These days Floating Car Data (FCD) is one of the major data sources in Intelligent Transportation System (ITS) applications like route suggestion, traffic monitoring, traffic flow analysis and etc. Due to GPS limited accuracy and noises and road network errors, utilizing of FCD in ITS applications needs an efficient and accurate map matching framework. Map matching is a well-established problem which deals with mapping raw time stamped location traces to edge of road network graph. Along with high success rate, novel map matching applications faces several challenges including variable sampling frequency and processing speed of FCD big data. In this paper we have proposed a general, efficient, accurate and distributed map matching framework. The proposed framework can handle variable sampling frequency data accurately. Although this framework does not depend on additional data other than road network and GPS, achieved high success rate shows effectiveness of our system. We have used spatial proximity, heading difference, bearing difference and shortest path as our matching criteria. We also employed dynamic weights for each criteria to make our framework independent from local parameters. We have also employed confidence levels to improve our matching success rate. To answer low frequency data challenges, we have present an extra criteria based on A* shortest path method with dynamic weighting method. We have used HDOP for weighting shortest path criteria. When we are not confident enough about a point matching, we use shortest path criteria to improve success rate and by this method we keep our overhead low. For the evaluation we have studied New York City (NYC) OSM trajectories as the case study. We also used OSM NYC road network as the base map. The evaluation results indicate 95.2% MM success rate in high sampling mode (10s) along with 89.5% success rate in low sampling frequency (120s). We have compared our method with a known map matching method that In the case of low sampling frequency, our method has improved matching accuracy up to 9.7%. We have evaluated the effect of utilizing shortest path criteria in low frequency scenario. Our results show that using shortest path have improved our result up to 3.5%. One of the major challenges in using FCD is storage, managing, analysis and batch processing of this big data. To face this challenge in this framework we have used cloud computing technologies along with MapReduce paradigm based on Hadoop framework. The proposed cloud computing based framework can answer technical challenges for efficient and real-time storage, management, process and analyze of traffic big data. Our evaluation results indicate we have matched 7000 points/second on a cluster with 5 processing nodes. We have also processed 5 million records in 530 seconds using a cluster with 5 processing nodes. The main contributions are as follows: 1) we have proposed a general, distributed map matching framework using cloud computing technologies to answer to upstream ITS applications, 2) We have improved an efficient and accurate map matching algorithm which can handle different sampling frequencies using shortest path method and confidence level, 3) we have used dynamic method for weighting geometric, directional and shortest path constrains.

This paper discusses the design and implementation of an inductorless differential VCO with a maximum oscillation frequency of 20 GHz, in a 47 GHz SiGe process technology. The VCO is based on a full-wave rectification frequency-doubling technique, applied to a half rate differential single-stage feedback oscillator. It also benefits from a new circuit phenomenon named hereinafter Self Injection Locking (SIL). The implemented VCO has an area of 0.5 mm2 and features a remarkably high ratio of VCO frequency to process fT. Based on measurement results, the VCO consumes a DC power of less than 165 mW and exhibits a phase noise of -96 dBc/Hz at 1 MHz offset.

Most geologic changes have a seismic response but sometimes this is expressed only in certain spectral ranges hidden within the broadband data. Spectral decomposition is one of the methods which can be utilized to help interpreting such cases. There are several time-frequency methods including: short-time Fourier transform (STFT), continuous wavelet transform (CWT), Wigner-Ville distribution (WVD), S-transform, and matching pursuit decomposition (MPD). In this paper, we use the MPD method. This method is newer than the other time-frequency methods used in exploration seismology. Mallat and Zhang (1993) have improved time and frequency resolution simultaneously by using MPD method. In this method, a signal is decomposed into constructive wavelets. Time and frequency properties of wavelets are used locally for spectral decomposition. Pursuits are the algorithms which search the best time-frequency matching between the signal and a linear combination of selected wavelets from wavelet dictionary. Matching pursuit which is an iterative procedure optimizes signal estimation by each new wavelet chosen from a dictionary. These wavelets combined linearly to obtain the best match with the signal. A signal should expand to waveforms which their time-frequency properties could be matched to local structures. Such waveforms are called time-frequency atoms. There are many approaches to match wavelets of dictionary to a seismic signal and to obtain time-frequency spectrum in matching pursuit decomposition. The base of all approaches is the Mallat and Zhang’s algorithm. However, computing time of the original algorithm is very high due to many iterations and that is why particular conditions have been applied in different researches to limit the matching pursuit algorithm for obtaining the lower performing time. In this work, particular conditions are rather similar to Wang’s (2007) method. On seismic data, layer thickness is described on the basis of the seismic travel time. When a layer with different properties has a thickness by one-fourth wavelength, top and base reflections will interfere constructively. For thin layers less than tuning thickness, combined seismic amplitude decreases with thickness (when reflection coefficients of the top and of the base are opposite). Generally, spectral decomposition has many applications in interpretation of seismic sections and so there will be extra needs to study and develop them. Thin layers and many stratigraphic hydrocarbon reservoirs are beneath the threshold of the vertical seismic resolution (tuning thickness) and because of their low thicknesses, they are not resolvable. For this reason, mapping the small-scale geological structures is one of the important interpretational cases. When the thickness of a thin layer decreases pick frequency slightly increases. In this work, this issue has been used to detect thin layers by time-frequency spectrum and by single-frequency sections obtained from MPD. In this paper, we investigated the performance of the matching pursuit decomposition for time-frequency analysis of seismic sections to delineate and detect thin layers on synthetic data (including simple thin layer model and also wedge model) and real data. It is observed that the interpretation of thin layers is simpler by single-frequency sections. It is shown that for a simple thin layer if considerable frequency in single-frequency sections increases, ability in resolving layer interfaces would be increased. In the wedge model, as the frequency increases resolution threshold of layer interfaces moves to a lower thickness and therefore it would be possible to detect lower thickness layers. The tuning thickness has been decreased from 19 meters in original seismic section to 12 meters in 80 Hz frequency section. In the real data, it is shown that when a thin layer is not resolvable in a seismic section it might be detected using the MPD method. In this case, by providing 20, 40, 60, 80 and 100 Hz single-frequency sections when high frequency sections are studied, interfaces of thin layer are appeared gradually. It is concluded that time-frequency sections are useful instruments to detect and delineate thin layers.

‎T‎oday, with the increasing access to administrative databases and the high volume of data registered in organizations, the traditional methods of data collection and analysis are not effective due to the response burden. Accordingly, the transition from traditional ‎survey methods to modern methods of data collection and analysis with the register-based statistics approach has received more and more attention from statistical data analysts. In register-based methods, it is especially important to create an integrated database by linking database records of different organizations. ‎Many record linkage algorithms have been developed using the Fellegi and Sunter ‎‎‎model‎. ‎The Fellegi-Sunter model does not leverage information contained in field values and does not care about specific possible values of a string variable (more common and less common values)‎. ‎In this ‎‏‎article‎, ‎a method that can be able to infuse these differences in specific possible values of a string variable in the Fellegi-Sunter model is presented‎.‎ ‎‎‎On the ‎other, ‎‎the ‎‎model proposed by Fellegi-Sunter‎, ‎as well as the method for adjusting the matching weights in the frequency-based record linkage‎, ‎binding in this paper, ‎are based on the assumption of conditional independence‎. ‎In some applications of record linkage‎, ‎this assumption is not met in agreement or disagreement of common variables which are used for matching‎. ‎One solution used in such a case is to use log-linear model which allows interactions between matching variables in the model‎.‎‎ In this ‎‏‎article‎, ‎we deal with two generalizations of Fellegi-Sunter ‎‎‎‎‎model, ‎one with the correction of the matching weights and the other with using a log-linear model with interactions in absence of conditional independence‎. ‎The proposed methods are implemented on labour force data set of Statistical Centre of Iran using R‎.

In this paper, a wideband rectenna without using matching networks is presented. In addition of wide bandwidth, the omnidirectional radiation pattern, maximum radio frequency to dc conversion efficiency, harvesting capability of the minimum input power level, easy fabrication process cause this antenna be a good choice for radio frequency energy harvesting applications. Matching network has been eliminated and the antenna structure has been used to match with rectifier for energy harvesting with maximum efficiency. Based on the minimum input power level, two different structures have been suggested as the rectenna. The suggestive model meets proper efficiency within the frequency band of 1.71-2.5GHz and harvests the input power levels of 0dBm and -5dBm by implementing the two proposed structures with the maximum efficiencies of 74 and 68%, respectively. The multi-tone state has been also investigated which indicated the maximum obtained efficiencies of about 42 and 44% for the 2- and 3-tone modes, respectively.

This article aims at the improvement of Synthetic Aperture Radar (SAR) resolution by using a Matched Filter (MF) based on the Fractional Fourier Transform (FrFT) that has been called a Matched Slope Filter (MSF). Generally, the received SAR signals are processed by well-known algorithms to extract the final image, such as the Chirp Scaling Algorithm (CSA) and the Range Doppler Algorithm (RDA). Implementing a Matched Filter (MF) that aims at compressing the received signal in the range and azimuth directions is a principal part of these algorithms to deliver target positioning and high resolution. Because the transmitted signal by SARs has often been Linear Frequency Modulated (LFM), the received echo from the targets in the range direction is the LFM. On the other hand, there is always a chirp signal in the azimuth orientation. Thus, this paper proposes the Matched on Slope Filter to improve the compression of the azimuth signals. It's clear the proposed method has been adopted for LFM signal compression in the range direction also. The evaluation results show that our method that uses the FrFT in the time-frequency domain for implementing a Matched Slope Filter enhances the resultant azimuth resolution and reduces the sidelobe level compared to the other frequency-based method.

A historical review of Radio Frequency Energy Harvesting (RFEH) Rectenna (Rectifier Antenna) Systems without a matching network is performed, with emphasis on the antenna part. As the antenna, matching network and rectifier are the main parts of the rectenna systems, the reasons behind the elimination of the matching network are presented and different special antennas suitable for direct matching to the rectifier, without using a matching network, are reviewed. Since the diode in the rectifier is a nonlinear element, its input impedance is changed with varying operating conditions such as input power, frequency and output load impedance of the rectifier. So, it is a challenge for researchers to match the antenna impedance directly to the rectifier in variable operational conditions.

In this article, an active electrically small Horn antenna for very high frequency (VHF) and ultra-high frequency (UHF) frequencies is presented. The proposed horn antenna has a height of 5 cm and a diameter of 4.28 cm which can cover 6-12 GHz without a special active circuit with the VSWR of less than 2. A Non-foster Active Adaptation Circuit is used to reduce the antenna input frequency from 164 MHz to 880 MHz. Good matching is visible between the simulation results and the measurement of the antenna reflection coefficient with the active matching circuit. The proposed structure has more than 137 % bandwidth. With the proposed active antenna, the problem of non-portability of VHF and UHF Horn antenna antennas has been solved. Finally, by analyzing the time domain, the stability of the circuit is examined, and the results of the stability test show that the system, including the antenna and the circuit, is stable. The antenna and the matching circuits are simulated by CST microwave studio and advanced design system, respectively.

Coded excitation is one of the important methods to increase medical ultrasound imaging depth. Commonly match filters are used to retain the axial resolution of ultrasound images in this type of excitation. Frequency dependent attenuation in the propagation medium of ultrasound wave, degrades the pulse compression performance of matched filter in coded excitation ultrasound imaging. In this paper fractional Fourier transform is proposed as an alternative method for pulse compression in high attenuating medium. Additionally a chirp signal detector is proposed in fractional domain in order to detect the echo signals and compare the performance of matched filter and fractional Fourier transform quantitatively. The comparison of this two methods shows that signal to noise ratio of fractional Fourier transform output is more than that of matched filter in deep parts in which ultrasound wave faces high level of attenuation. Simulation results show that pulse compression with fractional Fourier transform is less sensitive to frequency dependent attenuation. In other words, in the presence of frequency dependent attenuation, the detection probability of echo signal in fractional domain is more than that of match filter. The amount of improvement in the proposed method depends on the imaging depth and the value of attenuation in the medium. In other words, the more the imaging depth the more improvement is achieved by the propose method. Finally using Wigner-Ville time-frequency representation we consider the reason of better performance of fractional Fourier transform over matched filter.