Fusing inertial sensor data in an extended kalman filter for 3D camera tracking

Due to copyright restrictions, the access to the full text of this article is only available via subscription.In a setup where camera measurements are used to estimate 3D egomotion in an extended Kalman filter (EKF) framework, it is well-known that inertial sensors (i.e., accelerometers and gyroscopes) are especially useful when the camera undergoes fast motion. Inertial sensor data can be fused at the EKF with the camera measurements in either the correction stage (as measurement inputs) or the prediction stage (as control inputs). In general, only one type of inertial sensor is employed in the EKF in the literature, or when both are employed they are both fused in the same stage. In this paper, we provide an extensive performance comparison of every possible combination of fusing accelerometer and gyroscope data as control or measurement inputs using the same data set collected at different motion speeds. In particular, we compare the performances of different approaches based on 3D pose errors, in addition to camera reprojection errors commonly found in the literature, which provides further insight into the strengths and weaknesses of different approaches. We show using both simulated and real data that it is always better to fuse both sensors in the measurement stage and that in particular, accelerometer helps more with the 3D position tracking accuracy, whereas gyroscope helps more with the 3D orientation tracking accuracy. We also propose a simulated data generation method, which is beneficial for the design and validation of tracking algorithms involving both camera and inertial measurement unit measurements in general.TÜBİTA

Multivariate sensor data analysis for oil refineries and multi-mode identification of system behavior in real-time

Large-scale oil refineries are equipped with mission-critical heavy machinery (boilers, engines, turbines, and so on) and are continuously monitored by thousands of sensors for process efficiency, environmental safety, and predictive maintenance purposes. However, sensors themselves are also prone to errors and failure. The quality of data received from these sensors should be verified before being used in system modeling. There is a need for reliable methods and systems that can provide data validation and reconciliation in real-time with high accuracy. In this paper, we develop a novel method for real-time data validation, gross error detection and classification over multivariate sensor data streams. The validated and high-quality data obtained from these processes is used for pattern analysis and modeling of industrial plants. We obtain sensor data from the power and petrochemical plants of an oil refinery and analyze them using various time-series modeling and data mining techniques that we integrate into a complex event processing engine. Next, we study the computational performance implications of the proposed methods and uncover regimes where they are sustainable over fast streams of sensor data. Finally, we detect shifts among steady-states of data, which represent systems' multiple operating modes and identify the time when a model reconstruction is required using DBSCAN clustering algorithm.Turkish Petroleum Refineries Inc. (TUPRAS) RD CenterPublisher versio

Design and implementation of dual band microstrip patch antenna for WLAN energy harvesting system

Since the demand for self-sustained wireless systems is increasing, there is a trend towards RF energy harvesting. It is a key solution to energize the low power systems such as the Internet of Things (IoT) devices without replacing the batteries periodically. This paper presents the design and analysis of RF energy harvesting system that consists of dual-band microstrip patch antenna operating at 2.4 GHz and 5.8 GHz, an impedance matching network, 4-stage voltage doubler and a storing circuit. The antenna is designed using ADS Agilent and sonnet suites software that provides a directivity of 5.5 dBi and 6.3 dBi at 2.4 GHz and 5.8 GHz respectively. The measured results of the fabricated antenna are well agreement with the simulated results. Simulated results show that for an input received power of 10 mW, the proposed system can provide 4.5 mW power at the output of 4-stage voltage rectifier with an overall efficiency of 45%.TÜBİTAKPublisher versio

COVID-19 hastalarında mitral anüler kalsifikasyonun mortalite ve miyokard hasarı ile ilişkisi

Coronavirus disease-2019 (COVID-19) can particularly affect the respiratory and cardiovascular systems and cause serious mortality. Mitral annular calcification (MAC) is a mitral valve pathology associated with cardiac mortality. We aimed to evaluate the effect of MAC on myocardial injury (MI) and mortality, which can develop secondary to COVID-19 infection. Materials and Methods After applying the exclusion criteria, thorax computed tomography (CT) images of the remaining 1151 consecutive COVID-19 patients were evaluated. Calculation of MAC scores was done by two expert radiologists blinded to the study data. MI was defined as those with hs-TnI level (≥34 ng/dl). Patients included in the study were classified as having mortality and not occurring. Results Male gender, advanced age (>65), hypertension, diabetes mellitus, chronic obstructive pulmonary disease, chronic kidney disease (CKD), coronary artery disease, heart failure and atrial fibrillation rates were statistically higher in the mortality group (p<0.05). The presence of MAC was 34.1% in the mortality group, while it was 16% in the survival group (p<0.001). MI was observed 49.3% in the mortality group, while it was 16.2% in the survival group (p<0.001). Presence of MAC was associated with MI (14.8% vs 38.7%, p<0.001). Age (OR=1.976, 95% CI 1.166-3.346, p=0.011), male gender (OR=1.784, 95% CI 1.101-2.892, p=0.019), CKD (OR=2.293, 95% CI 1.085-4.485, p=0.030), MI (OR=2.893, 95% CI 1.735-4.823, p<0.001) and advanced lung involvement on CT (OR=2.231, 95% CI 1.084-4.594, p=0.029) were the independent predictors of mortality Conclusion In terms of MI and mortality risk in COVID-19 patients, it may be recommended to evaluate MAC from the CT images.Koronavirüs hastalığı-2019 (COVID-19) özellikle solunum ve kardiyovasküler sistemleri etkileyerek mortaliteye ve ciddi morbiditelere neden olabilir. Mitral halka şeklindeki kalsifikasyon (MAC), kardiyak mortalite ile ilişkili bir mitral kapak patolojisidir. Bu çalışmada, MAC’ın COVID-19 enfeksiyonuna sekonder gelişebilen miyokard hasarı (MI) ve mortalite üzerine etkisini değerlendirmeyi amaçladık. Gereç ve Yöntemle Dışlama kriterleri uygulandıktan sonra geriye kalan 1151 ardışık COVID-19 hastasının toraks bilgisayarlı tomografi (BT) görüntüleri değerlendirildi. MAC puanlarının hesaplanması, çalışma verilerine kör olan iki uzman radyolog tarafından yapıldı. MI, hs-TnI düzeyi (≥34 ng/dl) olanlar olarak tanımlandı. Çalışmaya dahil edilen hastalar mortalitesi olan ve olmayan olarak sınıflandırıldı. Bulgular Mortalite grubunda erkek cinsiyet, ileri yaş (>65), hipertansiyon, diabetes mellitus, kronik obstrüktif akciğer hastalığı, kronik böbrek hastalığı (KKD), koroner arter hastalığı, kalp yetmezliği ve atriyal fibrilasyon oranları istatistiksel olarak daha yüksekti (p<0.05). Mortalite grubunda MAC varlığı %34.1, sağkalım grubunda ise %16 idi (p<0.001). Miyokardiyal hasar mortalite grubunda %49.3, sağkalım grubunda ise %16.2 olarak saptandı (p<0.001). MAC varlığı MI ile ilişkiliydi (%14.8’e karşılık %38.7, p<0.001).Yaş (OR=1.976, 95% CI 1.166-3.346, p=0.011), erkek cinsiyet (OR=1.784, 95% CI 1.101-2.892, p=0.019), kronik böbrek yetersizliği (OR=2.293, 95% CI 1.085-4.485, p=0.030), MI (OR=2.893, 95% CI 1.735-4.823, p<0.001) ve küçük hücreli akciğer tutulumu (OR=2.231, 95% CI 1.084-4.594, p=0.029) mortalitenin bağımsız belirleyicileri idi. Sonuç COVID-19 hastalarında MI ve mortalite riski açısından BT görüntülerinden MAC değerlendirilmesi önerilebilir

New CagL amino acid polymorphism patterns of helicobacter pylori in peptic ulcer and non-ulcer dyspepsia

Background and Objectives: Helicobacter pylori infection is associated with chronic gastritis, ulcers, and gastric cancer. The H. pylori Type 4 secretion system (T4SS) translocates the CagA protein into host cells and plays an essential role in initiating gastric carcinogenesis. The CagL protein is a component of the T4SS. CagL amino acid polymorphisms are correlated with clinical outcomes. We aimed to study the association between CagL amino acid polymorphisms and peptic ulcer disease (PUD) and non-ulcer dyspepsia (NUD). Materials and Methods: A total of 99 patients (PUD, 46; NUD, 53) were enrolled and screened for H. pylori by qPCR from antrum biopsy samples. The amino acid polymorphisms of CagL were analyzed using DNA sequencing, followed by the MAFFT sequence alignment program to match the amino acid sequences. Results: Antrum biopsy samples from 70 out of 99 (70.7%) patients were found to be H. pylori DNA-positive. A positive band for cagL was detected in 42 out of 70 samples (PUD, 23; NUD, 19), and following this, these 42 samples were sequenced. In total, 27 different polymorphisms were determined. We determined three CagL amino acid polymorphism combinations, which were determined to be associated with PUD and NUD. Pattern 1 (K35/N122/V134/T175/R194/E210) was only detected in PUD patient samples and was related to a 1.35-fold risk (p = 0.02). Patterns 2 (V41/I134) and 3 (V41/K122/A171/I174) were found only in NUD patient samples and were linked to a 1.26-fold increased risk (p = 0.03). Conclusions: We observed three new patterns associated with PUD and NUD. Pattern 1 is related to PUD, and the other two patterns (Patterns 2 and 3) are related to NUD. The patterns that we identified include the remote polymorphisms of the CagL protein, which is a new approach. These patterns may help to understand the course of H. pylori infection.Istanbul Aydin University Scientific Research Projects Uni

Analysis of asynchronous cognitive radio system with imperfect sensing and bursty primary user traffic

Due to copyright restrictions, the access to the full text of this article is only available via subscription.This paper presents a theoretical analysis of the spectrum utilization levels in a cognitive radio system. We assume that the traffic of the primary network is bursty and asynchronous with the secondary network, which performs imperfect spectrum sensing. Collisions of the primary and the secondary packets are assumed to result in increased packet error probabilities. We present primary and secondary utilization levels under optimized secondary transmission periods for varying primary traffic characteristics and secondary sensing performance levels. The results are also validated by extensive Monte Carlo simulations. We find that an asynchronous cognitive radio network with imperfect spectrum sensing is feasible when optimized transmission periods are used. The effects of primary traffic’s burst pattern and secondary sensing performance are discussed.European Commission ; TÜBİTA

On sensor fusion for head tracking in augmented reality applications

Due to copyright restrictions, the access to the full text of this article is only available via subscription.The paper presents a simple setup consisting of a camera and an accelerometer located on a head mounted display, and investigates the performance of head tracking for augmented reality applications using this setup. The information from the visual and inertial sensors is fused in an extended Kalman filter (EKF) tracker. The performance of treating accelerometer measurements as control inputs is compared to treating both camera and accelerometer measurements as measurements, i.e., fusing them in the measurement update stage of the EKF simultaneously. It is concluded via simulations that treating accelerometer measurements as control inputs performs practically as good as treating both measurements as measurements, while providing a lower complexity tracker.TÜBİTA

Bispectrum estimation using a MISO autoregressive model

Due to copyright restrictions, the access to the full text of this article is only available via subscription.Bispectra are third-order statistics that have been used extensively in analyzing nonlinear and non-Gaussian data. Bispectrum of a process can be computed as the Fourier transform of its bicumulant sequence. It is in general hard to obtain reliable bicumulant samples at high lags since they suffer from large estimation variance. This paper proposes a novel approach for estimating bispectrum from a small set of given low lag bicumulant samples. The proposed approach employs an underlying MISO system composed of stable and causal autoregressive components. We provide an algorithm to compute the parameters of such a system from the given bicumulant samples. Experimental results show that our approach is capable of representing non-polynomial spectra with a stable underlying system model, which results in better bispectrum estimation than the leading algorithm in the literature

Energy sensing strategy optimization for opportunistic spectrum access

Due to copyright restrictions, the access to the full text of this article is only available via subscription.This paper introduces a correlator-based energy sensing strategy for opportunistic spectrum access in a slow, flat-fading channel. The correlator provides weighted energy accumulation in time. We assume that the noise variance is known and the primary user (PU) traffic follows a two state Markov chain with known idle and busy rates. Using Chebyshev bounds on missed detection and false alarm probabilities, we find that the optimal weighting function is an increasing function of time and its shape is dependent on the PU traffic characteristics and SNR. We show that the traditional flat-integration based energy collection method is suboptimal both in the error probability and channel utilization sense.European Commission ; Argela Technologies ; Türk Teleko