Monte Carlo-based Noise Compensation in Coil Intensity Corrected Endorectal MRI

Background: Prostate cancer is one of the most common forms of cancer found in males making early diagnosis important. Magnetic resonance imaging (MRI) has been useful in visualizing and localizing tumor candidates and with the use of endorectal coils (ERC), the signal-to-noise ratio (SNR) can be improved. The coils introduce intensity inhomogeneities and the surface coil intensity correction built into MRI scanners is used to reduce these inhomogeneities. However, the correction typically performed at the MRI scanner level leads to noise amplification and noise level variations. Methods: In this study, we introduce a new Monte Carlo-based noise compensation approach for coil intensity corrected endorectal MRI which allows for effective noise compensation and preservation of details within the prostate. The approach accounts for the ERC SNR profile via a spatially-adaptive noise model for correcting non-stationary noise variations. Such a method is useful particularly for improving the image quality of coil intensity corrected endorectal MRI data performed at the MRI scanner level and when the original raw data is not available. Results: SNR and contrast-to-noise ratio (CNR) analysis in patient experiments demonstrate an average improvement of 11.7 dB and 11.2 dB respectively over uncorrected endorectal MRI, and provides strong performance when compared to existing approaches. Conclusions: A new noise compensation method was developed for the purpose of improving the quality of coil intensity corrected endorectal MRI data performed at the MRI scanner level. We illustrate that promising noise compensation performance can be achieved for the proposed approach, which is particularly important for processing coil intensity corrected endorectal MRI data performed at the MRI scanner level and when the original raw data is not available.Comment: 23 page

PADS: Practical Attestation for Highly Dynamic Swarm Topologies

Remote attestation protocols are widely used to detect device configuration (e.g., software and/or data) compromise in Internet of Things (IoT) scenarios. Unfortunately, the performances of such protocols are unsatisfactory when dealing with thousands of smart devices. Recently, researchers are focusing on addressing this limitation. The approach is to run attestation in a collective way, with the goal of reducing computation and communication. Despite these advances, current solutions for attestation are still unsatisfactory because of their complex management and strict assumptions concerning the topology (e.g., being time invariant or maintaining a fixed topology). In this paper, we propose PADS, a secure, efficient, and practical protocol for attesting potentially large networks of smart devices with unstructured or dynamic topologies. PADS builds upon the recent concept of non-interactive attestation, by reducing the collective attestation problem into a minimum consensus one. We compare PADS with a state-of-the art collective attestation protocol and validate it by using realistic simulations that show practicality and efficiency. The results confirm the suitability of PADS for low-end devices, and highly unstructured networks.Comment: Submitted to ESORICS 201

Islam and contemporary society: emerging paradigms to explain muslim communities

There is hardly any country, where most of the people do not follow a particular religious view, but no other religious groups need to address so many controversies as the Muslims do. Islam is no more merely a religion; it is a political agenda, a manifestation of orthodoxy, an enticement to establish particular ideology and many more. Islam has integrated a variety of political and social facet into it; hence diversity in comprehension emerged. Various scholars analyzed numerous aspects of Islam. This paper attempts to narrate the most imperative aspects of Islam in the modern day and tries to delineate the significant role that Islam plays in the life and living of individuals of all around the world

Artificial Recharge of Groundwater as a Management Tool for the Kabul Basin, Afghanistan

Decades of war and political instability, consecutive droughts, population increase and displacement, caused serious infrastructural damages to water resources of Afghanistan. The main source of water supply for people in Afghanistan is groundwater. However, over-exploitation of groundwater has led to groundwater level declines in most parts of the country. Kabul, the largest city of Afghanistan, is the capital city with a population of 4.5 million and the fifth fastest-growing city in the world. The city has observed groundwater level declines of 5-10 meters (m) since 1980. Decline of about 30 m has also been observed in one of the monitoring wells in the Kabul City. The groundwater level decline will considerably affect life, agriculture and industry in Kabul, Afghanistan. This study proposes an artificial recharge of groundwater by surplus flow of the Kabul River in rainy season, as a management tool for the Kabul Basin, Afghanistan. A direct surface recharge method by means of a recharge basin is suggested to help natural recharge. Computer programs MODFLOW-2005, MODPATH 6 and Groundwater Modeling System (GMS) have been employed in this study. The objective of the study is to increase groundwater storage in the basin so as to reach the sustainable yield. Results indicate that a daily diversion of 75000 cubic meters per day (m3/d) from the Kabul River to the recharge basin during rainy season, increases the groundwater storage by an annual amount of 9 million cubic meters (Mm3) and fulfills the objective of the study. Results also show that recharged water remains in the groundwater storage sufficient time to ensure water quality improvements. This study is the first ever work on evaluating the applicability and effectiveness of artificial recharge in Afghanistan. The approach followed in this thesis is backed by careful review of studies on water resources in Afghanistan, exploring literatures in the topic of artificial recharge, and utilization of newest applications of related groundwater computer programs. Therefore, this study suits as an insight for future researches on artificial recharge of groundwater in Afghanistan

Inference on \u3cem\u3e(Y \u3c X)\u3c/em\u3e in a Pareto Distribution

Inference on the reliability R = P(Y \u3c X) in a Pareto distribution with a known scale parameter is considered. Point estimates and confidence intervals of R are obtained a test of hypothesis is also considered