525 research outputs found
Pengaruh Kompensasi terhadap Komitmen Organisasional dan Turnover Intention pada Agent Pru Megas
Penelitian ini bertujuan untuk mengetahui pengaruh kompensasi terhadap komitmen organisasional dan turnover intention pada agent PRU Megas. Penelitian ini dilakukan pada Perusahaan anak cabang dari PT. Prudential Life Assurance (Prudential Indonesia) yang bernama PRU Megas berlokasi di masceti jalan bypass Prof Ida Bagus Mantra, Gianyar, Bali dengan menggunakan 65 orang sebagai responden penelitian. Teknik penentuan sampel yang digunakan dalam penelitian ini adalah teknik sensus. Pengumpulan data dilakukan melalui wawancara dan kuesioner. Teknik analisis data yang digunakan pada penelitian ini adalah path analysis yang diolah menggunakan software SPSS. Hasil yang diperoleh dalam penelitian ini menunjukkan bahwa seluruh hipotesis diterima. Berdasarkan hasil analisis, penelitian ini menunjukan bahwa kompensasi berpengaruh positif terhadap komitmen organisasional, komitmen organisasional berpengaruh negatif terhadap turnover intention dan kompensasi berpengaruh negatif terhadap turnover intention
DANTE: Deep AlterNations for Training nEural networks
We present DANTE, a novel method for training neural networks using the
alternating minimization principle. DANTE provides an alternate perspective to
traditional gradient-based backpropagation techniques commonly used to train
deep networks. It utilizes an adaptation of quasi-convexity to cast training a
neural network as a bi-quasi-convex optimization problem. We show that for
neural network configurations with both differentiable (e.g. sigmoid) and
non-differentiable (e.g. ReLU) activation functions, we can perform the
alternations effectively in this formulation. DANTE can also be extended to
networks with multiple hidden layers. In experiments on standard datasets,
neural networks trained using the proposed method were found to be promising
and competitive to traditional backpropagation techniques, both in terms of
quality of the solution, as well as training speed.Comment: 19 page
BLOOD VESSELS SEGMENTATION METHOD FOR RETINAL FUNDUS IMAGES BASED ON ADAPTIVE PRINCIPAL CURVATURE AND IMAGE DERIVATIVE OPERATORS
Diabetes is a common disease in the modern life. According to WHO’s data, in 2018, there were 8.3% of adult population had diabetes. Many countries over the world have spent a lot of finance, force to treat this disease. One of the most dangerous complications that diabetes can cause is the blood vessel lesion. It can happen on organs, limbs, eyes, etc. In this paper, we propose an adaptive principal curvature and three blood vessels segmentation methods for retinal fundus images based on the adaptive principal curvature and images derivatives: the central difference, the Sobel operator and the Prewitt operator. These methods are useful to assess the lesion level of blood vessels of eyes to let doctors specify the suitable treatment regimen. It also can be extended to apply for the blood vessels segmentation of other organs, other parts of a human body. In experiments, we handle proposed methods and compare their segmentation results based on a dataset – DRIVE. Segmentation quality assessments are computed on the Sorensen-Dice similarity, the Jaccard similarity and the contour matching score with the given ground truth that were segmented manually by a human
Antagonistic activity of cellular components of Pseudomonas species against Aeromonas hydrophila
Antagonistic effects of Pseudomonas fluorescens, P. aeruginosa and P. putida were studied against 12 strains of Aeromonas
hydrophila (Ah1–Ah12). Four different fractions of cellular component (i.e. whole cell product, heat killed whole cell product,
intra cellular product and extra cellular product) of all Pseudomonas species were equally effective in reducing growth of A.
hydrophila strains, as measured by the zone of inhibition in an in vitro sensitivity test and have potential action against A.
hydrophila infection in fishes
Gauging the three-nucleon spectator equation
We derive relativistic three-dimensional integral equations describing the
interaction of the three-nucleon system with an external electromagnetic field.
Our equations are unitary, gauge invariant, and they conserve charge. This has
been achieved by applying the recently introduced gauging of equations method
to the three-nucleon spectator equations where spectator nucleons are always on
mass shell. As a result, the external photon is attached to all possible places
in the strong interaction model, so that current and charge conservation are
implemented in the theoretically correct fashion. Explicit expressions are
given for the three-nucleon bound state electromagnetic current, as well as the
transition currents for the scattering processes
\gamma He3 -> NNN, Nd -> \gamma Nd, and \gamma He3 -> Nd. As a result, a
unified covariant three-dimensional description of the NNN-\gamma NNN system is
achieved.Comment: 23 pages, REVTeX, epsf, 4 Postscript figure
Gauging the spectator equations
We show how to derive relativistic, unitary, gauge invariant, and charge
conserving three-dimensional scattering equations for a system of hadrons
interacting with an electromagnetic field. In the method proposed, the
spectator equations describing the strong interactions of the hadrons are
gauged using our recently introduced gauging of equations method. A key
ingredient in our model is the on-mass-shell particle propagator. We discuss
how to gauge this on-mass-shell propagator so that both the Ward-Takahashi and
Ward identities are satisfied. We then demonstrate our gauging procedure by
deriving the gauge-invariant three-dimensional expression for the deuteron
photodisintegration amplitude within the spectator approach.Comment: 17 pages, REVTeX, epsf, 1 Postscript figur
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