Biologically Inspired Sensing and MIMO Radar Array Processing

The contributions of this dissertation are in the fields of biologically inspired sensing and multi-input multi-output: MIMO) radar array processing. In our research on biologically inspired sensing, we focus on the mechanically coupled ears of the female Ormia ochracea. Despite the small distance between its ears, the Ormia has a remarkable localization ability. We statistically analyze the localization accuracy of the Ormia\u27s coupled ears, and illustrate the improvement in the localization performance due to the mechanical coupling. Inspired by the Ormia\u27s ears, we analytically design coupled small-sized antenna arrays with high localization accuracy and radiation performance. Such arrays are essential for sensing systems in military and civil applications, which are confined to small spaces. We quantitatively demonstrate the improvement in the antenna array\u27s radiation and localization performance due to the biologically inspired coupling. On MIMO radar, we first propose a statistical target detection method in the presence of realistic clutter. We use a compound-Gaussian distribution to model the heavy tailed characteristics of sea and foliage clutter. We show that MIMO radars are useful to discriminate a target from clutter using the spatial diversity of the illuminated area, and hence MIMO radar outperforms conventional phased-array radar in terms of target-detection capability. Next, we develop a robust target detector for MIMO radar in the presence of a phase synchronization mismatch between transmitter and receiver pairs. Such mismatch often occurs due to imperfect knowledge of the locations as well as local oscillator characteristics of the antennas, but this fact has been ignored by most researchers. Considering such errors, we demonstrate the degradation in detection performance. Finally, we analyze the sensitivity of MIMO radar target detection to changes in the cross-correlation levels: CCLs) of the received signals. Prior research about MIMO radar assumes orthogonality among the received signals for all delay and Doppler pairs. However, due to the use of antennas which are widely separated in space, it is impossible to maintain this orthogonality in practice. We develop a target-detection method considering the non-orthogonality of the received data. In contrast to the common assumption, we observe that the effect of non-orthogonality is significant on detection performance

Integrating cluster analysis with MCDM methods for the evaluation of local agricultural production

This study aims to cluster Turkish cities based on their local agricultural production and rank them in terms of performance by combining cluster analysis and multi-criteria decision-making (MCDM) methods. In this context, a three-phase methodology is developed. In the first phase, Ward\u27s method is utilized to cluster cities according to agricultural production characteristics. In the second phase, the objective criteria weights are determined using the Criteria Importance Through Intercriteria Correlation technique (CRITIC). In the third phase, to rank the clusters in terms of performance, the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) method is applied. Due to the results, the 81 cities are divided into six clusters in terms of agricultural production features. The cluster with the highest performance is Cluster 6, in which Konya is alone. Cluster 4, which includes Antalya and Mersin, follows this cluster. Cluster 1 with 25 cities and Cluster 2 with 19 cities are the clusters with the lowest results. The results show that only a few cities such as Konya, Antalya, and Mersin are generating more than tens of them in combination. These findings reveal that local governments should reconsider their agricultural programs and develop new strategies under the direction of the central government

A Comparison of Risk Exposure in Aquaculture and Agricultural Businesses

Agriculture and aquaculture have common features associated with their biological nature affecting risk exposure of the businesses. The aim of this paper is to compare risk exposure in salmon farming and agricultural enterprises in Norway by using an implicit error component model to examine the risk structure of yields, prices and economic returns at the farm level. Results indicate a higher farm-level year-to-year variability in yields, prices and economic returns in salmon farming than in agricultural enterprises. The variability in livestock enterprises was generally lower than for crop enterprises. Return on assets was highest in salmon farming with an average annual return of 9.2%. All of the agricultural farm types exhibited a negative average return on assets on average. Stochastic dominance tests of the distribution of economic returns from aquaculture and agricultural farm types showed salmon farming to be the most risk efficient alternative and salmon farming was most attractive from an investor’s perspective.Risk analysis, variability, Norway, Risk and Uncertainty,

Thermoelastic impact damage on glass

Etched, as-received and abraded float glass, and etched low-expansion borosilicate glass were impacted at a velocity of 5.62 m/s by a spherical steel impactor of 10.3 mm diameter. The temperature of the glass specimens and that of the impactor were varied, and the effect of thermal shock on the resulting impact damage was investigated. The number, density and the radial spread of inner ring cracks that formed inside the primary ring crack, and the probability of cone crack formation were observed to increase significantly with increasing temperature difference between the impacting bodies, and with the abrasion of the glass surfaces prior to impact. Impacts on soda-lime-silica float glass at specimen temperatures of 700 and 750 °C revealed inner ring cracks without cone cracks, suggesting that significant strength degradation may result in glasses under these impact conditions. Borosilicate glass was found to be much more resistant to inner ring crack formation than soda-lime-silica glass

Patient Perceptions of Comorbid Depression in Heart Disease

Depression is a risk factor for the development of heart disease, as well as for poor prognosis among patients with existing disease. However, clinical trials of treatment of depression in patients with heart disease have not resulted in improved cardiac outcomes, and have demonstrated modest effects on depression. The nature of depression in heart patients must be better understood in order to improve treatment and health outcomes. In samples of patients with medical illness as well as in patients with depression, illness perceptions have been useful in predicting both treatment outcomes and self-management behaviors such as coping and adherence. This is the first study to examine patient perceptions of comorbid depression in heart disease. The purpose of the study was to identify baseline correlates of illness perceptions in the context of a depression treatment study. Results from 112 patients with comorbid depression and heart disease, manifested as stable coronary heart disease or heart failure, show that depression is strongly associated with perceived consequences, but that personality factors are more strongly related to several other illness perception dimensions. Depression history variables did not predict illness perceptions, but moderated the effect of personality on timeline perceptions. Relationships among dimensions of illness perceptions were somewhat consistent with findings from other study populations. This study represents an important first step in clarifying how patients with heart disease conceptualize comorbid depression. Future research is needed to determine if these perceptions predict coping with depression, adherence to treatment, or treatment outcomes

The effects of leptin on F-actin remodelling in type 1 diabetes

Background: The aim of the current study is to investigate the effect of leptin on cytoskeleton structures in both in vivo and in vitro model of diabetes. Materials and methods: For in vivo studies, leptin in different doses (240, and 480 mg/kg) was injected to the diabetic rats after 1-week of streptozotocin (STZ, 55 mg/kg) treatment. Leptin levels were analysed in serum, liver, and pancreas samples. Hepatic and pancreatic F- and G-actin expressions were determined by Western blotting. For in vitro studies, hepatic and pancreatic primary cell lines were obtained from the control rats. To these cultures, STZ (15 and 30 mM), leptin (50, 60 and 100 ng/mL), and their combinations were applied for 1, 3, and 4 weeks. After the treatment period, F-actin was visualised by the Alexa-fluor fluorescent dye.  Results: Streptozotocin decreased the G-actin in both tissues in vivo. However, leptin caused a dose-dependent increase in G-actin levels while F-actin decreased in both tissues. Moreover, leptin caused the perimembranous condensation of actin filaments and amelioration of F-actin structures in vivo. A dose-dependent corruption of F-actin filament structures was observed in leptin-treated primary cells in vitro, while STZ also caused corruption of these filaments. Co-exposure of STZ and leptin caused the amelioration of F-actin filaments, while the peri- membranous condensation was also observed as was in vivo study.  Conclusions: Leptin therapy could be a candidate for diabetes, but it should not be ruled out as being important the severity of diabetes and leptin doses.