Today’s modern medical imaging research faces the challenge of detecting brain tumor through Magnetic Resonance Images (MRI). Normally, to produce images of soft tissue of human body, MRI images are used by experts. It is used for analysis of human organs to replace surgery. For brain tumor detection, image segmentation is required. For this purpose, the brain is partitioned into two distinct regions. This is considered to be one of the most important but difficult part of the process of detecting brain tumor. Hence, it is highly necessary that segmentation of the MRI images must be done accurately before asking the computer to do the exact diagnosis. Earlier, a variety of algorithms were developed for segmentation of MRI images by usin

In recent years, Wireless Sensor Networks (WSNs) are attracting more attention in many fields as they are extensively used in a wide range of applications, such as environment monitoring, the Internet of Things, industrial operation control, electric distribution, and the oil industry. One of the major concerns in these networks is the limited energy sources. Clustering and routing algorithms represent one of the critical issues that directly contribute to power consumption in WSNs. Therefore, optimization techniques and routing protocols for such networks have to be studied and developed. This paper focuses on the most recent studies and algorithms that handle energy-efficiency clustering and routing in WSNs. In addition, the prime

Fish are regarded as a crucial indicator of alterations in the aquatic environment due to their position at the apex of the food chain. Monitoring these alterations is crucial for identifying modifications in the aquatic ecosystem. The principal elements influencing fish health are temperature, pH, dissolved oxygen, salinity, pesticide contamination, microplastics, and algal presence. These elements substantially influence fish health regarding development, reproduction, respiration, oxygen stress, and the internal enzymes associated with digesting and other metabolic functions. Alterations in global environmental conditions and anthropogenic pollutants result in modifications to fish populations, their lives, and their behavior and

The aim of this work is the synthesis of new grafted PVA polymer with a derivative of Erythro-ascorbic acid (pentulosono-ɣ -lactone-2, 3-enedianisoate). All synthesized compounds were characterized by thin layer chromatography (TLC) and FTIR spectra and aldehyde was also characterized by (U.V-Vis), 1HNMR, 13CNMR and mass spectra. They were also evaluated for antimicrobial properties by dilute method against four pathogenic bacteria (Escherichia coli ,Klebsiella pneumonae, Staphylococcus aureus, Staphylococcus Albus) and two fungal (Aspergillus Niger, Yeast). All polymer metal complexes showed good activities against the various microbial isolates. The polymer metal complexes showed higher activity than the free polymer. The order of increa

Thrust blocks and restraint joints are the two most popular methods of counteracting the thrust force that generated at pipe fittings (bends, Tee, wye, reducers, dead ends, etc…). Both systems perform the same function, which is to prevent the joints from separating from the pipes. The aim of the study is to review previous studies and scientific theories related to the study and design of thrust blocks and restraint joints to study the behavior of both systems under thrust force and to study the factors and variables that affect the behavior of these systems. The behavior of both systems must be studied because they cannot be abandoned, as each system has conditions whose use is more feasible, scientific, and economic

Significant advances in the automated glaucoma detection techniques have been made through the employment of the Machine Learning (ML) and Deep Learning (DL) methods, an overview of which will be provided in this paper. What sets the current literature review apart is its exclusive focus on the aforementioned techniques for glaucoma detection using the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) guidelines for filtering the selected papers. To achieve this, an advanced search was conducted in the Scopus database, specifically looking for research papers published in 2023, with the keywords "glaucoma detection", "machine learning", and "deep learning". Among the multiple found papers, the ones focusing

Over the past few years, ear biometrics has attracted a lot of attention. It is a trusted biometric for the identification and recognition of humans due to its consistent shape and rich texture variation. The ear presents an attractive solution since it is visible, ear images are easily captured, and the ear structure remains relatively stable over time.  In this paper, a comprehensive review of prior research was conducted to establish the efficacy of utilizing ear features for individual identification through the employment of both manually-crafted features and deep-learning approaches. The objective of this model is to present the accuracy rate of person identification systems based on either manually-crafted features such as D

Background: Significant advancements have been observed in the additive manufacturing (AM) technology industry in recent decades. Due to the inherent variations among each AM manufacturing technique, new areas of investigation continually arise and require consideration. Additionally, the novel applications of additive manufacturing present new difficulties and possibilities for targeted focus. The aim of this manuscript is to conduct a comprehensive literature review that describes the various processing methods, precision levels, types of materials utilized, and potential applications of 3D printing technology in the field of dentistry. Data: An online search was conducted on databases including Research Gate, Google Scholar, and

Subcutaneous vascularization has become a new solution for identification management over the past few years. Systems based on dorsal hand veins are particularly promising for high-security settings. The dorsal hand vein recognition system comprises the following steps: acquiring images from the database and preprocessing them, locating the region of interest, and extracting and recognizing information from the dorsal hand vein pattern. This paper reviewed several techniques for obtaining the dorsal hand vein area and identifying a person. Therefore, this study just provides a comprehensive review of existing previous theories. This model aims to offer the improvement in the accuracy rate of the system that was shown in previous studies and