Frequency Tuned Research Articles

Frequency-tuned selectivity enhancement of Mg@ZnO-TiO2 nanoflake-based heterojunction sensor devices.

Selectivity improvement by the frequency tuning of Mg@ZnO-TiO2 nanoflake-based heterojunction devices under exposure to different volatile organic compounds is the prime focus of the present paper. The synthesis of Mg@ZnO-TiO2 nanoflakes was carried out using a solution process followed by a low-cost hydrothermal method. A capacitive measurement approach was used to find the resonant frequencies of the device in 2-butanone, acetone, 2-propanol, ethanol, and methanol environments in the frequency range from 0.001 to 220 kHz. A Cole-Cole plot derived from impedance measurements suggested that the device impedance consisted of capacitance (Cz = 2.01 pF and CT = 2.17 pF) and resistance (Rz = 13 552.2 kΩ and RT = 3500.574 kΩ) from the ZnO nanoflake layer and TiO2 thin film layer, respectively. The maximum capacitive responses to 2-butanone (C4H8O), acetone (C3H6O), 2-propanol (C3H8O), ethanol (C2H5OH), and methanol (CH3OH) were recorded at resonant frequencies of 1.000 kHz, 0.791 kHz, 0.702 kHz, 0.319 kHz and 0.103 kHz, respectively, at the corresponding temperature of 125 °C, 100 °C, 100 °C, 75 °C, and 75 °C, respectively. The device offered optimum capacitive responses of 221.32%, 242.65%, 317.09%, 373.96%, and 401.24% to 100 ppm of 2-butanone, acetone, 2-propanol, ethanol, and methanol, respectively. Experimental observation confirmed that the capacitive response inversely varied with the resonant frequency. Such an inverse relation was correlated with the dielectric variation at the junction interface, change in the molecular weights of VOCs, and their sticking coefficient. An equivalent circuit diagram with the help of adsorption-desorption isotherms and an energy band model is illustrated to correlate the device optimum capacitive response at the tuned frequencies under different VOC media.

Fabric Defect Detection Algorithm Based on Image Saliency Region and Similarity Location

In order to solve the problem of defect detection and to contour accurate segmentation of periodic texture fabric images, a fabric defect detection method based on saliency region and similarity location is proposed. Firstly, the image to be detected was processed by color space conversion, Gaussian filtering, and contrast enhancement, and a frequency-tuned (FT) salient region detection algorithm was used to estimate a saliency map of the enhanced image. The fabric image was divided into image blocks of the same size with overlapping areas through a sliding window, and then the statistical parameters of each image block were calculated. The outliers in the statistical parameters were filtered out using inter-quartile range (IQR). Through the positioning and processing of image defects, abnormal elimination was carried out, and the defect outline was finally obtained. The experimental results show that the method proposed in this paper has better performance in terms of qualitative characterization of Acc, Precision, Recall, and F1 score.

Salient target detection in hyperspectral image based on visual attention

Salient target detection in hyperspectral image is a significant task in image segmentation, target tracking, image classification and so on. Many existing saliency detection algorithms for hyperspectral image detection cannot present the boundary of the salient target well and the description of the target is not enough. A method based on visual attention to detect the salient target of hyperspectral image is proposed in this paper. In this method, frequency-tuned (FT) salient detection model is combined with spectral salient to detect target in hyperspectral image. FT model is used to get target with clear border, and spectral information is made full use of to improve the accuracy of target detection. Firstly, FT is used to detect saliency of hyperspectral image and the saliency map is generated. Then, spectral information of the hyperspectral image is measured by similarity, and the spectral saliency is obtained by calculating spectral angle distance between the spectral vectors. Finally, the FT's saliency map and the spectral saliency map are combined to form the final saliency target maps. Experimental results show that our method is superior to other methods in saliency target detection of hyperspectral image, and the precision-recall curve and F-measure are better as well.

Improvement of the phase noise model based on an optoelectronic oscillator using a directly modulated distributed feedback laser

A scheme of dual-loop optoelectronic oscillator (OEO) based on a directly modulated distributed feedback (DFB) laser is proposed and experimentally demonstrated. In the proposed scheme, thanks to the DFB laser with enough output optical power utilized as an optical source and a modulator at the same time, high-performance microwave signals are generated without external modulator and erbium-doped fiber amplifier (EDFA). A theoretical model based on the control theory is detailed to assess the single sideband (SSB) phase noise performance of the dual-loop OEO. The laser frequency noise under small-signal direct modulation is proposed and introduced to make the phase noise model more complete for the first time. According to the theoretical analysis, the close-in (<1 MHz) SSB phase noise floor of the dual-loop OEO is dominated by the flicker noise when the offset frequency is below 10 kHz, and determined by the laser’s relative intensity noise (RIN) when the offset frequency is beyond 10 kHz. Microwave signals with the frequency tuned from 8 to 12 GHz and 3-dB linewidth less than 100 Hz are realized. The side mode suppression ratio (SMSR) of the generated microwave signals are measured to be 55 dB based on the dual-loop configuration. Meanwhile, within the whole frequency tuning range, the SSB phase noises of about −125 dBc/Hz at 10 kHz offset frequency are obtained. The experimental results of the SSB phase noise agree very well with the simulation results based on the theoretical model.

The second harmonic neurons in auditory midbrain of Hipposideros pratti are more tolerant to background white noise

Although acoustic communication is inevitably influenced by noise, behaviorally relevant sounds are perceived reliably. The noise-tolerant and -invariant responses of auditory neurons are thought to be the underlying mechanism. So, it is reasonable to speculate that neurons with best frequency tuned to behaviorally relevant sounds will play important role in noise-tolerant perception. Echolocating bats live in groups and emit multiple harmonic signals and analyze the returning echoes to extract information about the target features, making them prone to deal with noise in their natural habitat. The echolocation signal of Hipposideros pratti usually contains 3–4 harmonics (H1H4), the second harmonic has the highest amplitude and is thought to play an essential role during echolocation behavior. Therefore, it is reasonable to propose that neurons tuned to the H2, named the H2 neurons, can be more noise-tolerant to background noise. Taking advantage of bat's stereotypical echolocation signal and single-cell recording, our present study showed that the minimal threshold increases (12.2 dB) of H2 neurons in the auditory midbrain were comparable to increase in bat's call intensity (14.2 dB) observed in 70 dB SPL white noise condition, indicating that the H2 neurons could work as background noise monitor. The H2 neurons had higher minimal thresholds and sharper frequency tuning, which enabled them to be more tolerant to background noise. Furthermore, the H2 neurons had consistent best amplitude spikes and sharper intensity tuning in background white noise condition than in silence. Taken together, these results suggest that the H2 neurons might account for noise-tolerant perception of behaviorally relevant sounds.

Klasifikasi Jenis Buah dan Sayuran Menggunakan SVM Dengan Fitur Saliency-HOG dan Color Moments

Fruit is part of a plant that comes from the flower or pistil of the plant and usually has seeds. Meanwhile, vegetables are leaves, legumes, or seeds that can be cooked. Fruits and vegetables have many variants that can be distinguished based on color, shape, and texture. The Saliency-HOG feature and Color moments were used in this study to extract shapes and colors features in fruit and vegetable images. In this study, the Support Vector Machine (SVM) method was used to classify the types of fruit and vegetables. The dataset used in this study is a public dataset consisting of 114 images of fruit and vegetables. Each type of fruit and vegetable contains 100 images consisting of 70 images as training data and 30 images as testing data. There are 4 saliency features used in the testing phase, namely Region Contrast (RC), Frequency-tuned (FT), Histogram Contrast (HC), and Spectral Residual (SR). Based on the test results, the Saliency-HOG and Color Moments features were able to provide good results with the best precision, recall, and accuracy being 98.57%, 98.55%, and 99.120%, respectively.

Robustness Improvement of Visual Templates Matching Based on Frequency-Tuned Model in RatSLAM.

This paper describes an improved brain-inspired simultaneous localization and mapping (RatSLAM) that extracts visual features from saliency maps using a frequency-tuned (FT) model. In the traditional RatSLAM algorithm, the visual template feature is organized as a one-dimensional vector whose values only depend on pixel intensity; therefore, this feature is susceptible to changes in illumination intensity. In contrast to this approach, which directly generates visual templates from raw RGB images, we propose an FT model that converts RGB images into saliency maps to obtain visual templates. The visual templates extracted from the saliency maps contain more of the feature information contained within the original images. Our experimental results demonstrate that the accuracy of loop closure detection was improved, as measured by the number of loop closures detected by our method compared with the traditional RatSLAM system. We additionally verified that the proposed FT model-based visual templates improve the robustness of familiar visual scene identification by RatSLAM.

Robust and Accelerated Frequency-Tuned Salient Object Detection via Color Quantization

Frequency-tuned (FT) saliency detector has been widely used in various image processing and computer vision applications. However, removing high frequency noise and textures by a Difference of Gaussians (DoG) filter is still time-consuming, which hinders real-time execution of FT. In this paper, an improved algorithm is proposed to tackle the obstacles to performance improvement. It exploits color quantization within natural images and substitute Gaussian filtering process. Experimental results demonstrate that the proposed method runs up to about two times as fast as FT while resulting in almost the same saliency map.

A Tunable Planar Balun with an Isolation Circuit Using Varactors Loaded Coupled Lines

In this paper, a frequency tunable planar balun composed of varactors loaded coupled lines (VL-CLs) is presented. By tuning the capacitances of the varactors, a wide frequency tuning range is obtained. Moreover, good impedance match, balanced output ports amplitude, and consistent output ports phase difference (PD) are maintained during the tuning. A detailed theoretical analysis using the signal flow diagram and the even-odd mode method is presented to clarify the characteristics of the proposed balun. To achieve ideal output matching and isolation for the proposed balun, a novel frequency tuned isolation circuit (IsC) is designed and connected to the balun. In theory, a frequency tuning range of 200% can be realized. In practice, due to the limited capacitances of the varactors, a prototype with a tunable frequency of 1.0 GHz ~ 2.0 GHz (66.7%) is designed, fabricated, and measured. The measured results show that more than21 dB of return loss (RL), 180° ± 1.8° of phase difference, 0.43 dB of amplitude imbalance (AP), and 22 dB of isolation are obtained at all tuning center frequencies, agreeing well with the simulated results.

Vision-Based Target Tracking for Unmanned Surface Vehicle Considering Its Motion Features

Target tracking is a key task for maintenance of maritime rights and interests in the coastal countries, which mainly depends on the cruises of large official ships, and their deficiencies are high cost and less stealth. USVs (Unmanned Surface Vehicles) have been gradually employed in maritime ISR(Intelligence, Surveillance and Reconnaissance) due to autonomy, safety and flexibility. In this paper, a target tracking algorithm for USV's vision is proposed, which considers motion features of the USV, such as velocity, pitch and heading. Firstly, a CM(Centroid Matching) method for the target detection is proposed based on FT(Frequency-Tuned) saliency method, which can remove environment disturbances. Secondly, a fDSST(fast Discriminative Scale Space Tracker) is improved for target tracking by considering motion information of the USV from aboard GPS and IMU(Inertial Measurement Unit), where the learning rates of the correlation filters are adjusted adaptively according to variety of the velocity, pitch and heading of the USV. Lastly, the modified target detection and tracking are integrated to acquire a robust tracking result. Based on our USV called as `Jiuhang 490', sea tracking trials for rubber boat in four encountering scenes are executed at Nanjiang port in Qingdao city, China in July 2018. The favorable performance of the proposed algorithm is quantitatively validated comparing to the original fDSST algorithm in the accuracy of position, scale of the target and the tracking speed.

Biologically Visual Perceptual Model and Discriminative Model for Road Markings Detection and Recognition

The detection and recognition of arrow markings is a basic task of autonomous driving. To achieve all-day detection and recognition of arrow markings in complex environment, we propose a hybrid model by exploiting the advantages of biologically visual perceptual model and discriminative model. Firstly, the arrow markings are extracted from the complex background in the region of interest (ROI) by the biologically visual perceptual model using the frequency-tuned (FT) algorithm. Then candidates for road markings are detected as maximally stable extremal regions (MSER). In recognition stage, biologically visual perceptual model calculates the sparse solution of arrow markings using sparse learning theory. Finally, discriminative model uses the Adaptive Boosting (AdaBoost) classifier trained by sparse solution to classify arrow markings. Experimental results show that the hybrid model achieves detection and recognition of arrow markings in complex road conditions with the precision, recall, and F-measure being 0.966, 0.88, and 0.92, respectively. The hybrid model is robust and has some advantages compared with other state-of-the-art methods. The hybrid model proposed in this paper has important theoretical significance and practical value for all-day detection and recognition in complex environment.

Resonance frequency tuning of an RF cavity through sliding mode extremum seeking

Tuning of the natural resonance frequency of an RF cavity is crucial to achieve maximum power transfer from the cavity to the beam, to reduce power requirements, and to guarantee a predictable particle speed gain within each accelerator structure. So far, most operational cavities are frequency tuned through a phase comparison technique, which is sensitive to temperature variations if the facility or signal transportation cables are not temperature controlled. Temperature induced phase errors render this technique labor and time intensive. This paper presents an RF cavity tuning scheme, based on reflected power measurements and sliding mode extremum seeking control, to eliminate the phase measurement related difficulties. A stability analysis provides conditions on how to choose the controller parameters to guarantee stable system operation up to twice the cavity bandwidth, which is a controllable bandwidth improvement of a factor of two. The system has been implemented in two of TRIUMF’s (Canada’s particle accelerator centre) room temperature resonators and long term measurements show that the system effectively counteracts the RF heating effect as well as diurnal temperature variations.

An Improved Text Localization Method for Natural Scene Images

In order to extract text information effectively from natural scene image with complex background, multi-orientation perspective and multilingual languages, we present a new method based on the improved Stroke Feature Transform (SWT). Firstly, The Maximally Stable Extremal Region (MSER) method is used to detect text candidate regions. Secondly, the SWT algorithm is used in the candidate regions, which can improve the edge detection compared with tradition SWT method. Finally, the Frequency-tuned (FT) visual saliency is introduced to remove non-text candidate regions. The experiment results show that, the method can achieve good robustness for complex background with multi-orientation perspective, various characters and font sizes.

Investigation of pulsed mode operation with the frequency tuned CAPRICE ECRIS.

In order to increase the intensity of the highly charged ions produced by the Electron Cyclotron Resonance Ion Sources (ECRISs), techniques like the frequency tuning and the afterglow mode have been developed and in this paper the effect on the ion production is shown for the first time when combining both techniques. Recent experimental results proved that the tuning of the operating frequency of the ECRIS is a promising technique to achieve higher ion currents of higher charge states. On the other hand, it is well known that the afterglow mode of the ECRIS operation can provide more intense pulsed ion beams in comparison with the continuous wave (cw) operation. These two techniques can be combined by pulsing the variable frequency signal driving the traveling wave tube amplifier which provides the high microwave power to the ECRIS. In order to analyze the effect of these two combined techniques on the ion source performance, several experiments were carried out on the pulsed frequency tuned CAPRICE (Compacte source A Plusiers Résonances Ionisantes Cyclotron Electroniques)-type ECRIS. Different waveforms and pulse lengths have been investigated under different settings of the ion source. The results of the pulsed mode have been compared with those of cw operation.

Enhanced cortical representation of auditory frequency as a result of early blindness

A fundamental ability found to be enhanced by early blindness is frequency discrimination; however, the neural basis of this enhancement is unclear. Responses to a variety of auditory stimuli have been found throughout occipital cortex, but clear evidence for frequency tuning has not been reported. In auditory cortex, attenuated responses to pure tones have been found in early blind and anophthalmic individuals (Stevens and Weaver, 2009; Watkins et al., 2013). Here, we measured responses to pure tones in 5 early-blind and 5 age-matched sighted subjects to assess group differences in the organization of auditory frequency representations within occipital and auditory cortex. Methods: Stimuli consisted of pure tones ranging from 88 to 8000 Hz, which were presented in partially randomized order while subjects performed a 1-back frequency matching task. Data were analyzed using an adaptation of the population receptive field technique (Dumoulin and Wandell, 2008). We modeled the aggregate receptive field underlying each voxel's response as a one-dimensional Gaussian function of frequency, with a center and standard deviation that reflect preferred frequency and tuning bandwidth, respectively. Results: Within auditory cortex, we could reliably measure individual tonotopic maps in both subject groups, and we saw no evidence for an attenuation of responses. Relative to controls, early-blind subjects showed an enhanced representation of low to middle frequencies (<4 kHz) and narrower tuning bandwidths. In occipital cortex, blind but not sighted subjects showed evidence of auditory frequency tuning. Frequency tuned voxels in occipital cortex favored the mid-frequency range (1-8 kHz) and had narrower bandwidths then those found in auditory cortex. Conclusions: Early blindness results in an increased cortical representation of behaviorally relevant frequencies within both auditory and occipital cortex. Future work will examine how responses in these cortical areas relate to frequency discrimination performance in individual subjects. Meeting abstract presented at VSS 2014

Viscoelastic effects on frequency tuning of a dielectric elastomer membrane resonator

As a recent application of dielectric elastomers (DEs), DE resonators have become an alternative to conventional silicon-based resonators used in MEMS and have attracted much interest from the research community. However, most existing modeling works for the DE resonators ignore the intrinsic viscoelastic effect of the material that may strongly influence their dynamic performance. Based on the finite-deformation viscoelasticity theory for dielectrics, this paper theoretically examines the in-plane oscillation of a DE membrane resonator to demonstrate how the material viscoelasticity affects the actuation and frequency tuning processes of the resonator. From the simulation results, it is concluded that not only the applied voltage can change the natural frequency of the resonator, but also the inelastic deformation contributes to frequency tuning. Due to the viscoelasticity of the material, the electrical loading rate influences the actuation process of the DE resonator, while it has little effect on the final steady frequency tuned by the prescribed voltage within the safety range. With the consideration of the typical failure modes of the resonator and the evolution process of the material, the tunable frequency range and the safe range of the applied voltage of the DE membrane resonator with different dimension parameters are determined in this work, which are found to be dependent on the electrical loading rate. This work is expected to provide a better understanding on the frequency tuning of viscoelastic DE membrane resonators and a guideline for the design of DE devices.

Frequency tuned air-slot mode-gap cavities in two dimensional photonic crystals

We present frequency tuned air-slot mode-gap nanocavities in two dimensional photonic crystals by introducing elliptical air holes in the cavity region. Shape alteration from the regular circle to ellipse offers a great structural freedom to tune the optical properties of the nanocavities. By changing the ellipticity and orientation angle of the ellipse, the resonant frequency of nanocavities can be continuously tuned almost covering the entire mode gap region. It is also found that the resonant frequency is very sensitive to the shape alteration and the fine tuning of the cavity resonant frequencies can be performed. The results show that our designs can be used to construct flexible PC devices with broadband and controllable frequency tuning.

Robust Frequency-tuned Salient Region Detection

Detection of visually salient image regions has been of great research interest in recent years. It is useful for a wide range of applications such as object detection, video summarization and object segmentation. In this paper, we propose a modified method based on frequency-tuned (FT) model for salient region detection that outputs full resolution saliency maps with well-defined boundaries of salient objects. For FT model, saliency is considered as a distance to the mean spatial frequency content that is too simple for complex scenes and inconsistent with our usual sense. Our modified model, which called as Robust FT, following the assumptions of salient region, can get better saliency maps. We consider the mean spatial frequency content as background and formulate a much more robust model to descript it. By practical experiments, it is verified that our model obtains better results than original methods.

Voltage-tuned relativistic backward wave oscillator

A relativistic backward wave oscillator for the 10-GHz range with the oscillation frequency tuned within about 5% by changing the accelerating voltage from 600 to 350 kV has been developed. Discrete variations in the voltage and the corresponding frequency tuning from pulse to pulse is rapidly performed by changing the anode-cathode distance in the vacuum diode without breaking vacuum in the working volume. During this, the electron beam power remains almost constant, while the output microwave power varies within 0.4–0.8 GW. The introduction of a dielectric cylinder into the accelerating gap provides a smooth voltage drop from 600 to 350 kV with the corresponding frequency tuning during a 20-ns pulse.

Low Phase Noise, 18 kHz Frequency Tuning Step, 5 GHz, 15 bit Digitally Controlled Oscillator in 0.18 .MU.m CMOS Technology

A method to realize the fine frequency-tuning steps using tiny capacitors instead of Metal-Insulator-Metal (MIM) capacitors is proposed for a digitally controlled oscillator (DCO). The tiny capacitors are realized by the coplanar transmission lines which are arranged unsymmetrical in a 6 metal layers (M6) foundry of 0.18µm CMOS technology. These transmission line based capacitors are designed by using electro-magnetic field simulator, and co-designed by using SPICE simulator. Finally, these capacitors are employed to design 15bit DCO and fabricated the proposed DCO in 0.18µm CMOS technology, and tested. The measured phase noise of DCO was -118.3dBc/Hz (@1MHz offset frequency), and the oscillating frequency tuned from 4.86GHz to 5.36GHz in the minimum frequency-tuning step of 18kHz.