The advanced Device-to-Device (D2D) system is recognized as one of the key emerging technologies to support the increasing wireless data traffic of fifth generation (5G) systems and beyond. In this paper, we aim to st...
详细信息
作者：
Anwar, AymanKhalifa, YassinLucatorto, ErinCoyle, James L.Sejdic, ErvinUniversity of Toronto
Faculty of Applied Science & Engineering Department of Electrical and Computer Engineering TorontoON Canada University of Pittsburgh
Center for Research Computing and Information Technology Analytics PittsburghPA United States Cairo University
Faculty of Engineering Systems and Biomedical Engineering Department Giza Egypt University of Pittsburgh
School of Health and Rehabilitation Sciences Department of Communication Science and Disorders PittsburghPA United States University of Toronto
North York General Hospital Faculty of Applied Science & Engineering Department of Electrical and Computer Engineering TorontoON Canada
Swallowing assessment is a crucial task to reveal swallowing abnormalities. There are multiple modalities to analyze swallowing kinematics, such as videofluoroscopic swallow studies (VFSS), which is the gold standard ...
详细信息
We consider the problem of vertex recoloring: we are given n vertices with their initial coloring, and edges arrive in an online fashion. The algorithm is required to maintain a valid coloring by means of vertex recol...
详细信息
We consider the problem of vertex recoloring: we are given n vertices with their initial coloring, and edges arrive in an online fashion. The algorithm is required to maintain a valid coloring by means of vertex recoloring, where recoloring a vertex incurs a cost. The problem abstracts a scenario of job placement in machines (possibly in the cloud), where vertices represent jobs, colors represent machines, and edges represent "anti affinity" (disengagement) constraints. online coloring in this setting is a hard problem, and only a few cases were analyzed. One family of instances which is fairly well-understood is bipartite graphs, i.e., instances in which two colors are sufficient to satisfy all constraints. In this case it is known that the competitive ratio of vertex recoloring is Θ(log n). In this paper we propose a generalization of the problem, which allows using additional colors (possibly at a higher cost), to improve overall performance. Concretely, we analyze the simple case of bipartite graphs of bounded largest bond (a bond of a connected graph is an edge-cut that partitions the graph into two connected components). From the upper bound perspective, we propose two algorithms. One algorithm exhibits a trade-off for the uniform-cost case: given Ω(log β) ≤ c ≤ O(log n) colors, the algorithm guarantees that its cost is at most O(logn/c ) times the optimal offline cost for two colors, where n is the number of vertices and β is the size of the largest bond of the graph. The other algorithm is designed for the case where the additional colors come at a higher cost, D > 1: given ∆ additional colors, where ∆ is the maximum degree in the graph, the algorithm guarantees a competitive ratio of O(log D). From the lower bounds viewpoint, we show that if the cost of the extra colors is D > 1, no algorithm (even randomized) can achieve a competitive ratio of o(log D). We also show that in the case of general bipartite graphs (i.e., of unbounded bond size), any determinis
The Alternating Current Optimal Power Flow (AC OPF) is crucial for power system analysis, yet existing algorithms face challenges in meeting the diverse requirements of practical applications. This paper presents a Py...
详细信息
Personalized drug response prediction is an approach for tailoring effective therapeutic strategies for patients based on their tumors’ genomic characterization. While machine learning methods are widely employed in ...
详细信息
Renewable energy sources such as solar and wind power are increasingly being used as alternative energy sources globally to create a low carbon society. For the next generation grid with significant share of distribut...
Renewable energy sources such as solar and wind power are increasingly being used as alternative energy sources globally to create a low carbon society. For the next generation grid with significant share of distributed energy sources, energy storage technologies are essential. Vanadium redox flow batteries (VRFBs) have many advantages over other energy storage technologies. In the context of the solar plant operation, these batteries can significantly improve ancillary services of frequency regulation and voltage control to support the grid. This paper develops a VRFB model to apply a stand-alone solar system for residential applications. Both maximum power point tracking and voltage control modes are applied to the solar system. A bidirectional DC-DC converter is designed for management of the 5 kWh battery system. The vanadium redox flow battery (VRFB) is used to control the unpredictability of energy supply, serving both as an energy source and a consumer. Introduction of the VRFB and corresponding energy management system enables smoothening and energy shift of solar output, enhances the system reliability with real-time monitoring, operation, regulation, stable and effective operation, and overall system performance optimization. Described system is validated by simulations in MATLAB/Simulink.
Monocular depth estimation is an effective approach to environment perception due to simplicity of the sensor setup and absence of multisensor calibration. Deep learning has enabled accurate depth estimation from a si...
Monocular depth estimation is an effective approach to environment perception due to simplicity of the sensor setup and absence of multisensor calibration. Deep learning has enabled accurate depth estimation from a single image by exploiting semantic cues such as the sizes of known objects and positions on the ground plane thereof. However, learning-based methods frequently fail to generalize on images collected with different vehicle-camera setups due to the induced perspective geometry bias. In this work, we propose an approach for camera parameters invariant depth estimation in autonomous driving scenarios. We propose a novel joint parametrization of camera intrinsic and extrinsic parameters specifically designed for autonomous driving. In order to supplement the neural network with information about the camera parameters, we fuse the proposed parametrization and image features via the novel module based on a self-attention mechanism. After thorough experimentation on the effects of camera parameter variation, we show that our approach effectively provides the neural network with useful information, thus increasing accuracy and generalization performance.
In this work, design of unequally spaced antenna arrays with uniform excitation is considered. The design is based on numerical optimization of array's sidelobe power. The corresponding optimization problem is non...
In this work, design of unequally spaced antenna arrays with uniform excitation is considered. The design is based on numerical optimization of array's sidelobe power. The corresponding optimization problem is nonconvex and highly nonlinear. Therefore, we consider the Quasi-Newton method for its solving. Such an approach allows the application of versatile objective functions. This is illustrated in the design of linear and planar arrays. Resulting beam patterns exhibit high beam efficiency and low sidelobe level.
Determining the best shortest path between locations in intelligent transportation systems is crucial but challenging. Traditional approaches, which assume fixed travel times, fall short of accurately reflecting dynam...
详细信息
暂无评论