A data-driven method was proposed to realistically animate garments on human poses in reduced space. Firstly, a gradient based method was extended to generate motion sequences and garments were simulated on the sequen...
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A data-driven method was proposed to realistically animate garments on human poses in reduced space. Firstly, a gradient based method was extended to generate motion sequences and garments were simulated on the sequences as our training data. Based on the examples, the proposed method can fast output realistic garments on new poses. Our framework can be mainly divided into offline phase and online phase. During the offline phase, based on linear blend skinning(LBS), rigid bones and flex bones were estimated for human bodies and garments, respectively. Then, rigid bone weight maps on garment vertices were learned from examples. In the online phase, new human poses were treated as input to estimate rigid bone transformations. Then, both rigid bones and flex bones were used to drive garments to fit the new poses. Finally, a novel formulation was also proposed to efficiently deal with garment-body penetration. Experiments manifest that our method is fast and accurate. The intersection artifacts are fast removed and final garment results are quite realistic.
A radiation hardening algorithm named as state-conservation on 2nd order clock and data recovery (CDR) system is presented in this paper. This proposed algorithm is used to resist the single event transient (SET) of C...
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This paper studies the communication pattern of data-parallel applications from the perspective of job execution, and discovers multiple inter-coflow dependencies. These inter-coflow dependencies, collectively named a...
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ISBN:
(纸本)9781509036547
This paper studies the communication pattern of data-parallel applications from the perspective of job execution, and discovers multiple inter-coflow dependencies. These inter-coflow dependencies, collectively named as semantic flow (seflow), can expose job-level semantics. It is observed that most distributed computing frameworks describe their job execution as directed acyclic graphs (DAG). So a seflow comprises not only all the coflows of a job but also the DAG-based relationship between them. Seflow, coflow and flow can be viewed as the top-down abstractions for communication of jobs.
Two-dimensional high-resolution inviscid and viscous detonations were conducted in the supersonic combustible mixture with the open-source program AMROC. The results show that as the grid resolution increases, more sm...
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MIMO system is widely studied for its high performance in wireless communication, of which the THP algorithm is a bottleneck of performance. Generally the THP is implemented in ASIC for high performance, which unfortu...
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ISBN:
(纸本)9781467388399
MIMO system is widely studied for its high performance in wireless communication, of which the THP algorithm is a bottleneck of performance. Generally the THP is implemented in ASIC for high performance, which unfortunately makes it a difficulty for system updating. Compared to the ASIC solution, configurable processing, as its inherent flexibility and extension, becomes a promising solution for this difficulty, especially in the case of FPGA based systems where multi-core method is utilized to make up for the performance deficiency of soft cores. This paper explores a micro blaze based-multi-core system to increase the performance of THP algorithm while keeping the system flexibility. In support of the flexibility to update the algorithm, the effective adaption of this approach is demonstrated. Moreover, optimized application specific hardware is combined with data-level paralleled software modules in the multi-core embedded system, which increases the performance of THP algorithm to a 6× speed over all-soft single-core solution.
Groupwise analytics on big data have been widely used in statistics, computer science, parallel computing and many other fields in recent years. At The same time, Aggregation queries is one of the most important analy...
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ISBN:
(纸本)9781509055227
Groupwise analytics on big data have been widely used in statistics, computer science, parallel computing and many other fields in recent years. At The same time, Aggregation queries is one of the most important analytics techniques. In big data eras, the aggregation queries on the ever-increasing data volumes will consumes much time, the traditional methods of traversing the entire dataset is not acceptable to users. Data sampling is a technique that only process a part of data to get an approximate result, the technique can save a lot of time when dealing with a vast amount of data with the sacrifice of accuracy. This paper will introduce several data sampling algorithms for approximate aggregation queries for big data, and analyze the shortcomings and advantages of each methods. Including the technique apply to the sparse data which meaning data has a limited population but a wide range.
Virtual Machine（VM） allocation for multiple tenants is an important and challenging problem to provide efficient infrastructure services in cloud data centers. Tenants run applications on their allocated VMs, and th...
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Virtual Machine（VM） allocation for multiple tenants is an important and challenging problem to provide efficient infrastructure services in cloud data centers. Tenants run applications on their allocated VMs, and the network distance between a tenant＇s VMs may considerably impact the tenant＇s Quality of Service（Qo S）. In this study, we define and formulate the multi-tenant VM allocation problem in cloud data centers, considering the VM requirements of different tenants, and introducing the allocation goal of minimizing the sum of the VMs＇ network diameters of all tenants. Then, we propose a Layered Progressive resource allocation algorithm for multi-tenant cloud data centers based on the Multiple Knapsack Problem（LP-MKP）. The LP-MKP algorithm uses a multi-stage layered progressive method for multi-tenant VM allocation and efficiently handles unprocessed tenants at each stage. This reduces resource fragmentation in cloud data centers, decreases the differences in the Qo S among tenants, and improves tenants＇ overall Qo S in cloud data centers. We perform experiments to evaluate the LP-MKP algorithm and demonstrate that it can provide significant gains over other allocation algorithms.
FinFET technologies are becoming the mainstream process as technology scales down. Based on a 28-nm bulk p- FinFET device, we have investigated the fin width and height dependence of bipolar amplification for heavy-io...
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FinFET technologies are becoming the mainstream process as technology scales down. Based on a 28-nm bulk p- FinFET device, we have investigated the fin width and height dependence of bipolar amplification for heavy-ion-irradiated FinFETs by 3D TCAD numerical simulation. Simulation results show that due to a well bipolar conduction mechanism rather than a channel （fin） conduction path, the transistors with narrower fins exhibit a diminished bipolar amplification effect, while the fin height presents a trivial effect on the bipolar amplification and charge collection. The results also indicate that the single event transient （SET） pulse width can be mitigated about 35% at least by optimizing the ratio of fin width and height, which can provide guidance for radiation-hardened applications in bulk FinFET technology.
It is widely believed that Shor＇s factoring algorithm provides a driving force to boost the quantum computing ***, a serious obstacle to its binary implementation is the large number of quantum gates. Non-binary quan...
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It is widely believed that Shor＇s factoring algorithm provides a driving force to boost the quantum computing ***, a serious obstacle to its binary implementation is the large number of quantum gates. Non-binary quantum computing is an efficient way to reduce the required number of elemental gates. Here, we propose optimization schemes for Shor＇s algorithm implementation and take a ternary version for factorizing 21 as an example. The optimized factorization is achieved by a two-qutrit quantum circuit, which consists of only two single qutrit gates and one ternary controlled-NOT gate. This two-qutrit quantum circuit is then encoded into the nine lower vibrational states of an ion trapped in a weakly anharmonic potential. Optimal control theory（OCT） is employed to derive the manipulation electric field for transferring the encoded states. The ternary Shor＇s algorithm can be implemented in one single step. Numerical simulation results show that the accuracy of the state transformations is about 0.9919.
Real-life behaviors shown by the mobile users typically exhibit plenty noises, making it hard to construct an effective recommendation engine. In this paper, we present a fused model based on the LR algorithm and the ...
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ISBN:
(纸本)9781509006212
Real-life behaviors shown by the mobile users typically exhibit plenty noises, making it hard to construct an effective recommendation engine. In this paper, we present a fused model based on the LR algorithm and the GBDT algorithm to recommend vertical industry commodities in a mobile setting. A set of specifically designed methods are proposed to deal with the data preprocessing and feature extraction problem for the mobile recommendation scenario. The proposed method is evaluated on a large scale real-world dataset provided by the Alibaba mobile shopping department. Result on the F1 score has seen an improvement of 2%-36% compared with the baseline.
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