16,998 research outputs found

    A social spider algorithm for global optimization

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    The growing complexity of real-world problems has motivated computer scientists to search for efficient problem-solving methods. Metaheuristics based on evolutionary computation and swarm intelligence are outstanding examples of nature-inspired solution techniques. Inspired by the social spiders, we propose a novel social spider algorithm to solve global optimization problems. This algorithm is mainly based on the foraging strategy of social spiders, utilizing the vibrations on the spider web to determine the positions of preys. Different from the previously proposed swarm intelligence algorithms, we introduce a new social animal foraging strategy model to solve optimization problems. In addition, we perform preliminary parameter sensitivity analysis for our proposed algorithm, developing guidelines for choosing the parameter values. The social spider algorithm is evaluated by a series of widely used benchmark functions, and our proposed algorithm has superior performance compared with other state-of-the-art metaheuristics.postprin

    Delay Aware Intelligent Transient Stability Assessment System

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    Transient stability assessment is a critical tool for power system design and operation. With the emerging advanced synchrophasor measurement techniques, machine learning methods are playing an increasingly important role in power system stability assessment. However, most existing research makes a strong assumption that the measurement data transmission delay is negligible. In this paper, we focus on investigating the influence of communication delay on synchrophasor-based transient stability assessment. In particular, we develop a delay aware intelligent system to address this issue. By utilizing an ensemble of multiple long short-term memory networks, the proposed system can make early assessments to achieve a much shorter response time by utilizing incomplete system variable measurements. Compared with existing work, our system is able to make accurate assessments with a significantly improved efficiency. We perform numerous case studies to demonstrate the superiority of the proposed intelligent system, in which accurate assessments can be developed with time one third less than state-of-the-art methodologies. Moreover, the simulations indicate that noise in the measurements has trivial impact on the assessment performance, demonstrating the robustness of the proposed system.published_or_final_versio

    Coordinated autonomous vehicle parking for vehicle-to-grid services

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    Coordinated Autonomous Vehicle Parking for Vehicle-to-Grid Services: Formulation and Distributed Algorithm

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    Autonomous vehicles (AVs) will revolutionarize ground transport and take a substantial role in the future transportation system. Most AVs are likely to be electric vehicles (EVs) and they can participate in the vehicle-to-grid (V2G) system to support various V2G services. Although it is generally infeasible for EVs to dictate their routes, we can design AV travel plans to fulfill certain system-wide objectives. In this paper, we focus on the AVs looking for parking and study how they can be led to appropriate parking facilities to support V2G services. We formulate the Coordinated Parking Problem (CPP), which can be solved by a standard integer linear program solver but requires long computational time. To make it more practical, we develop a distributed algorithm to address CPP based on dual decomposition. We carry out a series of simulations to evaluate the proposed solution methods. Our results show that the distributed algorithm can produce nearly optimal solutions with substantially less computational time. A coarser time scale can improve computational time but degrade the solution quality resulting in possible infeasible solution. Even with communication loss, the distributed algorithm can still perform well and converge with only little degradation in speed.postprin

    Entry of Not-for-Profit Food Cooperatives and Its Implications on For-Profit Retailers

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    Propelled by the recent social activism that calls for not-for-profit food cooperatives (coops) to address the food desert and job desert issues, more food coops are establishing their presence in less-populated areas or poor communities. This trend has motivated us to examine the entry conditions for food coops with the following two related social missions: (A) maximize reserve to support the local community needs; and (B) maximize sales to support the local economy. We present a game-theoretic model to analyze the competition between an entrant not-for-profit coop and an incumbent for-profit retailer in a market comprising heterogeneous consumers with different annual consumption rates and social benefit levels. We examine the coop's pricing strategy and entry conditions, the impact of the coop's entry on the retailer's profit, and the conditions under which the retailer should deter the coop's entry. Our analytical results indicate that a coop can afford to enter the market only when its fixed annual operating cost is below a certain threshold. Upon entry, it is optimal for the coop to set a membership fee and a member-only discount to attract at least those consumers with high consumption rate. We show that the coop’s entry is detrimental for the retailer. However, interestingly, even if the retailer can profitably deter the coop’s entry, it is actually optimal for the retailer to tolerate it when the coop's annual fixed operating cost is below a threshold, where this threshold is lower for a coop with mission (B) than mission (A)

    Scene Coordinate Regression with Angle-Based Reprojection Loss for Camera Relocalization

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    Image-based camera relocalization is an important problem in computer vision and robotics. Recent works utilize convolutional neural networks (CNNs) to regress for pixels in a query image their corresponding 3D world coordinates in the scene. The final pose is then solved via a RANSAC-based optimization scheme using the predicted coordinates. Usually, the CNN is trained with ground truth scene coordinates, but it has also been shown that the network can discover 3D scene geometry automatically by minimizing single-view reprojection loss. However, due to the deficiencies of the reprojection loss, the network needs to be carefully initialized. In this paper, we present a new angle-based reprojection loss, which resolves the issues of the original reprojection loss. With this new loss function, the network can be trained without careful initialization, and the system achieves more accurate results. The new loss also enables us to utilize available multi-view constraints, which further improve performance.Comment: ECCV 2018 Workshop (Geometry Meets Deep Learning

    A high incidence of native portal vein thrombosis in veterans undergoing liver transplantation

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    The incidence of native portal vein thrombosis (PVT) in liver transplant recipients has been reported to range from 2.1 to 13.8%. We have identified an inordinately high incidence of PVT in a consecutive series of U.S. veterans receiving liver transplants. Between October 1989 and February 1994, 88 consecutive U.S. veterans received 99 orthotopic liver transplants under primary Tacrolimus (Prograf, formerly FK506) based immunosuppression. A number of clinical features were examined in an effort to identify risk factors for PVT and outcome was compared to patients without PVT. Native PVT was present in 23/88 (26%) patients. All of these patients were male U.S. veterans with a mean age of 47 years. When compared to the 65 patients without PVT, we found no significant difference with respect to underlying liver disease, age, Childs-Pugh score (mean = 12), UNOS status as defined prior to April 1995 (95% UNOS 3 or 4), previous abdominal surgery, or liver volume. Median blood loss for patients with PVT (21 units of packed red blood cells) was greater than for those without PVT (14 units, P = 0.04). Portal thrombectomy was performed in 11 patients, 11 patients required mesoportal jump grafts, and 1 patient had an interposition graft. Standard veno-venous bypass was used in 10 patients with single bypass utilized for the remainder. Actuarial patient survival for all patients at 1, 2, and 4 years was 88, 85, and 79%, respectively. There was no significant difference in patients with or without PVT. Patients with PVT had poorer graft survival than patients without PVT (86% vs 65%, 1 year; 81% vs 65%, 2 years; 81% vs 61%, 4 years; P = 0.03); however, this was not related to technical problems with the portal venous inflow. PVT occurred in 26% of U.S. veterans undergoing liver transplantation. These patients bad significantly higher operative blood loss and poorer graft survival. The high incidence of postnecrotic cirrhosis in a predominantly male group of patients with advanced disease, as is evident by the high mean Childs-Pugh score and UNOS status, perhaps accounts for our observations

    Magnetic ordering at the edges of graphitic fragments: Magnetic tail interactions between the edge-localized states

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    To understand the formation mechanism of magnetic moments at the edges of graphitic fragments, we carry out first-principles density-functional calculations for the electronic and magnetic structures of graphitic fragments with various spin and geometric configurations. We find that interedge and interlayer interactions between the localized moments can be explained in terms of interactions between the magnetic tails of the edge-localized states. In addition, the dihydrogenated edge states as well as Fe ad-atoms at the edge are studied in regard to the magnetic order and proximity effects.open28621
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