Shot Classification in Broadcast Soccer Video

In this paper, we present an effective hierarchical shot classification scheme for broadcast soccer video. We first partition a video into replay and non-replay shots with replay logo detection. Then, non-replay shots are further classified into Long, Medium, Close-up or Out-field types with color and texture features based on a decision tree. We tested the method on real broadcast FIFA soccer videos, and the experimental results demonstrate its effectiveness.

A Neural Correlate of Oculomotor Sequences in Supplementary Eye Field

AbstractComplex learned motor sequences can be composed of a combination of a small number of elementary actions. To investigate how the brain represents such sequences, we devised an oculomotor sequence task in which the monkey had to choose the target solely by the sequential context, not by the current stimulus combination. We found that many neurons in the supplementary eye field (SEF) became active with a specific target direction (D neuron) or a specific target/distractor combination (C neuron). Furthermore, such activity was often selective for one among several sequences that included the combination (S neuron). These results suggest that the SEF contributes to the generation of saccades in many learned sequences

Distance-Based Opportunistic Mobile Data Offloading.

Cellular network data traffic can be offload onto opportunistic networks. This paper proposes a Distance-based Opportunistic Publish/Subscribe (DOPS) content dissemination model, which is composed of three layers: application layer, decision-making layer and network layer. When a user wants new content, he/she subscribes on a subscribing server. Users having the contents decide whether to deliver the contents to the subscriber based on the distance information. If in the meantime a content owner has traveled further in the immediate past time than the distance between the owner and the subscriber, the content owner will send the content to the subscriber through opportunistic routing. Simulations provide an evaluation of the data traffic offloading efficiency of DOPS

Action and Trajectory Planning for Urban Autonomous Driving with Hierarchical Reinforcement Learning

Reinforcement Learning (RL) has made promising progress in planning and decision-making for Autonomous Vehicles (AVs) in simple driving scenarios. However, existing RL algorithms for AVs fail to learn critical driving skills in complex urban scenarios. First, urban driving scenarios require AVs to handle multiple driving tasks of which conventional RL algorithms are incapable. Second, the presence of other vehicles in urban scenarios results in a dynamically changing environment, which challenges RL algorithms to plan the action and trajectory of the AV. In this work, we propose an action and trajectory planner using Hierarchical Reinforcement Learning (atHRL) method, which models the agent behavior in a hierarchical model by using the perception of the lidar and birdeye view. The proposed atHRL method learns to make decisions about the agent's future trajectory and computes target waypoints under continuous settings based on a hierarchical DDPG algorithm. The waypoints planned by the atHRL model are then sent to a low-level controller to generate the steering and throttle commands required for the vehicle maneuver. We empirically verify the efficacy of atHRL through extensive experiments in complex urban driving scenarios that compose multiple tasks with the presence of other vehicles in the CARLA simulator. The experimental results suggest a significant performance improvement compared to the state-of-the-art RL methods.Comment: ICML Workshop on New Frontiers in Learning, Control, and Dynamical System

Equine estrogens differentially inhibit DNA fragmentation induced by glutamate in neuronal cells by modulation of regulatory proteins involved in programmed cell death

BACKGROUND: Recent data indicate that excitotoxicity of high levels of neurotransmitter glutamate may be mediated via programmed cell death (apoptosis) and that it can be prevented in HT22 mouse hippocampal cells by various equine estrogens with Δ(8),17β-estradiol (Δ(8),17β-E(2)) being the most potent. In order to delineate the mechanism(s), glutamate-induced cell death of HT22 cells was assessed by measuring (a) DNA fragmentation in the presence or absence of 11 equine estrogens (components of the drug CEE); (b) cell death and (c) levels of anti-apoptotic (Bcl-2) and proapoptotic (Bax) proteins in the presence or absence of two equine estrogens, Δ(8),17β-E(2 )and 17β-estradiol (17β-E(2)) by LDH release assay and Western blot analysis respectively. RESULTS: Glutamate treatment induced cell death was time and dose-dependent. After 18 to 24 h, glutamate induced DNA fragmentation and morphological characteristics of apoptotic cell death. DNA fragmentation and morphological changes induced by 10 mM glutamate were completely inhibited by some equine estrogens. Exposure of cells to various concentrations of glutamate, resulted in a significant increase in cell death associated LDH release that was time-dependent. Both Δ(8),17β-E(2 )and 17β-E(2 )inhibited the glutamate-induced LDH release and cell death in a dose-dependent manner with Δ(8),17β-E(2 )being 10 times more potent than 17β-E(2). Western blot analysis indicated that glutamate also significantly decreased the levels of Bcl-2 and increased Bax levels. This glutamate-induced change in the ratio of Bcl-2 to Bax was reversed by estrogens with Δ(8),17β-E(2 )being more potent. CONCLUSIONS: In HT22 mouse hippocampal cells, glutamate induced apoptosis that was associated with DNA fragmentation, morphological changes and up-regulation of the pro-apoptotic protein Bax and down-regulation of the anti-apoptotic protein Bcl-2. This apoptotic process was differentially prevented by some equine estrogens with Δ(8),17β-E(2 )being more potent than 17β-E(2). Since HT22 cells lacked both glutamate and estrogen receptors, the neuroprotective effects of estrogens most likely involve both genomic and non-genomic mechanisms. Since Δ(8)-estrogens are less feminizing estrogens than 17β-E(2), further chemical modifications of these Δ(8)-estrogens may provide more selective estrogens that will be useful in the prevention of neurodegenerative diseases such as Alzheimer's and Parkinson's in both aging men and women

Dynamic User Grouping and Joint Resource Allocation with Multi-Cell Cooperation for Uplink Virtual MIMO Systems

This paper proposes a novel joint resource allocation algorithm combining dynamic user grouping, multi-cell cooperation and resource block (RB) allocation for single carrier-frequency division multiple access (SC-FDMA) uplink in multicell virtual MIMO systems. We first develop the dynamic multicell user grouping criteria using minimum mean square error (MMSE) equalization and adaptive modulation (AM) with bit error rate (BER) constraint. Then, we formulate and solve a new throughput maximization problem whose resource allocation includes cell selection, dynamic user grouping and RB pattern assignment. Furthermore, to reduce the computational complexity significantly, especially in the case of large numbers of users and RBs, we present an efficient iterative Hungarian algorithm based on user and resource partitions (IHA_URP) to solve the problem by decomposing the large scale problem into a series of small scale sub-problems, which can obtain close-to-optimal solution with much lower complexity. The simulation results show that our proposed joint resource allocation algorithm with dynamic multicell user grouping scheme achieves better system throughput with BER guarantee than fixed user grouping algorithm and other proposed schemes in the literature

A Location Prediction Algorithm for Mobile Communications Using Directional Antennas

A directional communication scheme, TRAC, is proposed in this paper to deal with issues in mobile directional communications. Directional communication can bring benefits in terms of spatial reuse, power consumption, and security. Using direction antennas implies that the transmitters must know the direction or location of the receiver. It is necessary to predict the receiver's location to keep the transmitter's antenna pointing in the right direction if nodes travel always. TRAC is composed of the location prediction and antenna adjustment. It predicts a possible circular region where the moving receiver may enter into in the near future. The transmitter points its antenna at the predicted circular region and adjusts the beam-width of its directional antenna to cover the predicted region. The authors validated the TRAC algorithm on some vehicles traces. The validation indicated that the algorithm efficiency of TRAC is larger than 96%. TRAC can be employed in mobile communications without nodes' history movement traces