Contribution of integrating seismic coherency and AVO attributes in delineating sand bars reservoirs,Offshore Nile Delta,Egypt, A case study

The geometry and extension of Offshore Nile Delta sand bar complex deposited in a structurally controlled shallow marine basin is delineated by integrating seismic coherency and AVO attributes. Coherency is the imaging of discontinuities within the seismic data, where faults, sand bar boundaries and fluid contacts (GWC) were mapped, using an optimum analysis window of 40 × 40 × 64, and instantaneous amplitude of time slice image map at 1652 ms. AVO attributes are applied to reservoir sands of significant bright spot response. AVO attributes volumes, include the (A * B), (A + B), and (A ? B) of the intercept and gradient, generated from near, mid, and far angle stacks. The seismic coherency volume delineated two major bounding faults of the reservoir, that converged at the western end of the field and open out to the east where, the reservoir is dip-closed. Four boundaries between five sand bars oriented in NW-SE direction are detected. GWC is delineated at the deepest part of the reservoir towards the southeastern part.AVO attributes indicated that the reservoir top is characterized by positive bright spots, negative Poisson’s ratio, and increasing in the scaled S-reflectivity. Meanwhile, the bottom is characterized by bright spots, positive Poisson’s ratio, and decreasing in the scaled S-reflectivity. AVO volumes were consistent, and show the typical response of Class III gas sands. Five high positive amplitude sand bars oriented NW-SE are confirmed. Three of them were successfully tested. The two prolific southern sand bars exhibit higher amplitude haven’t been tested.     

Exploring video content structure for hierarchical summarization

In this paper, we propose a hierarchical video summarization strategy that explores video content structure to provide the users with a scalable, multilevel video summary. First, video-shot- segmentation and keyframe-extraction algorithms are applied to parse video sequences into physical shots and discrete keyframes. Next, an affinity (self-correlation) matrix is constructed to merge visually similar shots into clusters (supergroups). Since video shots with high similarities do not necessarily imply that they belong to the same story unit, temporal information is adopted by merging temporally adjacent shots (within a specified distance) from the supergroup into each video group. A video-scene-detection algorithm is thus proposed to merge temporally or spatially correlated video groups into scenario units. This is followed by a scene-clustering algorithm that eliminates visual redundancy among the units. A hierarchical video content structure with increasing granularity is constructed from the clustered scenes, video scenes, and video groups to keyframes. Finally, we introduce a hierarchical video summarization scheme by executing various approaches at different levels of the video content hierarchy to statically or dynamically construct the video summary. Extensive experiments based on real-world videos have been performed to validate the effectiveness of the proposed approach.Published online: 15 September 2004 Corespondence to: Xingquan ZhuThis research has been supported by the NSF under grants 9972883-EIA, 9974255-IIS, 9983248-EIA, and 0209120-IIS, a grant from the state of Indiana 21^th Century Fund, and by the U.S. Army Research Laboratory and the U.S. Army Research Office under grant DAAD19-02-1-0178.     

An Immutable Framework for Smart Healthcare Using Blockchain Technology

The advancements in sensing technologies, information processing, and communication schemes have revolutionized the healthcare sector. Electronic Healthcare Records (EHR) facilitate the patients, doctors, hospitals, and other stakeholders to maintain valuable data and medical records. The traditional EHRs are based on cloud-based architectures and are susceptible to multiple cyberattacks. A single attempt of a successful Denial of Service (DoS) attack can compromise the complete healthcare system. This article introduces a secure and immutable blockchain-based framework for the Internet of Medical Things (IoMT) to address the stated challenges. The proposed architecture is on the idea of a lightweight private blockchain-based network that facilitates the users and hospitals to perform multiple healthcare-related operations in a secure and trustworthy manner. The efficacy of the proposed framework is evaluated in the context of service execution time and throughput. The experimental outcomes indicate that the proposed design attained lower service execution time and higher throughput under different control parameters.