Gravity Study using Multi-2.5D Modeling and 3D Presentation for Al Ma'aniyah Depression, Southwest of Iraq

Tectonic depression area within and/or beside widespread basin is regarded as an important location for sub-basin sedimentary sequence of Iraq which may represent an excellent accumulation of bounded sediments. Al-Ma'aniyah depression, southwest Iraq is one of such type of sub-basin. Free-air gravity data show a NS extend of this depression inside Saudi Arabia. This work focuses on studying and multi-2.5D model creation for the depression in the Iraqi territory part using Bouguer gravity data and mapping its basement relief. Firstly, the exact boundary of the depression was outlined utilizing the Free-Air gravity data. Then, a precise selection of regional field for the study area was determined by using the power spectrum method, which accordingly defines the residual anomalies that could represent structural enclosures. Many positive anomalies were assigned and enhanced using vertical and total horizontal derivatives, where they were interpreted as basement-related features. Subsequently, a 2.5D multi modeling and depth inversion for the Bouguer gravity data were accomplished by converting the gravity map to a stacked profiles depth map. A nineteen gravity profiles, which cover the study area, were modeled by assuming 2D intra-sedimentary bodies. These bodies were best presented by a 3D view that clarifies the nature of the subsurface modeled structures. The modeling shows an extra density at the northern part of the depression, in contrast, it suggests low density bodies at its southern part, the case that appears inconsistent with a previously performed magnetic interpretation. The inversion of gravity data shows that the basement depth at Al-Ma'aniyah depression ranges from 7.5 to10 km.

Efektifitas Penggunaan Sistem AEC (Smart mA) untuk Optimisasi Dosis dan Kualitas Citra pada Protokol CT Abdomen

This study aims to analyze Automatic Exposure Control (AEC) with Smart mA software on water phantom image quality and CTDIvol dose. The researched image quality is CT Number and noise. In addition, the CT Number is evaluated for accuracy, uniformity, and noise using the Noise Power Spectrum method. The results of image measurements with and without Smart mA on CT Number accuracy are still in the Standard range of ± 4 CT, the uniformity value of CT Number and noise is also still within the Standard, namely ± 2 CT. The use of Smart mA increases the noise value by 14.29%. The noise value from the noise power spectrum analysis when using Smart mA is higher than without using Smart mA. Meanwhile, the CTDIvol radiation dose from using Smart mA decreases by 52.33%. Image quality using Smart mA has a CT Number value almost the same or uniform with the test object, namely water phantom, so that the use of Smart mA can characterize body tissues well, but the noise value generated is more significant than without using Smart mA. Although the noise value generated by Smart mA is more excellent, visually, the noise value does not disturb the radiologist too much in determining the diagnosis because the image quality is still in good condition so that it can give a dose according to the patient's body thickness according to the ALARA principle. Keywords: CT Number, CTDIvol, AEC, NPS.

Depth Determınatıon From Gravıty Data Usıng Radıal Amplıtude Spectrum: The Dikili (İzmir) Geothermal Area

The Dikili geothermal area, in the northern part of Izmir province, is one of the best known geothermal areas in Western Anatolia. This study attempts to analyze and interpret Bouguer gravity data to determine average structural depth values and assess geothermal resources using the Radial Amplitude Spectrum Method (RASM), based on 2D Fast Fourier Transform (FFT) analysis. We selected four different areas to apply the method. The greatest advantage of this method over the conventional power spectrum method is that it can determine the mean depth from 2D FFT spectra, not using a single cross-section taken in one direction. Thus, the user can select an area rather than a direction and average depth can be determined more accurately. The results show that average depth values of the top of the reservoir vary between 314 and 640 m in the region.

Removing the giants and learning from the crowd: A new SZ power spectrum method and revised Compton y-map analysis

The Sunyaev-Zeldovich (SZ) effect provides a powerful cosmological probe, which traditionally is approached independently as cluster number count (CNC) or power spectrum (PS) analysis. Here, we devise a new method for analysing the y-map by introducing the survey completeness function, conventionally only used in the CNC analysis, in the yy-PS modeling. This provides a systematic method, based mainly on SZ observables, for obtaining two complementary y-maps, one incorporating detected/resolved clusters and the other relying only on diffuse/unresolved SZ contributions. We use the catalogue of clusters obtained in the Planck CNC analysis to define the completeness function linking these two y-maps. The split depends on the chosen signal-to-noise detection threshold, which we vary in our discussion. We carefully propagate the effect of completeness cuts on the non-Gaussian error contributions in the yy-PS analysis, highlighting the benefits of masking massive clusters. Our analysis of the Planck yy-PS for the unresolved component yields a mass bias of b = 0.15 ± 0.04, consistent with the standard value (b ≈ 0.2), in comparison to b = 0.4 ± 0.05 for the total yy-PS. We find indications for this drift being driven by the CIB-tSZ cross correlation, which dominantly originates from clusters in the resolved component of the y-map. Another possible explanation is the presence of a mass-dependent bias, which has been theoretically motivated and can be quantified with our novel method. We furthermore find first hints for the presence of the 2-halo terms in the yy-PS. Finally, the proposed method provides a new framework for combining the complementary information of the CNC and PS analyses in upcoming SZ surveys.

Analysis of gravity disturbance for boundary structures in the Aegean Sea and Western Anatolia

Western Anatolia has been shaped N–S-trending extensional tectonic regime and W-E trending horst, grabens and active faults due to the collision of Africa, Arabian and Eurasia plates. The borders of the Aegean Sea tectonic is limited between eastern of Greece, western of Anatolia and Hellenic subduction zone in the south of Crete. To evaluate these tectonic elements gravity disturbance data of the Aegean Sea and Western Anatolia was used in this study. It is thought that the gravity disturbance data reflects the tectonic elements and discontinuities way better than gravity anomaly due to the calculation from the difference between gravity and normal gravity at the same point so thus the tensors and invariants of the study area were calculated and the power spectrum method was applied to the gravity disturbance data. Various boundary analysis methods were applied to the gravity disturbance data to compare the discontinuities obtained from the tensors both theoretical and case study. These methods were tested initially on theoretical data. Within the scope of the theoretical study, a single model and three bodies model were taken into consideration. When the results are examined, it is observed that the Tzz tensor component gives very clear information about the location of the structure. Likewise, when the Txx, Tyy components and invariant results are examined, the vertical and horizontal boundaries were successfully obtained. In addition, the mean depths of these structures were determined using the power spectrum method. In the case application stage, the gravity disturbance data obtained from the Earth Gravitational Model of the eastern of the Aegean Sea and western of Anatolia were evaluated. The tensor and invariants of this gravity disturbance data were first calculated. New possible discontinuities have been identified in the tensors and some of the obtained discontinuities were clarified in their previous discussions. Also, the mean depths of the possible structures were calculated by the power spectrum method at four profiles taken from gravity disturbance data. These depth values are consistent with the depth values of the structural discontinuities obtained from previous studies. Finally, the upward continuation was applied to Tyy, Tyz and Tzz tensors up to 20 km. The positive anomaly values in Tyz and Tzz components and negative anomaly values in Tyy component are consistent with the Western Anatolia Transfer Zone. The structural differences between the eastern and the western of Western Anatolia are noteworthy in the upward continued results of the tensors. In addition, the positive and negative anomalies are notable in areas where the big earthquakes occurred in the last 3 years in the Tyz invariants.

Investigating Long-Term Behaviour of X-ray Binaries Using Archival Data

Long term modulations have been detected in a wide variety of both low and high-mass X-ray binaries. The All Sky Monitor on board the Rossi X-ray Timing Explorer provides the most extensive (~15 years) and sensitive X-ray archive for studying such behaviour. Since those variations were often intermittent and/or aperiodic, we used a time-dependent Dynamic Power Spectrum method to examine how the modulations themselves vary with time in a systematic way. Some were found to be remarkably stable, while others show a range of properties, from even longer variability time-scales to quite chaotic behaviour.

Identification of Cardiac Diseases from(ECG) Signals based on Fractal Analysis

This paper investigates the use of fractal geometry for analyzing ECG time series signals. A technique of identifying cardiac diseases is proposed which is based on estimation of Fractal Dimension (FD) of ECG recordings. Using this approach, variations in texture across an ECG signal can be characterized in terms of variations in the FD values. An overview of methods for computing the FD is presented focusing on the Power Spectrum Method (PSM) that makes use of the characteristic of Power Spectral Density Function (PSDF) of a Random Scaling Fractal Signal. A 20 dataset of ECG signals taken from MIT-BIH arrhythmia database has been utilized to estimate the FD, which established ranges of FD for healthy person and persons with various heart diseases. The obtained ranges of FD are presented in tabular fashion with proper analysis. Moreover, the experimental results showing comparison of Normal and Abnormal (arrhythmia) ECG signals and demonstrated that the PSM shows a better distinguish between the ECG signals for healthy and non-healthy persons versus the other methods.

Constructing Von Karman Random Media Model with Power Spectrum Method

In this paper, Von Karman random media is constructed with power spectrum method. The random media with Von Karman autocorrelation cannot be constructed in time domain but in frequency domain. So power spectrum method is utilized to solve the problem. The spectrum of random function is generated in frequency domain with random field and auto-correlation function. With inverse Fourier transformation, the Von Karman random media model is constructed. With different correlation lengths, six group of Von Karman random media are constructed.

Extracting Acoustic Emission Signal Feature of Grinding Processing

Acoustic Emission (AE) may be defined as a transient elastic stress wave generated by the rapid release of strain energy in local area of material. To overcome the limitation of some traditional techniques, the AE technique, which provides high sensitivity and responding speed, were developed in the present paper. AE signature is usually difficult to be extracted and characterized in grinding process of 1Cr18Ni9Ti coatings due to their high hardness, great ductility, inhomogeneous structure and irregular surface with lots of hard points and pores. In this paper, AE signal of stationary grinding status before wheel-workpiece contact was characterized first, then AE signal of the grinding process was analyzed using root-mean-square (RMS) and power spectrum method. Results showed that before the contact occurred, the grinding signal is stable, with low amplitude and frequency ranging all frequency channels and no peak signal. However, when contact occurred, the RMS and spectrum of AE signal increased obviously and the bandwidth varied exquisitely between 100 KHz and 300 KHz. The real contact time between wheel and workpiece was about 0.5 to 1 ms.