Reservoir characterization is an important component of hydrocarbon exploration and production, which requires the integration of different disciplines for accurate subsurface modeling. This comprehensive research paper delves into the complex interplay of rock materials, rock formation techniques, and geological modeling techniques for improving reservoir quality. The research plays an important role dominated by petrophysical factors such as porosity, shale volume, water content, and permeability—as important indicators of reservoir properties, fluid behavior, and hydrocarbon potential. It examines various rock cataloging techniques, focusing on rock aggregation techniques and self-organizing maps (SOMs) to identify specific and

Stereo lithography (SLA) three-dimensional (3D) printing process is a type of additive manufacturing techniques that uses digital models from computer-aided design to automatically produce customized 3D objects. Around 30 years, it has been widely utilized in the manufacturing, design, engineering, industrial sectors and its applications in dentistry for manufacturing prosthodontics are very important. The stereo lithography technology is highly regarded because it can produce items with excellent precision especially when selecting the best process parameters. This review article offers a useful and scientific summary of SLA three-dimensional printing technology and its brief history. The specific type of 3D printers which is SLA t

HTH Ahmed Dheyaa Al-Obaidi,", Ali Tarik Abdulwahid', Mustafa Najah Al-Obaidi", Abeer Mundher Ali', eNeurologicalSci, 2023

Feature selection (FS) constitutes a series of processes used to decide which relevant features/attributes to include and which irrelevant features to exclude for predictive modeling. It is a crucial task that aids machine learning classifiers in reducing error rates, computation time, overfitting, and improving classification accuracy. It has demonstrated its efficacy in myriads of domains, ranging from its use for text classification (TC), text mining, and image recognition. While there are many traditional FS methods, recent research efforts have been devoted to applying metaheuristic algorithms as FS techniques for the TC task. However, there are few literature reviews concerning TC. Therefore, a comprehensive overview was systematicall

Stereo lithography (SLA) three-dimensional (3D) printing process is a type of additive manufacturing techniques that uses digital models from computer-aided design to automatically produce customized 3D objects. Around 30 years, it has been widely utilized in the manufacturing, design, engineering, industrial sectors and its applications in dentistry for manufacturing prosthodontics are very important. The stereo lithography technology is highly regarded because it can produce items with excellent precision especially when selecting the best process parameters. This review article offers a useful and scientific summary of SLA three-dimensional printing technology and its brief history. The specific type of 3D printers which is SLA type b

Incorporating modern technology into education is becoming imperative. Numerous pharmacy institutions are incorporating virtual reality (VR) technology training into their curricula to enhance educational experience. This review examines the current state, historical evolution, and application of VR programs in pharmacy education and training. The review also provides details about the main challenges and limitations associated with the use of this technology. The VR technology, including virtual laboratories and simulations, significantly improves clinical training and educational outcomes. The utilization of VR in clinical teaching encounters numerous barriers, including ethical concerns and technological constraints, as well as other res

Sensibly highlighting the hidden structures of many real-world networks has attracted growing interest and triggered a vast array of techniques on what is called nowadays community detection (CD) problem. Non-deterministic metaheuristics are proved to competitively transcending the limits of the counterpart deterministic heuristics in solving community detection problem. Despite the increasing interest, most of the existing metaheuristic based community detection (MCD) algorithms reflect one traditional language. Generally, they tend to explicitly project some features of real communities into different definitions of single or multi-objective optimization functions. The design of other operators, however, remains canonical lacking any inte