Energy sources of rock burst and the influence of the surrounding rock mass

The kinetic energy for rock ejection in a rock burst event is converted from the strain energy stored in the burst rock, a portion of strain energy released from the surrounding rock mass and a portion of seismic energy transferred from fault-slip seismicity. The kinetic energy is mainly contributed by the burst rock itself in a small-scale strain burst, but the energy released from the surrounding rock mass plays a major role in a large-scale rock burst. Intergranular and extensional cracking is dominating in burst-prone rocks, while in the non-burst-prone rocks the dominating cracking is intragranular and shear. Both the crack density and the average opening width of cracks are very small in burst-prone rocks

HARMONIOUS MULTICAST RETRANSMISSION FOR LOW-POWER AND LOSSY NETWORKS FIRMWARE UPGRADING

Techniques are described herein for composing multicast retransmissions harmoniously by prioritizing transmission of new messages and regulating retransmission of old messages. Only the same multicast messages are forwarded simultaneously such that loss due to collision can be significantly reduced. By measuring the intervals of new messages and counting the duplicates, retransmissions are reasonably curbed with awareness of input rate and medium usage. This prevents the “domino effect” on a crowded channel when loss occurs. Moreover, self-silence mechanisms allow regular nodes to release channel resources for critical forwarders. Multicast retransmission is provided with guaranteed delivery rate, which is imperative for firmware upgrading in Low-Power and Lossy Networks (LLNs)

How To Create Cash Flows That Give A Priori IRRs?

We illustrate algebraically the way to numerically derive the cash flows of an investment project yielding a set of desired IRRs. This is significant given the dearth of practice questions with the appropriate cash flow numbers, and their corresponding sign, in widely adopted Finance textbooks that will allow students to find multiple IRRs as learning exercises. The note serves to fill that void by allowing the readers to change the IRR inputs in an Excel spreadsheet and have the corresponding cash flows output ready for an assignment. Instructors can use the Excel codes to create different cash flows that yield multiple IRRs with ease so that students in the same class or those in different semesters need not be given the same set of cash flows where plagiarism could compromise the learning process

Market Development, Information Diffusion and the Global Anomaly Puzzle

Previous literature finds anomalies are at least as prevalent in developed markets as in emerging markets; namely, the global anomaly puzzle. We show that while market development and information diffusion are linearly related, information diffusion has a nonlinear impact on anomalies. This is consistent with theoretical developments concerning the process of information diffusion. In extremely low efficiency regimes, without newswatchers sowing the seeds of price discovery and ensuring the long-run convergence of price to fundamentals, initial mispricing and subsequent correction will not occur. The concentration of emerging countries in low efficiency regimes provides an explanation to the puzzle

Market Development, Information Diffusion and the Global Anomaly Puzzle

Previous literature finds anomalies are at least as prevalent in developed markets as in emerging markets; namely, the global anomaly puzzle. We show that while market development and information diffusion are linearly related, information diffusion has a nonlinear impact on anomalies. This is consistent with theoretical developments concerning the process of information diffusion. In extremely low efficiency regimes, without newswatchers sowing the seeds of price discovery and ensuring the long-run convergence of price to fundamentals, initial mispricing and subsequent correction will not occur. The concentration of emerging countries in low efficiency regimes provides an explanation to the puzzle

Potential applications of deep learning in automatic rock joint trace mapping in a rock mass

In blasted rock slopes and underground openings, rock joints are visible in different forms. Rock joints are often exposed as planes confining rock blocks and visible as traces on a well-blasted, smooth rock mass surface. A realistic rock joint model should include both visual forms of joints in a rock mass: i.e., both joint traces and joint planes. Imaged-based 2D semantic segmentation using deep learning via the Convolutional Neural Network (CNN) has shown promising results in extracting joint traces in a rock mass. In 3D analysis, research studies using deep learning have demonstrated outperforming results in automatically extracting joint planes from an unstructured 3D point cloud compared to state-of-the-art methods. We discuss a pilot study using 3D true colour point cloud and their source and derived 2D images in this paper. In the study, we aim to implement and compare various CNN-based networks found in the literature for automatic extraction of joint traces from laser scanning and photogrammetry data. Extracted joint traces can then be clustered and connected to potential joint planes as joint objects in a discrete joint model. This can contribute to a more accurate estimation of rock joint persistence. The goal of the study is to compare the efficiency and accuracy between using 2D images and 3D point cloud as input data. Data are collected from two infrastructure projects with blasted rock slopes and tunnels in Norway.Potential applications of deep learning in automatic rock joint trace mapping in a rock masspublishedVersio