Mitigating Architectural Mismatch During the Evolutionary Synthesis of Deep Neural Networks

Evolutionary deep intelligence has recently shown great promise for producing small, powerful deep neural network models via the organic synthesis of increasingly efficient architectures over successive generations. Existing evolutionary synthesis processes, however, have allowed the mating of parent networks independent of architectural alignment, resulting in a mismatch of network structures. We present a preliminary study into the effects of architectural alignment during evolutionary synthesis using a gene tagging system. Surprisingly, the network architectures synthesized using the gene tagging approach resulted in slower decreases in performance accuracy and storage size; however, the resultant networks were comparable in size and performance accuracy to the non-gene tagging networks. Furthermore, we speculate that there is a noticeable decrease in network variability for networks synthesized with gene tagging, indicating that enforcing a like-with-like mating policy potentially restricts the exploration of the search space of possible network architectures.Comment: 5 page

Assessing Architectural Similarity in Populations of Deep Neural Networks

Evolutionary deep intelligence has recently shown great promise for producing small, powerful deep neural network models via the synthesis of increasingly efficient architectures over successive generations. Despite recent research showing the efficacy of multi-parent evolutionary synthesis, little has been done to directly assess architectural similarity between networks during the synthesis process for improved parent network selection. In this work, we present a preliminary study into quantifying architectural similarity via the percentage overlap of architectural clusters. Results show that networks synthesized using architectural alignment (via gene tagging) maintain higher architectural similarities within each generation, potentially restricting the search space of highly efficient network architectures.Comment: 3 pages. arXiv admin note: text overlap with arXiv:1811.0796

Exploring neutralino dark matter resonance annihilation via bA,bH -> b mu^+ mu^- at the LHC

One of the main channels which allows for a large rate of neutralino dark matter annihilation in the early Universe is via the pseudoscalar Higgs A-resonance. In this case, the measured dark matter abundance can be obtained in the minimal supergravity (mSUGRA) model when tan(beta)\sim 50 and 2m_{\tz_1}\sim m_A. We investigate the reaction pp\to b\phi\to b\mu^+\mu^- +X (where \phi =A or H) at the CERN LHC where requiring the tag of a single b-jet allows for amplification of the signal-to-background ratio. The rare but observable Higgs decay to muon pairs allows for a precise measurement of the Higgs boson mass and decay width. We evaluate signal and background using CalcHEP, with muon energy smearing according to the CMS detector. We find that the Higgs width (\Gamma_A) can typically be determined with the accuracy up to \sim 8% (\sim 17%) for m_A\sim 400 (600) GeV assuming 10^3 fb^{-1} of integrated luminosity. Therefore, the pp\to b\phi\to b\mu^+\mu^- +X process provides a unique possibility for direct \Gamma_A measurement at the LHC. While the Higgs width is correlated with the parameter \tan\beta for a given value of m_A, extracting \tan\beta is complicated by an overlap of the A and H peaks, radiative corrections to the b and \tau Yukawa couplings, and the possibility that SUSY decay modes of the Higgs may be open. In the case where a dilepton mass edge from \tz_2\to\ell^+\ell^-\tz_1 is visible, it should be possible to test the relation that 2m_{\tz_1}\sim m_A.Comment: 19 pages with 25 .eps figure

Nuclear matrix protein 2 antibody-positive adult dermatomyositis: a case report and review of the literature

Dermatomyositis is a clinically heterogenous inflammatory myopathy with unique cutaneous features. Myositis-specific antibodies can aid in diagnosis and anticipation of patient prognosis. Herein, we report a 22-year-old man who presented with multifocal erythematous plaques with violaceous papules on his bilateral elbows, neck, and face. He was diagnosed with biopsy-proven dermatomyositis and determined to be seropositive for nuclear matrix protein 2 antibody (NXP-2). He was treated with systemic corticosteroids, then intravenous methylprednisolone and azathioprine, and ultimately achieved greatest treatment response with intravenous immune globulin therapy

The Mechanical Strength of Malosma laurina Leaves Corresponds with Survivability During Extreme Drought

With the recent extreme drought that Southern California is facing, many plants’ survivability adaptations have proven insufficient. The Malosma laurina plant is known for it’s incredible ability to survive through droughts and wildfires with it’s adaptations of resprouts regeneration and it’s roots that can reach a depth of 40 feet to gather deep ground waters. We theorized that the mechanical strength of the leaves directly relates to its survivability during droughts. To explore this theory we took focused our theory specifically on M. laurina resprouts. With two groups, one fully alive and one dying, we took six samples from six plants within each group, for a total of twelve total plants and seventy-two leaf samples. We predicted that the alive plants, that are able to endure the drought, will have a higher mechanical strength due to the water filled cells within the leaf. We expected our results to conclude that plants that are healthier and better hydrated shall have a greater mechanical strength than those of poorer health and lower hydration

Ground-based PIV and numerical flow visualization results from the surface tension driven convection experiment

The Surface Tension Driven Convection Experiment (STDCE) is a Space Transportation System flight experiment to study both transient and steady thermocapillary fluid flows aboard the United States Microgravity Laboratory-1 (USML-1) Spacelab mission planned for June, 1992. One of the components of data collected during the experiment is a video record of the flow field. This qualitative data is then quantified using an all electric, two dimensional Particle Image Velocimetry (PIV) technique called Particle Displacement Tracking (PDT), which uses a simple space domain particle tracking algorithm. Results using the ground based STDCE hardware, with a radiant flux heating mode, and the PDT system are compared to numerical solutions obtained by solving the axisymmetric Navier Stokes equations with a deformable free surface. The PDT technique is successful in producing a velocity vector field and corresponding stream function from the raw video data which satisfactorily represents the physical flow. A numerical program is used to compute the velocity field and corresponding stream function under identical conditions. Both the PDT system and numerical results were compared to a streak photograph, used as a benchmark, with good correlation