Reliable data transfer and energy efficiency are the essential considerations for network performance in resource-constrained underwater environments. One of the efficient approaches for data routing in underwater wireless sensor networks (UWSNs) is clustering, in which the data packets are transferred from sensor nodes to the cluster head (CH). Data packets are then forwarded to a sink node in a single or multiple hops manners, which can possibly increase energy depletion of the CH as compared to other nodes. While several mechanisms have been proposed for cluster formation and CH selection to ensure efficient delivery of data packets, less attention has been given to massive data communication processes with sink node. As such, failure in communicating nodes would lead to a significant network void-holes problem. Considering the limited energy resources of nodes in UWSNs along with the heavy load of CHs in the routing process, this paper proposes a void-holes aware and reliable data forwarding strategy (VHARD-FS) in a proactive mode to control data packets delivery from CH nodes to the sink in UWSNs. In the proposed strategy, each CH node is aware of its neighbor’s performance ranking index to conduct a reliable packet transmission to the sink via the most energy-efficient route. Extensive simulation results indicate that the VHARD-FS outperforms existing routing approaches while comparing energy efficiency and network throughput. This study helps to effectively alleviate the resource limitations associated with UWSNs by extending network life and increasing service availability even in a harsh underwater environment.
The oil and gas industry relies heavily on IT innovations to manage business processes, but the exponential generation of data has led to concerns about processing big data, generating valuable insights, and making timely decisions. Many companies have adopted Big Data Analytics (BDA) solutions to address these challenges. However, determining the adoption of BDA solutions requires a thorough understanding of the contextual factors influencing these decisions. This research explores these factors using a new Technology-Organisation-Environment (TOE) framework, presenting technological, organisational, and environmental factors. The study used a Delphi research method and seven heterogeneous panelists from an Oman oil and gas company
... Show MoreHartha Formation is an overburdened horizon in the X-oilfield which generates a lot of Non-Productive Time (NPT) associated with drilling mud losses. This study has been conducted to investigate the loss events in this formation as well as to provide geological interpretations based on datasets from nine wells in this field of interest. The interpretation was based on different analyses including wireline logs, cuttings descriptions, image logs, and analog data. Seismic and coherency data were also used to formulate the geological interpretations and calibrate that with the loss events of the Hartha Fm.
The results revealed that the upper part of the Hartha Fm. was identified as an interval capable of creating potentia
... Show MoreOne of the most significant elements influencing weather, climate, and the environment is vegetation cover. Normalized Difference Vegetation Index (NDVI) and Normalized Difference Built-up Index (NDBI) over the years 2019–2022 were estimated based on four Landsat 8 TIRS’s images covering Duhok City. Using the radiative transfer model, the city's land surface temperature (LST) during the next four years was calculated. The aim of this study is to compute the temperature at the land's surface (LST) from the years 2019-2022 and understand the link, between LST, NDVI, and NDBI and the capability for mapping by LANDSAT-8 TIRS's. The findings revealed that the NDBI and the NDVI had the strongest correlation with the
... Show MoreThe purpose of this paper is to apply different transportation models in their minimum and maximum values by finding starting basic feasible solution and finding the optimal solution. The requirements of transportation models were presented with one of their applications in the case of minimizing the objective function, which was conducted by the researcher as real data, which took place one month in 2015, in one of the poultry farms for the production of eggs
... Show MoreData scarcity is a major challenge when training deep learning (DL) models. DL demands a large amount of data to achieve exceptional performance. Unfortunately, many applications have small or inadequate data to train DL frameworks. Usually, manual labeling is needed to provide labeled data, which typically involves human annotators with a vast background of knowledge. This annotation process is costly, time-consuming, and error-prone. Usually, every DL framework is fed by a significant amount of labeled data to automatically learn representations. Ultimately, a larger amount of data would generate a better DL model and its performance is also application dependent. This issue is the main barrier for
The aim of the current research is to identify the impact of the SWOT strategy on developing systemic intelligence among students of the Ibn Rushd College of Education for Human Sciences University of Baghdad / College of Education Ibn Rushd for Human Sciences. The current research community consists of (8590) male and female students, divided into (7) departments. The current research relied on one of the partial control designs, which is the design of non-random groups: experimental group and a control group with a pre and post-test. As for the research tool, It was represented by Tourmanin’s Systemic Intelligence Scale (2012) of (50) items that measure the eight components of systemic intelligence. The results of the Mann Whitney te
... Show MoreThe adoption of the concept of preventive war in any country especially in a country like the United States result in a lot of serious consequences, so that pre-emptive military action may alter certain regional arrangements based on the basis of political and security balance, and reduce the incidence of tensions that may worsen a sudden during the application of preventive war, so the concept is applicable to be a risk much more when you face the reality and that because the issues more importantly, it should prepare a detailed and careful study of the post –stage of the use of preventive military action and this requires realy no papers insist or documents discuss this but accurate this field study of the situation thereafter.
This article proposes a new strategy based on a hybrid method that combines the gravitational search algorithm (GSA) with the bat algorithm (BAT) to solve a single-objective optimization problem. It first runs GSA, followed by BAT as the second step. The proposed approach relies on a parameter between 0 and 1 to address the problem of falling into local research because the lack of a local search mechanism increases intensity search, whereas diversity remains high and easily falls into the local optimum. The improvement is equivalent to the speed of the original BAT. Access speed is increased for the best solution. All solutions in the population are updated before the end of the operation of the proposed algorithm. The diversification f
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