Practical Fss-Based Sensor Sensitivity

Frequency selective surfaces are a periodic array of unit cells that, when illuminated externally, have a specific frequency response that depends on element geometry, spacing, and substrate properties. Theoretically, FSS is assumed as an infinite array of unit cells with a plane wave excitation. However, in practice, an FSS is finite and hence, due to edge effects, the limited number of unit cells, and non-uniform illumination, the response will deviate from the theoretical. As it relates to FSS-based sensing in particular, a localized illumination is often used in order to improve the sensing resolution. However, due to the aforementioned factors, the sensitivity of the sensor may suffer as a result. Hence, the effect of these factors is studied on the FSS sensor response. Then, taking strain measurement as an example, the degradation in the sensor sensitivity to strain is evaluated in comparison with that of a theoretical FSS. The simulation results show that a finite FSS with non-uniform illumination has reduced sensitivity to strain. This degradation in sensitivity of reduces as the number of illuminated unit cells increases. However, the sensitivity of a finite FSS with uniform illumination is nearly constant with respect to the number of illuminated unit cells

Two-Dimensional In-Plane Strain Fss-Based Sensor

Frequency selective surface (FSS) based sensors have found application as sensors in the last decade. In this paper, a new sensor design is proposed for two-dimensional in-plane strain sensing. The unit cell of the FSS-based sensor includes two slot dipoles, oriented normal to one another and each with different dimensions, to create two unique resonant frequencies when interrogated with an incident electric field normal to the direction of measured strain. In this way, 2D strain can be characterized concurrently and independently. The error due to strain orthogonal to the direction of interest, along with the error due to the presence of shear strain, has also been characterized. The sensor has a maximum of 12% error for an applied strain due to 4% strain orthogonal to the measurement direction, and no more than 8% error for a maximum of 4% of shear strain

Impact of educational on dietary behavior self- efficacy of middle school student in Kerman city in the year of 2010.

Background: Nutrition is the most significant factor affecting the health statue of individuals and their longevity.In this respect , children and adolescents are more dependent to a healthy nutrition in order to have adequate physical growth and mental development and to be able to prevent chronic diseases in future. Therefore , encouraging this age groups for following healthy nutritional behavior should be considered as one of the health priorities of community. Objectives: The purpose of this study to determine effect of educational on dietary behavior self-efficacy middle school student in Kerman/Iran. Materials and Methods: In this experimental study from all private and public secondary schools of Kerman, 120 students were selected through multi- stage cluster random sampling and were randomly divided into two groups of experimental and control. Data were gathered by using a questionnaire. After performing a pre-test, eight 60-minute sessions of educational program on healthy nutrition and it’s importance in experimental group were hold by the researcher through giving lecture and providing question and answer time and educational booklet. Post-test was performed after three weeks in experimental group and control group and the results of pre- and post-tests were compared by using paired t-test, Chi-square, Fisher and independent t-test. Results: According to the results, self-efficacy in all domains of nutritional behavior showed a significant difference (p=%001) in experimental group (38.92±10.59) compared to the control group (-1.78 ± 0.33). The two groups showed significant difference in regard to the promotion of dietary behavior self- efficacy following the educational program (p=%001). Conclusion: Educational programs have positive effects on students’ dietary behaviors self-efficacy. Therefore,providing such educational programs for promotion of self-efficacy in various health issues and prevention is highly required. Keywords: Self-efficacy, Education, Nutritional behaviors, students

Frequency selective surface-based sensing: Theory and applications

Frequency selective surfaces (FSS) are periodic arrays of resonant elements with a specific (resonant) reflection/transmission response when illuminated by electromagnetic energy. FSSs have been utilized for different applications such as spatial filters, reflectors, lenses, radomes, and more recently, as sensors. FSS-based sensors have shown potential for numerous applications in structural health monitoring such as crack detection, concurrent strain and temperature sensing, normal and shear strain sensing, inspection of layered structures, etc. As FSS-based sensing is largely undeveloped, there are many critical aspects that must be fully understood before this sensing approach can be fully utilized. Therefore, the goal of this research is to advance the science behind FSS-based sensing in order to create a platform of knowledge upon which future engineers may utilize when designing FSS-based sensors. To this end, the theoretical (assuming infinite dimensions and a uniform excitation) FSS response is modeled using a cavity-based coupled-mode theory and subsequent quality factor analysis for patch and loop unit cells in order to study the effect of unit cell dimension, element geometry and substrate properties on the FSS frequency response. In addition, the differences between theoretical and practical FSSs are studied in order to obtain design rules and metrics to achieve a reliable (localized) sensing measurement by an FSS sensor, thereby improving the sensing resolution (from the dimensions of the sensor to smaller \u27cells\u27 within the sensor). Then, to achieve the maximum resolution of the FSS sensor, an approach is presented to determine the optimal sensor cell size. Additionally, a method using synthetic beamforming is presented to obtain an adaptive resolution for FSS sensing --Abstract, page iv

Effect of Illumination Pattern on FSS-Based Sensor Resolution

Frequency selective surfaces (FSSs) are periodic arrays of conductive elements, and when illuminated by electromagnetic energy, have a specific transmissive or reflective response. FSS-based sensing is a relatively new application of FSSs, and recently these sensors have shown promise for crack detection, strain and temperature sensing, amongst others. Generally speaking, when an FSS sensor is illuminated in its entirety, the response of the sensor is related to the entire FSS landscape. In this way, the resolution of the sensor is equal to the FSS dimensions. However, this is limiting as it relates to localized sensing. As such, to improve the achievable resolution, the FSS sensor must be illuminated locally in order for the detected response to be related to a specific region of the sensor. In this way, an FSS sensor can be considered as consisting of many sensor cells which are illuminated individually. To this end, in this paper, the effect of illumination pattern and cell dimensions are studied as it relates to the FSS sensor resolution. For this work, a grounded loop FSS was designed to operate at X-band (8.2-12.4 GHz). Five different FSS dimensions were considered for simulation, with three of these fabricated for measurement. From this, the achievable resolution for a given sensor design and illumination pattern is quantified. Additionally, the performance of these sensors is compared to that of the ideal FSS (infinite dimensions and uniform illumination). The results show that optimum sensor cell size (for a given FSS design and illumination pattern) is determined based on when the FSS response (resonant frequency and Q-factor) is constant (with respect to increasing cell size). In addition, as the cell size is directly related to the illumination footprint, the optimum cell size can be adjusted per sensing applications needs based on the illumination source and distance from the FSS

Design of a New Bi-State Active Frequency Selective Surface

This paper presents a bi-state frequency selective surface (FSS) designed using a passive and active FSS on both side of a thin dielectric substrate. Specifically, the proposed unit cell (of the bi-state FSS) includes a passive loaded cross dipole FSS on one side and an active dipole (utilizing PIN diodes) with perpendicular bias lines on the opposite side. The proposed bistate FSS is capable of functioning in reflection mode when the active FSS is reverse biased, and in transmission mode when forward biased. The proposed design also features reduced electrical size, thereby reducing the sensitivity of this design to incident angle of the interrogating electric field

Improvement in FSS-Based Sensor Sensitivity by Miniaturization Technique

Frequency selective surfaces are a planar array of elements (or unit cells) that, when illuminated externally, have a frequency response that depends on element geometry and spacing, and the dielectric properties and thickness of the substrate. Thus, FSSs are good candidates for wireless sensing for numerous nondestructive testing applications. As sensitivity is an important sensing issue, detection sensitivity of FSS-based sensors can be improved by increasing the number of unit cells within a given (physical) space. This is a result of the fact that more unit cells will contribute to the frequency response within a given physical area (i.e., the illuminating footprint upon the sensor) in addition to smaller inter-element spacing (e.g., higher mutual coupling). Both of these aspects increase the sensitivity of the sensor to geometrical changes, and can be physically realized through implementation of FSS miniaturization techniques. To this end, in this work, two FSS-based sensors have been designed; one of which is the miniaturized version of the other. Measurement results indicate that the miniaturized FSS sensor is more sensitive to geometrical variations