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Institution

Technion – Israel Institute of Technology

EducationHaifa, Israel
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 & Upper and lower bounds. 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.


Papers
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Journal ArticleDOI
TL;DR: A simple model that describes traffic flow in two dimensions finds a sharp jamming transition that separates between the low-density dynamical phase in which all cars move at maximal speed and the high-density jammedphase in which they are all stopped.
Abstract: A simple model that describes traffic flow in two dimensions is studied. A sharp jamming transition is found that separates between the low-density dynamical phase in which all cars move at maximal speed and the high-density jammed phase in which they are all stopped. Self-organization effects in both phases are studied and discussed.

667 citations

Journal ArticleDOI
TL;DR: It is shown that the proposed TEAM, ThrEshold Adaptive Memristor model is reasonably accurate and computationally efficient, and is more appropriate for circuit simulation than previously published models.
Abstract: Memristive devices are novel devices, which can be used in applications ranging from memory and logic to neuromorphic systems. A memristive device offers several advantages: nonvolatility, good scalability, effectively no leakage current, and compatibility with CMOS technology, both electrically and in terms of manufacturing. Several models for memristive devices have been developed and are discussed in this paper. Digital applications such as memory and logic require a model that is highly nonlinear, simple for calculations, and sufficiently accurate. In this paper, a new memristive device model is presented-TEAM, ThrEshold Adaptive Memristor model. This model is flexible and can be fit to any practical memristive device. Previously published models are compared in this paper to the proposed TEAM model. It is shown that the proposed model is reasonably accurate and computationally efficient, and is more appropriate for circuit simulation than previously published models.

666 citations

Journal ArticleDOI
TL;DR: The results showed that the nanosensor array could differentiate between ‘healthy’ and ‘cancerous’ breath, and between the breath of patients having different cancer types, and could lead to the development of an inexpensive, easy-to-use, portable, non-invasive tool that overcomes many of the deficiencies associated with the currently available diagnostic methods for cancer.
Abstract: Tumour growth is accompanied by gene and/or protein changes that may lead to peroxidation of the cell membrane species and, hence, to the emission of volatile organic compounds (VOCs). In this study, we investigated the ability of a nanosensor array to discriminate between breath VOCs that characterise healthy states and the most widespread cancer states in the developed world: lung, breast, colorectal, and prostate cancers. Exhaled alveolar breath was collected from 177 volunteers aged 20–75 years (patients with lung, colon, breast, and prostate cancers and healthy controls). Breath from cancerous subjects was collected before any treatment. The healthy population was healthy according to subjective patient's data. The breath of volunteers was examined by a tailor-made array of cross-reactive nanosensors based on organically functionalised gold nanoparticles and gas chromatography linked to the mass spectrometry technique (GC-MS). The results showed that the nanosensor array could differentiate between ‘healthy’ and ‘cancerous’ breath, and, furthermore, between the breath of patients having different cancer types. Moreover, the nanosensor array could distinguish between the breath patterns of different cancers in the same statistical analysis, irrespective of age, gender, lifestyle, and other confounding factors. The GC-MS results showed that each cancer could have a unique pattern of VOCs, when compared with healthy states, but not when compared with other cancer types. The reported results could lead to the development of an inexpensive, easy-to-use, portable, non-invasive tool that overcomes many of the deficiencies associated with the currently available diagnostic methods for cancer.

666 citations

Journal ArticleDOI
TL;DR: A theoretical analysis and experimentally demonstrate a Pancharatnam-Berry phase-based diffraction grating for laser radiation at a wavelength of 10.6microm.
Abstract: Space-variant Pancharatnam-Berry phase optical elements based on computer-generated subwavelength gratings are presented. By continuously controlling the local orientation and period of the grating we can achieve any desired phase element. We present a theoretical analysis and experimentally demonstrate a Pancharatnam-Berry phase-based diffraction grating for laser radiation at a wavelength of 10.6microm.

664 citations

01 Jan 2000
TL;DR: These spectral methods may be used for compression and progressive transmission of 3D content, and are shown to be vastly superior to existing methods using spatial techniques, if slight loss can be tolerated.
Abstract: We show how spectral methods may be applied to 3D mesh data to obtain compact representations. This is achieved by projecting the mesh geometry onto an orthonormal basis derived from the mesh topology. To reduce complexity, the mesh is partitioned into a number of balanced submeshes with minimal interaction, each of which are compressed independently. Our methods may be used for compression and progressive transmission of 3D content, and are shown to be vastly superior to existing methods using spatial techniques, if slight loss can be tolerated.

661 citations


Authors

Showing all 31937 results

NameH-indexPapersCitations
Robert Langer2812324326306
Nicholas G. Martin1921770161952
Tobin J. Marks1591621111604
Grant W. Montgomery157926108118
David Eisenberg156697112460
David J. Mooney15669594172
Dirk Inzé14964774468
Jerrold M. Olefsky14359577356
Joseph J.Y. Sung142124092035
Deborah Estrin135562106177
Bruce Yabsley133119184889
Jerry W. Shay13363974774
Richard N. Bergman13047791718
Shlomit Tarem129130686919
Allen Mincer129104080059
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
2023147
2022390
20213,397
20203,526
20193,273
20183,131