Signal processing methods for defect detection in multi-wire helical waveguides using ultrasonic guided waves

This thesis was submitted for the degree of Master of Philosophy and awarded by Brunel University LondonNon-Destructive Testing of industrial components carries vital importance, both financially and safety-wise. Among all Non-Destructive techniques, Long Range Ultrasonic Testing utilizing the guided wave phenomena is a young technology proven to be commercially valid. Owing to its well-documented analytical models, Ultrasonic Guided Waves has been successfully applied to cylindrical and plate-like structures. Its applications to complex structures such as multi-wire cables are fairly immature, mainly due to the high complexity of wave propagation. Research performed by the author approaches the long range inspection of overhead transmission line cables using ultrasonic guided waves. Existing studies focusing on guided wave application on power cables are extremely limited in inspection range, which dramatically degrades its chances of commercialization. This thesis consists of three main chapters, all of which approaches different problems associated with the inspection of power cables. In the first chapter, a thorough analysis of wave propagation in ACSR (most widely used power cable) cables is conducted. It is shown that high frequency guided waves, by concentrating the energy on the surface layers, can travel much further in the form of fundamental longitudinal wave mode, than previous studies have shown. Defect detection studies proved the system’s capability of detecting defects which introduce either increase or decrease in cross sectional area of the cable. Results of the chapter indicate the detectability of defects as small as 4.5% of the cross sectional area through a 26.5 meter long cable without any post-processing. In the second chapter, several algorithms are proposed to increase the inspection range and signal quality. Well-documented wavelet-denoising algorithm is optimized for power cables and up to 24% signal-to-noise ratio improvement is achieved. By introducing an attenuation correction framework, a theoretical inspection range of 75 meters is presented. A new framework combining dispersion compensation and attenuation correction is proposed and verified, which shows an inspection range of 130 meters and SNR improvement up to 8 dBs. Last chapter addresses the accurate localization of structural defects. Having proven the optimum excitation and related wave propagation in ACSR cables, a system having a more complex wave propagation characteristics is studied. A new algorithm combining pulse compression using Maximal Length Sequences and dispersion compensation is applied to multi-modal signals obtained from a solid aluminum rod. The algorithm proved to be able to improve signal quality and extract an accurate location for defects. Maximal Length Sequences are compared to chirp signals in terms of SNR improvement and localization, which produced favourable results for MLS in terms of localization and for chirp in terms of SNR improvement

Towards trajectory anonymization: a generalization-based approach

Trajectory datasets are becoming popular due to the massive usage of GPS and locationbased services. In this paper, we address privacy issues regarding the identification of individuals in static trajectory datasets. We first adopt the notion of k-anonymity to trajectories and propose a novel generalization-based approach for anonymization of trajectories. We further show that releasing anonymized trajectories may still have some privacy leaks. Therefore we propose a randomization based reconstruction algorithm for releasing anonymized trajectory data and also present how the underlying techniques can be adapted to other anonymity standards. The experimental results on real and synthetic trajectory datasets show the effectiveness of the proposed techniques

HybridAugment++: Unified Frequency Spectra Perturbations for Model Robustness

Convolutional Neural Networks (CNN) are known to exhibit poor generalization performance under distribution shifts. Their generalization have been studied extensively, and one line of work approaches the problem from a frequency-centric perspective. These studies highlight the fact that humans and CNNs might focus on different frequency components of an image. First, inspired by these observations, we propose a simple yet effective data augmentation method HybridAugment that reduces the reliance of CNNs on high-frequency components, and thus improves their robustness while keeping their clean accuracy high. Second, we propose HybridAugment++, which is a hierarchical augmentation method that attempts to unify various frequency-spectrum augmentations. HybridAugment++ builds on HybridAugment, and also reduces the reliance of CNNs on the amplitude component of images, and promotes phase information instead. This unification results in competitive to or better than state-of-the-art results on clean accuracy (CIFAR-10/100 and ImageNet), corruption benchmarks (ImageNet-C, CIFAR-10-C and CIFAR-100-C), adversarial robustness on CIFAR-10 and out-of-distribution detection on various datasets. HybridAugment and HybridAugment++ are implemented in a few lines of code, does not require extra data, ensemble models or additional networks.Comment: Accepted to ICCV 202

Improving the Productivity and Energy Efficiency by a Heat Treatment Method Applied to Aluminum Forged Parts

In industrial applications, hot forging of AA6082 alloy is carried at 480°C. After the hot forging operation parts are cooled down to room temperature and heated again up to 540°C for solution heat treatment and artificially aged. Heating-cooling-heating cycles leads to energy and time loss in production, and have long-termenvironmental and economic impacts. Mass production of aluminum parts for applications in various industries (automotive, aerospace etc.) requires a process with higher productivity. The aim of this study was to provide time and energy efficiency by combining hot forging and solution treatment processes into a single operation. AA6082 billets were forged at 540°C for 7.5, 15 and 30 minutes in order to achieve simultaneous solution treatment. Billets were then water quenched and artificially aged. Mechanical properties (hardness, tensile strength) as well as microstructure of samples were investigated. Required mechanical properties were achieved on the samples forged and treated at 540°C for 15 and 30 minutes

Displacement of the South Pole from 2006 to 2021: Role of sea ice and Antarctic surface temperature

The effect of global warming on the southern polar regions necessitates careful monitoring of glacier deformations and their movements, as well as an understanding of atmospheric physics. For this purpose, the yearly movements of UNAVCO stations-South Pole Station (AMU2) (winter-summer) and other stations in the South Pole region have been observed in this paper for about a fifteen-year period (2006–2021). In addition, the area differences of the Antarctic continent due to seasonal changes (winter-summer) between 1980 and 2021 were investigated in this study. Moreover, the height values of the stations on the Antarctic continent were observed seasonally. The subglacial lakes in the Antarctic continent cause the differences in the height values as a result of the seasonal changes. A decrease in sea ice of 0.91 million km2 for the winter season and 0.55 million km2 for the summer season during a 41-year period has been determined for four sectors of the Antarctic continent. The temperature changes on the Antarctic continent in the summer and winter seasons (2005–2022) were also evaluated in this paper. Air temperature increases was apparent especially in the Antarctic Peninsula, East Antarctic and West Antarctic coasts. The Weddell Sea and the Amundsen Sea regions have had the most sea ice loss, each with 1.24 million km2. On the other hand, it can be observed that the East Antarctic sector has expanded by 0.32 million km2

Optimization of a spectrofluorimetric method based on a central composite design for the determination of potassium losartan in pharmaceutical products

Here, a spectrofluorimetric method for the determination of potassium losartan (PL) in pharmaceutical products is described. The effects of critical parameters, pH, acid molarity, and temperature, on the fluorescence intensity of PL were analyzed, and these parameters were optimized using a central composite design (CCD). The highest fluorescent intensity at excitation (λex) and emission (λem) wavelengths of 248 nm and 410 nm, respectively, was achieved using 0.01 M sulfurous acid (pH 2) at 21.6 °C. Under optimum conditions, the method was linear from 0.025-0.5 µg/mL, with a reasonably high correlation coefficient (0.9993). Furthermore, the method was very sensitive (LOQ, 0.006), accurate (RE, ≤7.06), and precise (%RSD, ≤6.51). After development and validation of the method, samples containing PL were analyzed with this method, and the obtained data were statistically compared with those obtained with a previously published reference method using a two one-sided equivalence test (TOST). According to the data, the results from the proposed and reference assays were equivalent.Descreve-se método espectrofluorométrico para a determinação de losartana potássica (PL) em produtos farmacêuticos. Os efeitos de parâmetros críticos (pH, molaridade ácida e temperatura) na intensidade da fluorecência foram otimizados usando o planejamento de componente central (DCC). A mais alta intensidade fluorescente com λex=248 nm e λem= 410 nm foi obtida usando ácido sulfúrico 0.01 M (pH 2) e 21.6 ºC. Nas condições ideais, a linearidade do método foi estabelecida na faixa de concentração de 0.025-0.5 µg/mL com coeficiente de correlação bastante elevado (0.9993). Além disso, o método foi muito sensível com valor de LOQ 0.006, exato (RE≤7.06) e preciso (RSD%≤6.51). Depois do desenvolvimento e validação do método, amostras de medicamentos contendo PL foram analisadas com este método e os resultados obtidos foram comparados estatisticamente com método de referência, publicado anteriormente, usando o Teste de equivalência TOST (Teste de Equivalência Unilateral). De acordo com os dados estatísticos, os resultados do ensaio de referência e do método proposto foram equivalentes

Comparison of depression, anxiety and long-term quality of health in patients with a history of either primary closure or Limberg flap reconstruction for pilonidal sinus

OBJECTİVE: Pilonidal sinus is characterized by high operative morbidity mainly due to wound problems. We aimed to compare the quality of health, comfort and psychological status in patients who underwent surgery for pilonidal sinus. METHODS: A total of 205 pilonidal sinus patients operated on with either primary closure or Limberg flap reconstruction were compared in terms of depression, anxiety, and long-term quality of health by using Short Form 36, Beck Depression Inventory, and Beck Anxiety Inventory scales. RESULTS: There were 107 patients in the primary closure group with a mean follow-up of 29.6±7.7 months and 98 patients in the Limberg flap group with a mean follow-up of 34.1±7.3 months. In the SF-36 analysis, the mental health and bodily pain scores (59±6 and 56±11 in the primary closure group and 62±8 and 61±10 in the Limberg flap group) were significantly higher in the Limberg flap group (p = 0.014 and p = 0.002, respectively). The mean Beck Depression Inventory (19±6.13 vs. 16±4.90

The impact of metabolic risk management on recurrence of urinary stones

Introduction: Urinary stone disease is a common urologic problem and recurrence in stone formation is a very familiar issue to urologists. Although recurrence in stone formation has been linked to metabolic abnormalities, it can be accessible by metabolic risk analysis studies.Methods: Herein, we present our experience in metabolic risk management on recurrence of urinary stones for 10 years in Akdeniz University School of Medicine department of Urology. We retrospectively analyzed Akdeniz University Urinary Stone Database between dates of January 2000 and December 2010. We found over 3500 patients who were managed by SWL (shock wave lithotripsy) or PCNL (percutaneus nephrolithotripsy) or URS (Ureterorenoscopic lithotripsy) or open surgery.Results: 525 patients’ metabolic risk analysis was ordered due to recurrent urinary stone disease. Only 134 (25.5 %) current metabolic analysis were returned. Mean patient age was 32.2 years (range: 19-82 years).Patients were 103 male and 31 female. Stone analysis results were CaOx monohydrate in 48 (35.8 %), CaOx dihydrate in 8 (5.9 %), CaOx mono and dihydrate in 70 (52.2 %), uric acid in 3, CaOx monohydrate and uricacid in 2, cystine in 2, and struvite in 1 patient, respectively. The  metabolic risk analysis showed some abnormality in 54 (40.2 %) patients.Conclusion: Although compliance to metabolic risk analysis studies is low among recurrent urinary stone formers, some significant metabolic abnormalities could be detected in those who are effectively screened.Recurrence of urinary stones in patients who are started on appropriate metabolic management can be prevented