About: ASELSAN is a company organization based out in Ankara, Turkey. It is known for research contribution in the topics: Radar & Antenna (radio). The organization has 1045 authors who have published 1366 publications receiving 10840 citations.
Papers published on a yearly basis
TL;DR: In this paper, the authors cover the latest developments in enhanced mechanical properties of aluminium alloys, and high performance joining techniques, including laser beam welding and friction stir welding, and compare them with the traditional aluminum alloys.
Abstract: Aluminium alloys have been the primary material for the structural parts of aircraft for more than 80 years because of their well known performance, well established design methods, manufacturing and reliable inspection techniques. Nearly for a decade composites have started to be used more widely in large commercial jet airliners for the fuselage, wing as well as other structural components in place of aluminium alloys due their high specific properties, reduced weight, fatigue performance and corrosion resistance. Although the increased use of composite materials reduced the role of aluminium up to some extent, high strength aluminium alloys remain important in airframe construction. Aluminium is a relatively low cost, light weight metal that can be heat treated and loaded to relatively high level of stresses, and it is one of the most easily produced of the high performance materials, which results in lower manufacturing and maintenance costs. There have been important recent advances in aluminium aircraft alloys that can effectively compete with modern composite materials. This study covers latest developments in enhanced mechanical properties of aluminium alloys, and high performance joining techniques. The mechanical properties on newly developed 2000, 7000 series aluminium alloys and new generation Al–Li alloys are compared with the traditional aluminium alloys. The advantages and disadvantages of the joining methods, laser beam welding and friction stir welding, are also discussed.
08 Oct 2016
University of Ljubljana1, University of Birmingham2, Czech Technical University in Prague3, Linköping University4, Austrian Institute of Technology5, Carnegie Mellon University6, Parthenope University of Naples7, University of Isfahan8, Autonomous University of Madrid9, University of Ottawa10, University of Oxford11, Hong Kong Baptist University12, Kyiv Polytechnic Institute13, Middle East Technical University14, Hacettepe University15, King Abdullah University of Science and Technology16, Pohang University of Science and Technology17, University of Nottingham18, University at Albany, SUNY19, Chinese Academy of Sciences20, Dalian University of Technology21, Xi'an Jiaotong University22, Indian Institute of Space Science and Technology23, Hong Kong University of Science and Technology24, ASELSAN25, Australian National University26, Commonwealth Scientific and Industrial Research Organisation27, University of Missouri28, University of Verona29, Universidade Federal de Itajubá30, United States Naval Research Laboratory31, Marquette University32, Graz University of Technology33, Naver Corporation34, Imperial College London35, Electronics and Telecommunications Research Institute36, Zhejiang University37, University of Surrey38, Harbin Institute of Technology39, Lehigh University40
TL;DR: The Visual Object Tracking challenge VOT2016 goes beyond its predecessors by introducing a new semi-automatic ground truth bounding box annotation methodology and extending the evaluation system with the no-reset experiment.
Abstract: The Visual Object Tracking challenge VOT2016 aims at comparing short-term single-object visual trackers that do not apply pre-learned models of object appearance. Results of 70 trackers are presented, with a large number of trackers being published at major computer vision conferences and journals in the recent years. The number of tested state-of-the-art trackers makes the VOT 2016 the largest and most challenging benchmark on short-term tracking to date. For each participating tracker, a short description is provided in the Appendix. The VOT2016 goes beyond its predecessors by (i) introducing a new semi-automatic ground truth bounding box annotation methodology and (ii) extending the evaluation system with the no-reset experiment. The dataset, the evaluation kit as well as the results are publicly available at the challenge website (http://votchallenge.net).
TL;DR: It is demonstrated that extremely high repetition rates, which make ablation cooling possible, reduce the laser pulse energies needed for ablation and increase the efficiency of the removal process by an order of magnitude over previously used laser parameters.
Abstract: The use of femtosecond laser pulses allows precise and thermal-damage-free removal of material (ablation) with wide-ranging scientific, medical and industrial applications. However, its potential is limited by the low speeds at which material can be removed and the complexity of the associated laser technology. The complexity of the laser design arises from the need to overcome the high pulse energy threshold for efficient ablation. However, the use of more powerful lasers to increase the ablation rate results in unwanted effects such as shielding, saturation and collateral damage from heat accumulation at higher laser powers. Here we circumvent this limitation by exploiting ablation cooling, in analogy to a technique routinely used in aerospace engineering. We apply ultrafast successions (bursts) of laser pulses to ablate the target material before the residual heat deposited by previous pulses diffuses away from the processing region. Proof-of-principle experiments on various substrates demonstrate that extremely high repetition rates, which make ablation cooling possible, reduce the laser pulse energies needed for ablation and increase the efficiency of the removal process by an order of magnitude over previously used laser parameters. We also demonstrate the removal of brain tissue at two cubic millimetres per minute and dentine at three cubic millimetres per minute without any thermal damage to the bulk.
01 Jul 2017
University of Ljubljana1, University of Birmingham2, Czech Technical University in Prague3, Linköping University4, Austrian Institute of Technology5, Autonomous University of Madrid6, Parthenope University of Naples7, University of Isfahan8, University of Oxford9, Superior National School of Advanced Techniques10, Middle East Technical University11, Dalian University of Technology12, Chinese Academy of Sciences13, ASELSAN14, United States Naval Research Laboratory15, National University of Defense Technology16, University of Science and Technology of China17, Electronics and Telecommunications Research Institute18, Zhejiang University19, Beijing University of Posts and Telecommunications20, Huazhong University of Science and Technology21, University of Missouri22, Carnegie Mellon University23, General Electric24, King Abdullah University of Science and Technology25, University of California, Merced26, University of Surrey27, University at Albany, SUNY28
TL;DR: The Visual Object Tracking challenge VOT2017 is the fifth annual tracker benchmarking activity organized by the VOT initiative; results of 51 trackers are presented; many are state-of-the-art published at major computer vision conferences or journals in recent years.
Abstract: The Visual Object Tracking challenge VOT2017 is the fifth annual tracker benchmarking activity organized by the VOT initiative. Results of 51 trackers are presented; many are state-of-the-art published at major computer vision conferences or journals in recent years. The evaluation included the standard VOT and other popular methodologies and a new "real-time" experiment simulating a situation where a tracker processes images as if provided by a continuously running sensor. Performance of the tested trackers typically by far exceeds standard baselines. The source code for most of the trackers is publicly available from the VOT page. The VOT2017 goes beyond its predecessors by (i) improving the VOT public dataset and introducing a separate VOT2017 sequestered dataset, (ii) introducing a realtime tracking experiment and (iii) releasing a redesigned toolkit that supports complex experiments. The dataset, the evaluation kit and the results are publicly available at the challenge website1.
••17 Apr 2007
TL;DR: In this article, a general analysis of a frequency diverse transmit array antenna with a periodic modulated pattern in range, angle and time is presented, which makes a continuous scanning in range and angle without using any phase shifters.
Abstract: A general analysis of a frequency diverse transmit array antenna with a periodic modulated pattern in range, angle and time is presented. This antenna array system makes a continuous scanning in range and angle without using any phase shifters. The scanning is achieved using the frequency diversity by inserting a small amount of progressive frequency shift to each antenna element. The theory shows that there is the same modulation pattern in time, range and angle by taking the remaining two parameters fixed. The simulation results for radiation patterns of a binomial distribution array are presented. The expressions for determining the position and the angular bearing of a target for this type of antenna array system are given.
Showing all 1058 results
|Damon B. Farmer||56||162||18543|
|Margaret S. Livingstone||53||135||17259|
|Çetin Kaya Koç||41||195||7946|
|Osama A. Kandil||19||136||1245|
|Klaus Werner Schmidt||18||108||1199|
|H. Nevzat Özgüven||18||55||1868|
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