Optimality of Graphlet Screening in High Dimensional Variable Selection

Consider a linear regression model where the design matrix X has n rows and p columns. We assume (a) p is much large than n, (b) the coefficient vector beta is sparse in the sense that only a small fraction of its coordinates is nonzero, and (c) the Gram matrix G = X'X is sparse in the sense that each row has relatively few large coordinates (diagonals of G are normalized to 1). The sparsity in G naturally induces the sparsity of the so-called graph of strong dependence (GOSD). We find an interesting interplay between the signal sparsity and the graph sparsity, which ensures that in a broad context, the set of true signals decompose into many different small-size components of GOSD, where different components are disconnected. We propose Graphlet Screening (GS) as a new approach to variable selection, which is a two-stage Screen and Clean method. The key methodological innovation of GS is to use GOSD to guide both the screening and cleaning. Compared to m-variate brute-forth screening that has a computational cost of p^m, the GS only has a computational cost of p (up to some multi-log(p) factors) in screening. We measure the performance of any variable selection procedure by the minimax Hamming distance. We show that in a very broad class of situations, GS achieves the optimal rate of convergence in terms of the Hamming distance. Somewhat surprisingly, the well-known procedures subset selection and the lasso are rate non-optimal, even in very simple settings and even when their tuning parameters are ideally set

Multi-Agent Competition Simulation of Integrated Transportation System

Transportation networks have been developed during the recent decades with the rapid growth of economy. At the same time, the conflicts between different transportation modes were getting more and more intense. To describe the competition relationship in integrated transportation system, a multi-agent competition model was presented. It is important to provide decision support for regulators to lead more reasonable distribution of resources for planning and operating the integrated transportation network. Thus, a simulation program was developed to implement the proposed model and provide computer-aid decision support. Finally, several experiments were conducted to illustrate the effectiveness of this technique. DOI: http://dx.doi.org/10.11591/telkomnika.v11i1.190

E3^3-UAV: An Edge-based Energy-Efficient Object Detection System for Unmanned Aerial Vehicles

Motivated by the advances in deep learning techniques, the application of Unmanned Aerial Vehicle (UAV)-based object detection has proliferated across a range of fields, including vehicle counting, fire detection, and city monitoring. While most existing research studies only a subset of the challenges inherent to UAV-based object detection, there are few studies that balance various aspects to design a practical system for energy consumption reduction. In response, we present the E$^3$-UAV, an edge-based energy-efficient object detection system for UAVs. The system is designed to dynamically support various UAV devices, edge devices, and detection algorithms, with the aim of minimizing energy consumption by deciding the most energy-efficient flight parameters (including flight altitude, flight speed, detection algorithm, and sampling rate) required to fulfill the detection requirements of the task. We first present an effective evaluation metric for actual tasks and construct a transparent energy consumption model based on hundreds of actual flight data to formalize the relationship between energy consumption and flight parameters. Then we present a lightweight energy-efficient priority decision algorithm based on a large quantity of actual flight data to assist the system in deciding flight parameters. Finally, we evaluate the performance of the system, and our experimental results demonstrate that it can significantly decrease energy consumption in real-world scenarios. Additionally, we provide four insights that can assist researchers and engineers in their efforts to study UAV-based object detection further.Comment: 16 pages, 8 figure

Cracked modeling and vibration analysis of pipe with a part-through crack

Pipeline is an important transportation facility in the oil and gas industries. But cracks inevitably appear in the pipe body due to various factors. Mechanical analysis of cracked pipe structures based on local flexibility has received increased attention in the last three decades. However, few reports exist on the local flexibility of pipes with an arbitrary angled crack. In this paper, the general solution of the local flexibility equations of a pipe with a part through-crack subjected to axial force, shearing force, and bending moment is deduced with respect to an arbitrary angled crack. The proposed equations consider the influence of the crack orientation on the local flexibility coefficient. An adaptive Simpson method is used to calculate the local flexibility coefficients of a cracked pipe. The results of testing by Naniwadekar’s and Authors’ are used to validate the proposed method. The results demonstrate that the proposed method is accurate for calculating local flexibility and can be applied for vibration analysis in a pipe-like structure

Nonlinear dynamic response analysis of a cantilever beam with a breathing crack

The nonlinear dynamic characteristics of plane cracked beam subjected to a harmonic load at the tip are researched. A crack opens and closes during vibration that is simulated as a frictionless plane contact problem, and a finite element contact model for a cantilever cracked beam is established. The quarter-point element is used to describe the crack tip singularity. Based on the proposed finite element contact model, the influence of excitation frequency, crack depth and crack position on nonlinear dynamic characteristics are discussed in detail. Relative amplitude of frequency spectrum with respect to different factors is analyzed to realize sub-harmonics or super-harmonics of cracked beam. The research results demonstrate that there is obvious nonlinear dynamic behavior for plane beam with a fatigue crack, and the different feature of frequency spectrum can be used to identify the beam damage in structure. Meanwhile, the strategy of experimental validation to the FEM results is discussed

Damage modeling and simulation of vibrating pipe with part-through circumferential crack

A new finite element model is developed to perform vibration analysis of a cracked pipe. To formulate the method, the local flexibility coefficients of a part-through circumferential crack in a pipe that is subjected to axial force, shear force and bending moment are analytically derived using linear fracture mechanics. In particular, an adaptive Simpson method is utilized to carry out the numerical integration for calculating the flexibility coefficients. With the flexibility coefficients, a finite element model is established to study the vibration characteristics of the cracked pipe, with particular emphasis on the crack effect represented by change in natural frequency. As an illustrative application, the finite element model is utilized to identify a crack in a pipe by contour plots of frequency ratio as function of crack location and crack depth, with the crack location and depth identified accurately. The proposed method is effective in characterizing the vibration behavior of a pipe with a crack