dynamics

AbstractWe examine empirically the relationship between the dynamics of firm value and their financing and debt maturity choices. Theoretical studies show that the actual drift of firm value is a key determinant of firms’ leverage and debt maturity by incorporating the conflicts between undiversified insiders (managers) and well‐diversified outside investors. We empirically analyze firms’ incremental leverage and debt maturity choice important determinants of firms’ leverage and debt maturity, we find that the drift, or the expected return of total assets, does affect the firms’ choices of incremental leverage and debt maturity, as predicted by theoretical studies. Our results provide the evidence that the divergence of interests between undiversified managers and well‐diversified shareholders has significant impact on firms’ financing policies that are generally controlled by managers, and the resulting leverage and maturity choices may deviate from maximizing shareholders’ value.

REMOVED: Droplet size, velocity, and spray coverage from a magnetic-assisted sprayer

The increase in pesticide regulations, diminished pesticide options due to resistance concerns, and narrowing grower profit margins require each application to be optimised to reduce spray drift and enhance coverage. However, alternative strategies outside of increasing droplet size are needed as reductions in pest control have been observed. This research explored the potential of a magnetic-assisted sprayer (MAS) to aid in spray coverage and determine its impact on spray droplet size and velocity. The MAS minimally impacted spray droplet size characteristics across the four nozzle types tested (only five of twenty F-tests were statistically significant) and did not impact average or maximum droplet velocities when measured 51-cm from the nozzle compared to the conventional sprayer. Although statistically, the MAS increased droplet size by only 4.6 and 12.5% in two of 12 parameter instances compared to the conventional sprayer, there were indications it may reduce spray drift potential as the driftable fines (% of individual droplets measured with diameters less than 200 μm) were numerically less across all nozzle types tested. Across the five experiments, an improvement in spray coverage and deposition by the MAS compared to the conventional sprayer was only observed in one treatment from one experiment. Overall, the MAS minimally to negatively impacted the measured coverage and calculated deposition from water-sensitive paper. Future research is needed to measure actual spray drift from a MAS as well as to evaluate other potentially influential variables such as water quality, pesticide active ingredient, and plant species.

A New Dual-Mass MEMS Gyroscope Fault Diagnosis Platform.

MEMS gyroscopes are one of the core components of inertial navigation systems. The maintenance of high reliability is critical for ensuring the stable operation of the gyroscope. Considering the production cost of gyroscopes and the inconvenience of obtaining a fault dataset, in this study, a self-feedback development framework is proposed, in which a dualmass MEMS gyroscope fault diagnosis platform is designed based on MATLAB/Simulink simulation, data feature extraction, and classification prediction algorithm and real data feedback verification. The platform integrates the dualmass MEMS gyroscope Simulink structure model and the measurement and control system, and reserves various algorithm interfaces for users to independently program, which can effectively identify and classify seven kinds of signals of the gyroscope: normal, bias, blocking, drift, multiplicity, cycle and internal fault. After feature extraction, six algorithms, ELM, SVM, KNN, NB, NN, and DTA, were respectively used for classification prediction. The ELM and SVM algorithms had the best effect, and the accuracy of the test set was up to 92.86%. Finally, the ELM algorithm is used to verify the actual drift fault dataset, and all of them are successfully identified.

Machine learning-aided scenario-based seismic drift measurement for RC moment frames using visual features of surface damage

This paper presents a novel computer vision-based methodology for assessment of the seismic damage in reinforced concrete moment frames using visual characteristics of surface damage following an earthquake. An extensive collected database comprising 974 images associated with 256 cyclic-loaded damaged beam-column joints, providing a set of cracking and crushing progression with increasing the evolution of damage level, is collected and used for the development and validation of the methodology. Employing image processing techniques, the characteristics of the surface damage, including the cracking length and crushing areas, are measured and used in a scenario-based assessment for the seismic peak drift prediction. Based on the availability of the structural information, four scenarios are proposed using input parameters among cracking length, crushing areas, concrete compressive force, and the aspect ratio of the joint. The machine learning regression method is employed for developing nonlinear regression models for each scenario. The proposed models measure the seismic peak drift ratio during the earthquake excitation based on the visual damage features at the external surface of the components. Finally, the seismic peak drift ratio obtained by the proposed methodology of this paper can be used as an input engineering demand parameter in the existing seismic loss measurement frameworks. An example specimen at various drift ratios is also presented as a case study to evaluate the predicted versus actual experimental drift ratio.

Drift Potential Characteristics of a Flat Fan Nozzle: A Numerical and Experimental Study

This study explores the drift potential characteristics of a flat fan nozzle. The atomization and drift characteristics of fan-shaped pressure nozzles were studied at a spraying height of 0.6 m and a lateral wind speed of 0–6 m/s through a combination of computational fluid dynamics (CFD) analyses and wind tunnel experiments. The nozzle Lu 120-03 had a spraying pressure of 0.3 MPa. The results show that as the wind speed varies from 0 m/s to 6 m/s, the spray droplet spectrum also changes, and the droplet volume medium diameter increases. The cumulative droplet ratio and droplet spectral width of M oscillate within certain ranges. The amount of spray drift increases at higher wind speeds. The concentration of droplet deposition on the bottom of the wind tunnel gradually spreads downward in the wind direction. The determination coefficient R2 of the straight-line fitting of the drift characteristics is 0.982, which is highly consistent with the CFD simulation results. A CFD simulation-assisted wind tunnel test method, which is more convenient and repeatable than traditional field tests, is proposed to analyze the droplet spectrum and drift of Lechler series nozzles. The program can accurately simulate the actual drift and provide theoretical and data support for the optimization of atomization and drift characteristics of several types of flat fan nozzles under different spraying pressures and crosswinds in practical applications.

A real-time dynamic concept adaptive learning algorithm for exploitability prediction

Exploitability prediction has become increasingly important in cybersecurity, as the number of disclosed software vulnerabilities and exploits are soaring. Recently, machine learning and deep learning algorithms, including Support Vector Machine (SVM), Decision Tree, deep Neural Networks and their ensemble models, have achieved great success in vulnerability evaluation and exploitability prediction. However, they make a strong assumption that the data distribution is static over time and therefore fail to consider the concept drift problems due to the evolving system behaviours. In this work, we propose a novel consecutive batch learning algorithm, called Real-time Dynamic Concept Adaptive Learning (RDCAL), to deal with the concept drift and dynamic class imbalance problems existing in exploitability prediction. Specifically, we develop a Class Rectification Strategy (CRS) to handle the ‘actual drift’ in sample labels and a Balanced Window Strategy (BWS) to boost the minority class during real-time learning. Experimental results conducted on the real-world vulnerabilities collected between 1988 to 2020 show that the overall performance of classifiers, including Neural Networks, SVM, HoeffdingTree and Logistic Regression (LR), improves over 3% by adopting our proposed RDCAL algorithm. Furthermore, RDCAL achieves state-of-the-art performance on exploitability prediction compared with other concept drift algorithms.

Study of minimum requirements of confinement in concrete columns confined with WRG in moment resisting frames

The national concrete standard SNI 2847:2013 which refers to the ACI 318M-11 has not accommodated the influences of the axial load and deformation parameters as performance requirement, where both parameters are very critical to affect the required confining steel of concrete columns. This study presents the test results of reinforced concrete columns confined with WRG which were designed according to ACI standards. The test results were analyzed using several codes such as SNI 2847:2013, ACI 318M-14, CSA A23.3-04, and NZS 3101-06 standards. Furthermore, the minimum confinement equation is proposed for the design of columns confined with WRG, then it is also compared with selected confinement provisions. The study results showed that the equation for confining reinforcement adopted in the SNI 2847:2013 or ACI 318-11 is very conservative compared to other codes when applied to low axial load levels (≤ 0.25 Agf’c), but relatively less conservative or unsafe if the axial load level is greater than 0.3. From result of evaluation show that CSA A23.3-04 provide most conservative result for confinement design. The additional confinement design equations at ACI 318M-14 has been improve confinement design of ACI Code. Compared with SNI requirements, which do not depend on the level of axial load on the column, the equations proposed here would allow reduced confining reinforcement for columns with higher axial load. Overall, the proposed equation presents the best correlation to actual drift capacity of columns, and in addition it can be used for columns reinforced with WRG-transverse reinforcement having a yield strength higher than 500 MPa. The study also provides the recommendation for further refinement of SNI 2847 in the future related to the requirement of WRG confinement in concrete columns of Special Moment Frames in highly seismic regions.

Force Based Design and Direct Displacement Based Design for Dual System Structure

The Force Based Design (FBD) and the Direct Displacement-Based Design (DDBD) are methods for designing seismic-resistant buildings. Building structures designed, are expected to be suitable with the purpose and usefulness of a building. For this reason, this study compares the performance of dual system structures using the DDBD and FBD methods that aim to prove better performance with consideration of safety against users during an earthquake. This research method uses design analysis method to compare the value of the base shear force, reinforcement ratio, and performance level using software for static nonlinear pushover analysis. The results showed the value of the base shear force x direction of the DDBD method was 17.57% smaller than the FBD method, whereas for the y direction the DDBD value was greater than 9.38% of the FBD. The value of the reinforcement ratio of the beam, column and shear wall results is greater DDBD than FBD. The actual drift of the DDBD and FBD methods is slightly different. So that both are at the same level of performance, namely damage control. The performance level has not reached the performance target of life safety design in DDBD, but the structure has met the level performance requirements for offices.

Drift angle compensation-based adaptive line-of-sight path following for autonomous underwater vehicle

The aim of this study is to solve the problem of poor tracking in autonomous underwater vehicle (AUVs) that are operating based on traditional line-of-sight (LOS) method when tracking different paths in a complex marine environment. An adaptive-LOS (ALOS) guidance law with drift angle compensation is proposed, and is employed to calculate the AUV’s desired course (direction of velocity) and heading. First, an appropriate look-ahead distance is derived by the ALOS guidance law in consideration of the predefined path curvature, real-time tracking error and speed of the AUV. Subsequently, proper compensation is provided with respect to the actual drift angle. Compared with traditional LOS operation, this method flexibly adjusts to a suitable look-ahead distance while considering many related factors, providing a better path following performance. Both simulation and experimental results are presented to validate the effectiveness of this method.

Correcting for magnetic field drift in magic-angle spinning NMR datasets.

Magnetic field drift during magic angle spinning (MAS) NMR measurements is detrimental to the spectra, causing broadening of lines and distortion of lineshapes, especially in high-quality samples with linewidths of less than 0.1 ppm. We report that a simple linear correction for magnet drift can be used to improve the quality of proton detected MAS NMR measurements. Despite the fact that the magnetic field of superconducting magnets changes in a non-linear fashion, we find that when data acquisition is sufficiently short, a linear correction is a good approximation to the actual field drift. We used a script written in the C programming language for linear drift correction of multidimensional datasets (2D, 3D, 4D), which can be executed directly from Bruker Topspin. A second script allows datasets to be subdivided into arbitrarily short measurements, individually corrected, and concatenated before processing.

Optimizing Aircraft Utilization for Herbicide Application by Evaluation of Herbicide Spray Drift in West Bank Berbice Guyana South America

Aerial herbicide drift caused mainly by weather and climatic conditions may be the most challenging problem facing farmers. Spray drift reaching off-target areas can destroy sensitive crops; pollute air and water resources thus causing serious health problems to humans and animals. Nonetheless, buffer zones of 500 meters are indicated to limit these negative impacts of spray drift. The Guyana Sugar Corporation controls weeds and ripens canes by aerial herbicide application. The corporation, in the 1990s, instituted 750-metre buffer zones, which greatly affected the optimization of aircraft use in herbicide application and ripening of cane. This study tested the utility of the 750-meters buffer zone on Rose Hall, Albion and Blairmont Sugar estates. The actual drift distances were determined within 06:00 hours and 09:00 hours for 9 herbicide applications. Drift patterns associated with the three 1- hour time periods were correlated with prevailing weather conditions to determine optimal flying periods for the locations. The droplets concentration per sensitive paper was collected for each period. It was noted that the drift is less with the distance from the field up to 510 m; thereafter the number of droplets was 2 or less per sensitive paper. The wind speed increases as time goes up, thus increasing the drift. The windward side is where 510 m were recorded to have droplets of 2 and nil at 510 m from the opposite side.

Despair as Defiance: Kierkegaard’s Definitions in “The Sickness unto Death”

Abstract How are we to read and how translate the brief formulae with which ‟The Sickness unto Death” introduces two forms of ‛authentic despair’? In response to Michael Theunissen’s claim that, to conform with the actual drift of Kierkegaard’s thought, the first of the two forms of despair should be given priority, an alternative reading that conforms with the published ordering is defended on the strength of both the text itself and the development of Kierkegaard’s thought up to the time of its writing. The further aim, shared with Theunissen, is to widen the basis for assessing the continuing relevance of Kierkegaard’s analysis of despair.

Protocol with self‐adaptive GB for BANs

Body area networks (BANs) are systems of wearable computing devices for long-term monitoring of personal health care. BAN is an emerging technology for the worldwide ageing population. In the BAN system, the transceiver is the most energy-consuming part of a sensor node and radio transmission in the vicinity of the human body is highly lossy and inefficient. Therefore, the energy of the sensor node constraints the life cycle and quality of service of the network; consequently, low-cost protocol shaves attracted wide interest. This study proposes a frame structure model of a self-adaptive guard band protocol, which introduces a GB in each time slot according to the allowed maximum time drift of the crystal, adaptively adjusts the value of the GB based on the actual time drift, and then ensures that the node simultaneously maintains the sleeping state and synchronisation with the coordinator during beacon transmission, thus reducing the energy consumption.

An Alternative Option to Portfolio Rebalancing

Portfolio managers, whether running a passive or an active strategy, typically select target weights on the various asset classes and securities they hold. The prime example is choosing the mix between stocks and bonds. But as market prices evolve, actual weights drift away from the targets. This leads to tracking error and transaction costs in order to rebalance positions to the desired levels. Rebalancing entails selling assets that have gone up in value and increasing exposure to those whose prices have dropped. As Israelov and Tummala point out, this is how a short position in a call option behaves, and they show how to design a hedging strategy based on writing calls that offsets much of the basis risk in trying to run a portfolio with fixed asset weights. An empirical illustration shows that their proposed overlay strategy would have performed well historically in reducing unintended timing risk in a 60/40 stock/bond portfolio. An additional benefit of the plan is that by selling options, it harvests the volatility risk premium embedded in their prices, which enhances returns at the same time risk is being reduced.

Accurate Sample Time Reconstruction of Inertial FIFO Data.

In the context of modern cyber-physical systems, the accuracy of underlying sensor data plays an increasingly important role in sensor data fusion and feature extraction. The raw events of multiple sensors have to be aligned in time to enable high quality sensor fusion results. However, the growing number of simultaneously connected sensor devices make the energy saving data acquisition and processing more and more difficult. Hence, most of the modern sensors offer a first-in-first-out (FIFO) interface to store multiple data samples and to relax timing constraints, when handling multiple sensor devices. However, using the FIFO interface increases the negative influence of individual clock drifts—introduced by fabrication inaccuracies, temperature changes and wear-out effects—onto the sampling data reconstruction. Furthermore, additional timing offset errors due to communication and software latencies increases with a growing number of sensor devices. In this article, we present an approach for an accurate sample time reconstruction independent of the actual clock drift with the help of an internal sensor timer. Such timers are already available in modern sensors, manufactured in micro-electromechanical systems (MEMS) technology. The presented approach focuses on calculating accurate time stamps using the sensor FIFO interface in a forward-only processing manner as a robust and energy saving solution. The proposed algorithm is able to lower the overall standard deviation of reconstructed sampling periods below 40 s, while run-time savings of up to 42% are achieved, compared to single sample acquisition.

Quantifying panel zone effect on deflection amplification factor

SummaryDrift is a dominant feature in tall‐building design and can dictate the selection of structural systems. Because a reliable estimate of actual drifts is crucial for controlling structural damage, estimating drift considering intricate details seems noteworthy. In order to estimate story drifts during massive quakes, seismic design provisions generally specify a deflection amplification factor (Cd) to amplify elastic design drifts. In most of these codes, the amount of Cd is calculated from line‐element models without considering panel zone effects, despite the panel zone intensifying the story drift considerably. Therefore, the effect of panel zone on the story drift and Cd has been investigated in the current paper. Because Cd is independent of the number of stories, 4‐story frames, as benchmarks for special steel moment frames, with different thicknesses of the panel zone, are used. The effect of panel zone is provided as a correction factor for Cd. The results show that the panel zone should be considered in the analytical models; otherwise, the story drift will be underestimated up to 35%. Finally, a relation has been derived to consider panel zone effects on Cd, as a function of the panel zone thickness.

An optimized protocol for QoS and energy efficiency on wireless body area networks

Body area networks (BAN) are at the forefront of technologies for long-term monitoring of personal healthcare, which is intended be an effective strategy to address the aging population worldwide. The transceiver is the most energy-consuming part of a sensor node, and radio transmission in the vicinity of the human body is highly lossy and inefficient. Therefore, the energy of the sensor node constrains the life cycle and quality of service (QoS) of the network; consequently, low-cost protocol shave attracted wide interest. This paper proposes a frame structure model of a self-adaptive guard band (SAGB) protocol, which introduces a guard band (GB) in each time slot according to the allowed maximum time drift of the crystal, adaptively adjusts the value of the GB based on the actual time drift, and then ensures that the node simultaneously maintains the sleeping state and synchronization with the coordinator during beacon transmission, thus reducing the energy consumption.

Factors associated with atypical postoperative drift following surgery for consecutive exotropia

To evaluate the associations of clinical and surgical factors with atypical postoperative drift following surgery for consecutive exotropia. A total of 66 patients with consecutive exotropia (≥10Δ at distance), after historical surgery for esotropia were retrospectively identified at a tertiary medical center. All patients underwent unilateral lateral rectus recession (on adjustable suture) with medial rectus advancement and/or resection. Immediate postoperative target angle was 4Δ-10Δ of esotropia at distance, anticipating mild postoperative exodrift. Actual postoperative drift was calculated as change in distance deviation from immediately postadjustment to 6weeks. Typical drift was defined as 0Δ-9Δ of exodrift. Excessive exodrift was defined as ≥10Δ. Esodrift was defined as 1Δ or more. Univariate and multiple logistic regression analyses were performed to evaluate for associations with a wide range of clinical and surgical factors. Overall there was a median exodrift (4Δ, quartiles 0Δ-10Δ). Of the 66 patients, 18 (27%) showed excessive exodrift; 15 (23%), esodrift. In multiple logistic analyses, larger preoperative distance exodeviation was associated with excessive exodrift (P=0.01), and non-normal medial rectus attachment status (abnormal [stretched scar, pseudo-tendon], attached to pulley, or behind pulley) was associated with esodrift (P=0.02). Approximately half of patients show atypical drift following unilateral surgery for consecutive exotropia, with larger preoperative distance exodeviation associated with exodrift and non-normal medial rectus muscle status with esodrift. Knowing these associations may help when counseling patients regarding surgical outcomes.

On the utility of the ionosonde Doppler‐derived EXB drift during the daytime

AbstractVertical EXB drift measured using the ionosonde Doppler sounding during the daytime suffers from an underestimation of the actual EXB drift because the reflection height of the ionosonde signals is also affected by the photochemistry of the ionosphere. Systematic investigations have indicated a fair/good correlation to exist between the C/NOFS and ionosonde Doppler‐measured vertical EXB drift during the daytime over magnetic equator. A detailed analysis, however, indicated that the linear relation between the ionosonde Doppler drift and C/NOFS EXB drift varied with seasons. Thus, solar, seasonal, and also geomagnetic variables were included in the Doppler drift correction, using the artificial neural network‐based approach. The RMS error in the neural network was found to be smaller than that in the linear regression analysis. Daytime EXB drift was derived using the neural network which was also used to model the ionospheric redistribution in the SAMI2 model. SAMI2 model reproduced strong (weak) equatorial ionization anomaly (EIA) for cases when neural network corrected daytime vertical EXB drift was high (low). Similar features were also observed in GIM TEC maps. Thus, the results indicate that the neural network can be utilized to derive the vertical EXB drift from its proxies, like the ionosonde Doppler drift. These results indicate that the daytime ionosonde measured vertical EXB drift can be relied upon, provided that adequate corrections are applied to it.

Application of steel equivalent constitutive model for predicting seismic behavior of steel frame

In order to investigate the accuracy and applicability of steel equivalent constitutive model, the calculated results were compared with typical tests of steel frames under static and dynamic loading patterns firstly. Secondly, four widely used models for time history analysis of steel frames were compared to discuss the applicability and efficiency of different methods, including shell element model, multi-scale model, equivalent constitutive model (ECM) and traditional beam element model (especially bilinear model). Four-story steel frame models of above-mentioned finite element methods were established. The structural deformation, failure modes and the computational efficiency of different models were compared. Finally, the equivalent constitutive model was applied in seismic incremental dynamic analysis of a ten-floor steel frame and compared with the cyclic hardening model without considering damage and degradation. Meanwhile, the effects of damage and degradation on the seismic performance of steel frame were discussed in depth. The analysis results showed that: damages would lead to larger deformations. Therefore, when the calculated results of steel structures subjected to rare earthquake without considering damage were close to the collapse limit, the actual story drift of structure might already exceed the limit, leading to a certain security risk. ECM could simulate the damage and degradation behaviors of steel structures more accurately, and improve the calculation accuracy of traditional beam element model with acceptable computational efficiency.