Technion – Israel Institute of Technology

About: Technion – Israel Institute of Technology is a education organization based out in Haifa, Israel. It is known for research contribution in the topics: Population & Nonlinear system. The organization has 31714 authors who have published 79377 publications receiving 2603976 citations. The organization is also known as: Technion Israel Institute of Technology & Ṭekhniyon, Makhon ṭekhnologi le-Yiśraʼel.

Carbon Nanotubes Embedded in Oriented Polymer Nanofibers by Electrospinning

Abstract: The electrospinning process was used successfully to fabricate nanofibers of poly(ethylene oxide) (PEO) in which multiwalled carbon nanotubes (MWCNT) are embedded. Initial dispersion of MWCNTs in water was achieved using amphiphiles, either as small molecules (sodium dodecyl sulfate, SDS) or as a high molecular weight, highly branched polymer (Gum Arabic). These dispersions provided separation of the MWCNTs and their individual incorporation into the PEO nanofibers by subsequent electrospinning. The focus of this work is on the development of axial orientations in these multicomponent nanofibers. A theoretical model is presented for the behavior of rodlike particles representing CNTs in electrospinning. Initially the rods are randomly oriented, but due to the sinklike flow in a wedge they are gradually oriented mainly along the stream lines, so that straight CNTs are almost oriented upon entering the electrospun jet. The degrees of orientation of polymer, surfactant, and MWCNT were studied using X-ray dif...

Higher Order Thinking Skills and Low-Achieving Students: Are They Mutually Exclusive?

Abstract: Fostering students' higher order thinking skills is considered an important educational goal. Although learning theories see the development of students' thinking as an important goal for all students, teachers often believe that stimulating higher order thinking is appropriate only for high-achieving students. According to this view, low-achieving students are, by and large, unable to deal with tasks that require higher order thinking skills and should thus be spared the frustration generated by such tasks. Because this view may cause teachers to treat students in a nonegalitarian way, it is important to find out whether or not it is supported by empirical evidence. The goal of this study is to examine this issue in light of four different studies, by asking the following question: Do low-achieving students gain from teaching and learning processes that are designed to foster higher order thinking skills? Each of the4 studies addressed a different project whose goal was to teach higher order thinking in ...

Performance of the ATLAS trigger system in 2015

Abstract: During 2015 the ATLAS experiment recorded 3.8 fb(-1) of proton-proton collision data at a centre-of-mass energy of 13 TeV. The ATLAS trigger system is a crucial component of the experiment, respons ...

The implicit bias of gradient descent on separable data

Abstract: We examine gradient descent on unregularized logistic regression problems, with homogeneous linear predictors on linearly separable datasets. We show the predictor converges to the direction of the max-margin (hard margin SVM) solution. The result also generalizes to other monotone decreasing loss functions with an infimum at infinity, to multi-class problems, and to training a weight layer in a deep network in a certain restricted setting. Furthermore, we show this convergence is very slow, and only logarithmic in the convergence of the loss itself. This can help explain the benefit of continuing to optimize the logistic or cross-entropy loss even after the training error is zero and the training loss is extremely small, and, as we show, even if the validation loss increases. Our methodology can also aid in understanding implicit regularization in more complex models and with other optimization methods.