599 research outputs found
The association between accounting and market-based risk measures
The paper derives operating and financial measures of leverage and tests their association with market based measures of equity risk. It is the first such study to use purely accounting-based data to derive the leverage measures. In line with previous literature it conducts a new test on the relative importance of operating and financial leverage. The results suggest that operating costs have a greater impact.Systematic risk; Operating Leverage; Financial Leverage; Beta; Risk Premium; United Kingdom
Numerical analysis of subsoil-reinforced concrete slab interaction
This article presents the numerical modeling of
interaction between a reinforced concrete slab and
subsoil using ABAQUS. Subsoil was simulated as both
homogeneous half-space and inhomogeneous half-space.
Reinforcement bars in the concrete slab were accurately
modelled allowing capturing a precise deformation
profile of the slab in interaction with subsoil. Input data
for numerical analysis were adopted from a published
work. Results of the study were verified on the basis of
comparison with those of the previous study
A STUDY ON POWER OUTPUT OF HORIZONTAL-AXIS WIND TURBINES UNDER RAIN
The power of the wind turbine are significantly affected by the air conditions of the operating environment. Rain is a widespread phenomenon in many parts of the world especially in Vietnam, so exploring its effect on the power of wind turbines will provide valuable insights into the design of a new wind tower. In this paper, a method and a model is developed to estimate the effect of precipitation by simulating the actual physical processes of the rain drops forming on the surface of the blades of horizontal-axis wind turbines (HAWT), thereby determining optimal wetness, then power and performance respectively. Consequently, it makes a contribution to operation and control strategies for horizontal-axis wind turbines
Comparative study on the performance of face recognition algorithms
Facial and object recognition are more and more applied in our life. Therefore, this field has become important to both academicians and practitioners. Face recognition systems are complex systems using features of the face to recognize. Current face recognition systems may be used to increase work efficiency in various methods, including smart homes, online banking, traffic, sports, robots, and others. With various applications like this, the number of facial recognition methods has been increasing in recent years. However, the performance of face recognition systems can be significantly affected by various factors such as lighting conditions, and different types of masks (sunglasses, scarves, hats, etc.). In this paper, a detailed comparison between face recognition techniques is exposed by listing the structure of each model, the advantages and disadvantages as well as performing experiments to demonstrate the robustness, accuracy, and complexity of each algorithm. To be detailed, let’s give a performance comparison of three methods for measuring the efficacy of face recognition systems including a support vector machine (SVM), a visual geometry group with 16 layers (VGG-16), and a residual network with 50 layers (ResNet-50) in real-life settings. The efficiency of algorithms is evaluated in various environments such as normal light indoors, backlit indoors, low light indoors, natural light outdoors, and backlit outdoors. In addition, this paper also evaluates faces with hats and glasses to examine the accuracy of the methods. The experimental results indicate that the ResNet-50 has the highest accuracy to identify faces. The time to recognize is ranging from 1.1s to 1.2s in the normal environmen
A secure image steganography based on JND model
Minimizing distortion produced by embedding process is very important to improve the security of hidden message and maintain the high visual quality of stego images. To achieve these objectives, an effective strategy is to perform pixel selection which is well-known as a channel selection rule. In this approach, a pixel associated with the smallest image degradation is chosen to carry secret bits. From these facts, in this paper, a new secure channel selection rule for digital images in spatial domain is designed and proposed. In this new approach, the modified matrix embedding method is utilized as data hiding method because it introduces more than one embedding change to be performed. This enables us to select a suitable pixel to embed message bits with less degradation yielded in a stego-image. In pixel selection of the proposed method, a just noticeable difference value and gradient value of a considering pixel are employed together. The experimental results (which were conducted on 10,000 uncompressed images) indicate that stego images of the proposed approach achieve a higher perceptual quality and security than those of the stego-images created by the previous approaches
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