Privacy-Preserving Outsourcing of Large-Scale Nonlinear Programming to the Cloud

The increasing massive data generated by various sources has given birth to big data analytics. Solving large-scale nonlinear programming problems (NLPs) is one important big data analytics task that has applications in many domains such as transport and logistics. However, NLPs are usually too computationally expensive for resource-constrained users. Fortunately, cloud computing provides an alternative and economical service for resource-constrained users to outsource their computation tasks to the cloud. However, one major concern with outsourcing NLPs is the leakage of user's private information contained in NLP formulations and results. Although much work has been done on privacy-preserving outsourcing of computation tasks, little attention has been paid to NLPs. In this paper, we for the first time investigate secure outsourcing of general large-scale NLPs with nonlinear constraints. A secure and efficient transformation scheme at the user side is proposed to protect user's private information; at the cloud side, generalized reduced gradient method is applied to effectively solve the transformed large-scale NLPs. The proposed protocol is implemented on a cloud computing testbed. Experimental evaluations demonstrate that significant time can be saved for users and the proposed mechanism has the potential for practical use.Comment: Ang Li and Wei Du equally contributed to this work. This work was done when Wei Du was at the University of Arkansas. 2018 EAI International Conference on Security and Privacy in Communication Networks (SecureComm

CXCL12/CXCR4 axis: an emerging neuromodulator in pathological pain

The roles of chemokine C-X-C motif ligand 12 (CXCL12) and its receptor chemokine C-X-C motif receptor 4 (CXCR4) reveal this chemokine axis as an emerging neuromodulator in the nervous system. In the peripheral and central nervous systems, both CXCL12 and CXCR4 are expressed in various kinds of nociceptive structures, and CXCL12/CXCR4 axis possesses pronociceptive property. Recent studies have demonstrated its critical roles in the development and maintenance of pathological pain, and both neuronal and glial mechanisms are involved in this CXCL12/CXCR4 axis-mediated pain processing. In this review, we summarize the recent development of the roles and mechanisms of CXCL12/CXCR4 axis in the pathogenesis of chronic pain by sciatic nerve injury, human immunodeficiency virus-associated sensory neuropathy, diabetic neuropathy, spinal cord injury, bone cancer, opioid tolerance, or opioid-induced hyperalgesia. The potential targeting of CXCL12/CXCR4 axis as an effective and broad-spectrum pharmacological approach for chronic pain therapy was also discussed.published_or_final_versio

Monolithic millimeter-wave diode array beam controllers: Theory and experiment

In the current work, multi-function beam control arrays have been fabricated and have successfully demonstrated amplitude control of transmitted beams in the W and D bands (75-170 GHz). While these arrays are designed to provide beam control under DC bias operation, new designs for high-speed electronic and optical control are under development. These arrays will fill a need for high-speed watt-level beam switches in pulsed reflectometer systems under development for magnetic fusion plasma diagnostics. A second experimental accomplishment of the current work is the demonstration in the 100-170 GHz (D band) frequency range of a new technique for the measurement of the transmission phase as well as amplitude. Transmission data can serve as a means to extract ('de-embed') the grid parameters; phase information provides more complete data to assist in this process. Additional functions of the array beam controller yet to be tested include electronically controlled steering and focusing of a reflected beam. These have application in the areas of millimeter-wave electronic scanning radar and reflectometry, respectively

LiDAR-Guided Cross-Attention Fusion for Hyperspectral Band Selection and Image Classification

The fusion of hyperspectral and light detection and range (LiDAR) data has been an active research topic. Existing fusion methods have ignored the high-dimensionality and redundancy challenges in hyperspectral images (HSIs), despite that band selection methods have been intensively studied for HSI processing. This article addresses this significant gap by introducing a cross-attention mechanism from the transformer architecture for the selection of HSI bands guided by LiDAR data. LiDAR provides high-resolution vertical structural information, which can be useful in distinguishing different types of land cover that may have similar spectral signatures but different structural profiles. In our approach, the LiDAR data are used as the “query” to search and identify the “key” from the HSI to choose the most pertinent bands for LiDAR. This method ensures that the selected HSI bands drastically reduce redundancy and computational requirements while working optimally with the LiDAR data. Extensive experiments have been undertaken on three paired HSI and LiDAR datasets: Houston 2013, Trento, and MUUFL. The results highlight the superiority of the cross-attention mechanism, underlining the enhanced classification accuracy of the identified HSI bands when fused with the LiDAR features. The results also show that the use of fewer bands combined with LiDAR surpasses the performance of state-of-the-art fusion models

Deficits in lower limb muscle reflex contraction latency and peak force are associated with impairments in postural control and gross motor skills of children with developmental coordination disorder: A cross-sectional study

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Synchronization in small-world systems

We quantify the dynamical implications of the small-world phenomenon. We consider the generic synchronization of oscillator networks of arbitrary topology, and link the linear stability of the synchronous state to an algebraic condition of the Laplacian of the graph. We show numerically that the addition of random shortcuts produces improved network synchronizability. Further, we use a perturbation analysis to place the synchronization threshold in relation to the boundaries of the small-world region. Our results also show that small-worlds synchronize as efficiently as random graphs and hypercubes, and more so than standard constructive graphs

Comparison of chemical profiles and effectiveness between Erxian decoction and mixtures of decoctions of its individual herbs : a novel approach for identification of the standard chemicals

Acknowledgements This study was partially supported by grants from the Seed Funding Programme for Basic Research (Project Number 201211159146 and 201411159213), the University of Hong Kong. We thank Mr Keith Wong and Ms Cindy Lee for their technical assistances.Peer reviewedPublisher PD

Cluster transfer matrix method for the single electron box

With the newly developed cluster transfer matrix method, we calculate the average electron number n vs nx (the polarization charge) for varying junction conductance and its first derivative at nx=0 for finite temperatures, and demonstrate that the new method is as powerful as the Monte Carlo and renormalization group methods.Comment: 11 pages including figure