The consensus algorithm is the core mechanism of blockchain and is used to ensure data consistency among blockchain nodes. The PBFT consensus algorithm is widely used in alliance chains because it is resistant to Byzantine errors. However, the present PBFT (Practical Byzantine Fault Tolerance) still has issues with master node selection that is random and complicated communication. The IBFT consensus technique, which is enhanced, is proposed in this study and is based on node trust value and BLS (Boneh-Lynn-Shacham) aggregate signature. In IBFT, multi-level indicators are used to calculate the trust value of each node, and some nodes are selected to take part in network consensus as a result of this calculation. The master node is chosen

In order to reduce hydrostatic pressure in oil wells and produce oil from dead oil wells, laboratory rig was constructed, by injecting LPG through pipe containing mixture of two to one part of East Baghdad crude oil and water. The used pressure of injection was 2.0 bar, which results the hydrostatic pressure reduction around 246 to 222 mbar and flow rate of 34.5 liter/hr fluid (oil-water), at 220 cm injection depth. Effects of other operating parameters were also studied on the behavior of two phase flow and on the production of oil from dead oil wells.

Maximizing the net present value (NPV) of oil field development is heavily dependent on optimizing well placement. The traditional approach entails the use of expert intuition to design well configurations and locations, followed by economic analysis and reservoir simulation to determine the most effective plan. However, this approach often proves inadequate due to the complexity and nonlinearity of reservoirs. In recent years, computational techniques have been developed to optimize well placement by defining decision variables (such as well coordinates), objective functions (such as NPV or cumulative oil production), and constraints. This paper presents a study on the use of genetic algorithms for well placement optimization, a ty

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Oil well logging, also known as wireline logging, is a method of collecting data from the well environment to determine subterranean physical properties and reservoir parameters. Measurements are collected against depth along the well's length, and many types of wire cabling tools depend on the physical property of interest. Well probes generally has a dynamic respon to changes in rock layers and fluid composition. These probes or well logs are legal documents that record the history of a well during the drilling stages until its completion. Well probes record the physical properties of the well, which must then be interpreted in petrographic terms to obtain the characteristics of the rocks and flui

The rapid rise in the use of artificially generated faces has significantly increased the risk of identity theft in biometric authentication systems. Modern facial recognition technologies are now vulnerable to sophisticated attacks using printed images, replayed videos, and highly realistic 3D masks. This creates an urgent need for advanced, reliable, and mobile-compatible fake face detection systems. Research indicates that while deep learning models have demonstrated strong performance in detecting artificially generated faces, deploying these models on consumer mobile devices remains challenging due to limitations in computing power, memory, privacy, and processing speed. This paper highlights several key challenges: (1) optimiz

         The understanding exchange rate policy is fundamental in order to identify the mechanism by which works out macroeconomic, And the vital for macroeconomic analysis and empirical work to differentiate between the de facto regimes and de jure regimes, Where the proved surveys and studies issued by the international monetary fund that there is divergence between the de facto regime (Regime of exchange applied by the country actually) and between the de jure regime (Regime de jure through the documents and formal writings of officials of the central bank), And launched studies on the de facto regime (Being a the basis of evaluating monetary policy) Stabilized (peg-like)arrangements or

The aim of this study is to detect the level of psychological stress among unemployed individuals and the level of their wellbeing by finding the correlation between these two variables.

          The research sample consisted of (99) people who are currently unemployed and registered at the Ministry of Labor Affairs.

Schafer (1996) scale for psychological stress was used and alongside Ziout's (2012) scale for wellbeing.

          The results of the research showed an inverse relation between being unemployed and having wellbeing.

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Problem: Cancer is regarded as one of the world's deadliest diseases. Machine learning and its new branch (deep learning) algorithms can facilitate the way of dealing with cancer, especially in the field of cancer prevention and detection. Traditional ways of analyzing cancer data have their limits, and cancer data is growing quickly. This makes it possible for deep learning to move forward with its powerful abilities to analyze and process cancer data. Aims: In the current study, a deep-learning medical support system for the prediction of lung cancer is presented. Methods: The study uses three different deep learning models (EfficientNetB3, ResNet50 and ResNet101) with the transfer learning concept. The three models are trained using a