Worldwide, shipping documents are still primarily created and handled in the traditional paper manner. Processes taking place in shipping ports as a result are time-consuming and heavily dependent on paper. Shipping documents are particularly susceptible to paperwork fraud because they involve numerous parties with competing interests. With the aid of smart contracts, a distributed, shared, and append-only ledger provided by blockchain technology allows for the addition of new records. In order to increase maritime transport and port efficiency and promote economic development, this paper examines current maritime sector developments in Iraq and offers a paradigm to secure the management system based on a hyper-ledger fabric blockchain platform. The performance evaluation of the proposed system implies two scenarios: one organization and two organizations by examining throughput and latency. High transaction transmission rates on large block sizes produced positive results. Similarly, employing a small block size and higher send rates results in poor performance. Additionally, it was noted that throughput will decrease and latency will rise as the number of organizations increases. Block size and block timeouts should be high in applications with many concurrent transactions in order to maintain good throughput.
Laboratory model tests were performed to investigate the behavior of shallow and inclined skirted foundations placed on sandy soil with R.D%=30 and the extent of the impact of the positive and negative eccentric-inclined loading effect on them. To achieve the experimental tests, it was used a box of (600×600) mm cross-sectional and 600mm in height and a square footing of (50*50) mm and 10 mm in thickness attached to the skirt with Ds=0.5B and various an angle of (10°, 20°, 30°). The results showed that using skirts leads to a significant improvement in load-carrying capacity and decreased settlement. In addition, when the skirt angle increased, the ultimate load improved. Load-carrying capacity decreased with increasing eccentri
... Show MoreThis work aimed to study the effect of laser surface treatment on the mechanical characteristics and corrosion behaviour of grey cast iron type A159. Many technical applications used conventional surface treatment, but laser surface hardening has recently been used to enhance the surface properties of many alloys. The mechanical characteristics, including microstructure, microhardness, and wear resistance of A159 grey cast iron, were studied, in addition to corrosion behaviour. The experimental laser parameters in this work were 0.9, 1.2, and 1.5 KW power with continuous wave carbon dioxide lasers with scanning speeds of 10 and 12 mm/s were used. The results found that phase-transitional alterations in microstructure were influenced by lase
... Show MoreIn recent years, various methods have been developed to enhance the characteristics of asphalt pavement in order to face the continuous challenges of increasing traffic loads and changing climate conditions. One of the most popular and successful methods is modifying the asphalt mixtures or asphalt binder with the addition of polymers. Therefore, two types of Polyethylene (PE) polymer, High-Density PE (HDPE) and Low-Density PE (LDPE), are used in this research. Two methods were applied to prepare PE-modified asphalt mixtures: Semi-Wet Method (S-WM) and Dry Method (DM). The findings of the investigation indicated that the addition of PE polymer can reduce the wear loss of aggregate. In general, the experimental results revealed that asphalt
... Show MoreThe multimetric Phytoplankton Index of Biological Integrity (P-IBI) was applied throughout Rostov on Don city (Russia) on 8 Locations in Don River from April – October 2019. The P-IBI is composed from seven metrics: Species Richness Index (SRI), Density of Phytoplankton and total biomass of phytoplankton and Relative Abundance (RA) for blue-green Algae, Green Algae, Bacillariophyceae and Euglenaphyceae Algae. The average P-IBI values fell within the range of (45.09-52.4). Therefore, water throughout the entire study area was characterized by the equally "poor" quality. Negative points of anthropogenic impact detected at the stations are: Above the city of Rostov-on-Don (1 km, higher duct Aksai) was 38.57 i
... Show MoreLittle is known about hesitancy to receive the COVID‐19 vaccines. The objectives of this study were (1) to assess the perceptions of healthcare workers (HCWs) and the general population regarding the COVID‐19 vaccines, (2) to evaluate factors influencing the acceptance of vaccination using the health belief model (HBM), and (3) to qualitatively explore the suggested intervention strategies to promote the vaccination.
This was a cross‐sectional study based on electronic survey data that was collected in Iraq during December first‐19th, 2020. The electronic surve
Karbala province regarded one part significant zones in Iraq and considered an economic resource of vegetation such as trees of fruits, sieve and other vegetation. This research aimed to utilize Normalized Difference Vegetation index (NDVI) and Subtracted (NDVI) for investigating the current vegetation cover at last four decay. The Normalized Difference Vegetation Index (NDVI) is the most extensively used satellite index of vegetation health and density. The primary goals of this research are gather a gathering of studied area (Karbala province) satellite images in sequence time for a similar region, these image captured by Landsat (TM 1985, TM 1995, ETM+ 2005 and Landsat 8 OLI (Operational Land Imager) 2015. Preprocessing such gap filli
... Show MoreThis study proposes a pioneering Ethical Artificial Intelligence (EAI) framework for advancing sustainable development in Iraq by integrating eight multidimensional sustainability indicators—administrative, technological, economic, environmental, social, legal, security, and governance. Utilizing data from 60 completed development projects, the framework combines SPSS statistical analysis, the SMART-AI model, and Artificial Neural Networks (ANN) to identify key determinants of project success and failure. Results reveal a 37% project failure rate, with administrative and technological deficiencies emerging as the most influential predictors. The SMART-AI model achieved an accuracy of 91.3% using stratified k-fold cross-validation. A bilin
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