Amirkabir University of Technology

About: Amirkabir University of Technology is a education organization based out in Tehran, Iran. It is known for research contribution in the topics: Nonlinear system & Finite element method. The organization has 15254 authors who have published 31165 publications receiving 487551 citations. The organization is also known as: Tehran Polytechnic & Tehran Polytechnic University.

Integrated Millimeter-Wave Wideband End-Fire 5G Beam Steerable Array and Low-Frequency 4G LTE Antenna in Mobile Terminals

Abstract: In this paper, a novel technique of collocating a millimeter-wave end-fire 5G beam steerable array antenna with a low-frequency planar inverted-F antenna (PIFA) is presented. In this technique, the low-frequency antenna can be transparent by using some grating strips between the low- and high-frequency antennas. A quad-element mm-wave array with end-fire radiation patterns operating in 22–31 GHz is integrated with a dual-band low-frequency PIFA in a mobile terminal. The novelty of this paper is the collocation of a high-frequency end-fire 5G antenna array with an old-generation low-frequency antenna, such as 4G in small space in the mobile terminal, without interfering with the radiation pattern and impedance matching of both low- and high-frequency antennas. The proposed 5G antenna covers 22–31 GHz and can scan ±50° with the scan loss of better than 3 dB. The coverage efficiency of the proposed mm-wave 5G antenna is better than 50% and 80% for a minimum gain of 4 and 0 dBi in 22–31 GHz, respectively. The gain of the high-frequency antenna array is better than 9.5 dBi at 28 GHz. The low-frequency antenna covers some practical 4G LTE bands from 740–960 MHz and 1.7–2.2 GHz bands. The measured results in both low and high frequencies agree well with the simulations.

Investigation of the physico-chemical reactivity of a mesoporous bioactive SiO2–CaO–P2O5 glass in simulated body fluid

Abstract: A new mesoporous bioactive glass (MpBaG) based on SiO 2 –CaO–P 2 O 5 by the sol–gel method has been successfully synthesized for biomedical applications. The obtained material was evaluated by thermal gravimetric analysis (TGA), differential scanning calorimetry (DSC), X-ray powder diffraction (XRD), Fourier transform infrared spectroscopy (FTIR), scanning electron microscope (SEM), energy dispersive spectroscopy (EDS) and N 2 adsorption analysis. The N 2 adsorption isotherm analysis showed that the pores were in mesopore size range and the MpBaG presented a specific surface area 137.9 m 2 g − 1 and a median pore size 15.4 nm. The surface reactivity of the MpBaG was studied in vitro in simulated body fluid (SBF). Inductively coupled plasma-atomic emission spectrometry (ICP-AES), SEM, EDS, XRD and FTIR were used to characterize the MpBaG surfaces and the SBF compositional changes. Immediately after immersion in SBF, reactions occurred on the surface of MpBaG. It is notable that the obtained results from FTIR and XRD analyses showed all typical characteristic peaks of bone-like hydroxyapatite (HAp). Also, it was obvious that the other new peaks after immersion in SBF were certainly related to the formation of hydroxycarbonate apatite (HCAp) and carbonate calcium (calcite). Finally, this research demonstrated that the synthesized MpBaG is a non-toxic and biocompatible material for ongoing osteogenic studies in segmental defects in the goat model in vivo .

A Morphological-Based License Plate Location

Abstract: License plate location is an important phase in vehicle license plate recognition for intelligent transport systems. This paper presents a robust and real time method of license plate location. The proposed algorithm consists of some stages. In the first stage, we extract vertical edges of the input image using Sobel mask. In the next stage, histogram analysis is used for finding the candidate regions of license plate. Candidate regions are also verified by defined compact factor. In the last stage, we locate the license plate exactly with some morphological operators. Experiments have been conducted for this algorithm. 400 images taken from various scenes were employed, including diverse angles, different lightening conditions. The algorithm can quickly and correctly detect the region of license plate. The license plate detecting rate of success is 83.50%.