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"Hussein, Hayder"
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Review of Domain-Based Novelty Detection Using One Class Support Vector Machine
Novelty detection is a critical task in machine learning and data mining, aiming to identify previously unseen or abnormal patterns that are not represented during model training. Among the available novelty detection paradigms, domain-description approaches are particularly attractive because they learn an explicit boundary of normal data without strong distributional assumptions. This paper provides a focused review of domain-based novelty detection methods with emphasis on Support Vector Machine (SVM) formulations, particularly Support Vector Data Description (SVDD) and One-Class Support Vector Machines (OCSVM). We summarize the theoretical foundations of one-class classification and review recent research that enhances SVDD and OCSVM through robust boundary learning, improved feature representations, and computational efficiency. Based on the analyzed literature, the main technical directions for improving OCSVM and SVDD can be grouped into three trends: (i) robustification via modified loss functions and outlier-resistant formulations, (ii) integration with feature learning frameworks such as deep models and hybrid architectures, and (iii) acceleration strategies for large-scale and high-dimensional settings. Despite consistent performance improvements across applications, parameter sensitivity, optimization complexity, and limited adaptability under evolving data distributions remain persistent challenges. Finally, we outline concrete research opportunities toward scalable, adaptive, and self-tuning domain-description models for reliable deployment in real-world novelty detection scenarios.
Journal Article
A Review of the Effects of Key Parameters on the Performance of Horizontal and Vertical Axis Wind Turbines
Wind energy has emerged as one of the fastest-growing renewable energy sources, with horizontal axis wind turbines (HAWTs) predominantly deployed in large-scale applications. However, their effectiveness in urban environments is limited due to fluctuating wind patterns and space constraints. In contrast, vertical axis wind turbines (VAWTs) offer advantages such as compact design, low noise levels, and stable performance under low-speed and turbulent wind conditions, making them more suitable for urban settings. This review examines the performance characteristics of key VAWT configurations, including lift-based Darrieus turbines, drag-based Savonius turbines, and hybrid designs. Typical power coefficients (Cp) for these designs are approximately 0.4 for Darrieus, 0.15-0.2 for Savonius, and 0.3-0.35 for hybrid models. Optimal operation is generally achieved at a tip speed ratio (TSR) of 0.45, corresponding to a maximum Cp of around 0.306 and a torque coefficient of 0.68. The review also identifies critical design and operational parameters influencing turbine performance. Finally, it highlights the need for continued research to enhance efficiency, reliability, and integration of VAWTs into future urban energy systems.
Journal Article
Review on rehabilitation of rc deep beams using external bonded frp and nsm technique
Due to a variety of reasons, including increased service loads, environmental impacts, construction errors, and mechanical impediments, the strengthening process was becoming necessary for many concrete buildings worldwide. The strengthening process is carried out in several ways, the most common of which are the Near-Surface mounted (NSM) technique and the External Bonded Reinforcement (EBR) technique. The main object of the strengthening process is to increase the strength and durability of reinforced concrete structures and reducing early failure. This research discussed the most important papers that dealt with strengthening deep beams due to their exposure to heat or extreme loads using two techniques (NSM) and (EBR). Several results were reached through experimental testing of the specimens of each research, especially the most important of them: First, making openings, when necessary, away from the loading path because the opening in the loading path reduces the capacity of the beam. Secondly, resorting to using the mechanical method when installing the fiber-reinforced polymer externally, as it greatly reduces the tearing and collapse of the sheets. Third, the number of layers must be less than three when using (GFRP) sheets in the strengthening process, as violating this will cause a decrease in the final capacity of the beam. Fourth, resorting to inclined schemes when strengthening deep beams or repairing them with various materials made of carbon fiber-reinforced polymer (FRP). Finally, it is possible to use (CFRP) bars with (NSM) technology, as this option can be relied upon to rehabilitate damaged structures.
Journal Article
Numerical Tracking of the Behavior of Repaired Reinforced Concrete Beams by CFRP Sheets against Shear
This study simulates a procedure of rehabilitation of reinforced concrete beams with the aid of ANSYS 17 software. In this work, the BIRTH and DEATH procedure (in ANSYS) was adopted to model the post-repairing stage. This aspect has rarely been considered by previous studies that utilized a carbon fiber reinforced polymer (CFRP) sheet when retrofitting. To verify the suggested technique, six specimens were analyzed with two values of shear span-to-depth ratios (3 and 4) and three spaces of CFRP sheets (100mm, 150mm and 200mm). The effect of the repairing process on the structural performance of the retrofitted beam is also investigated.It is found that the suggested technique yielded a good agreement with the experimental results and the maximum differences in the failure loads between the numerical and experimental results were 10% and 4% for shear span-to-depth ratios of 3 and 4, respectively. It was also ascertained that upgrading reinforced concrete members within the early stages of loading showed a better enhancement in the loading capacity compared to upgrading reinforced concrete members close to the juncture of failure.
Journal Article
Heat Shock Affects Amino Acid Metabolism in Bovine Cumulus Cells and Denuded Oocytes During In Vitro Maturation
Increased heat levels can affect follicle development, oocyte maturation, and bovine fertility by disrupting amino acid (AA) metabolism and oocyte competence. This study aimed to explore the effect of heat shock on AA metabolism in bovine cumulus cells (CCs) or denuded oocytes (DOs). CCs and DOs were separately cultured for 24 h in vitro at 38.5 °C (control group), 39.5 °C (moderate heat shock-CC, MHS-CC group), or 40.5 °C (high heat shock-CC, HHS-CC group). AA levels were analyzed in 24-h in vitro maturation media using high-performance liquid chromatography. The findings indicated that the HHS-CC group consumed more AAs than the control (p = 0.04) or MHS-CC group (p = 0.03). Compared with the control and HHS-CC groups, the MHS-CC group exhibited elevated alanine levels (p = 0.02). The MHS-CC (p = 0.03) and HHS-CC (p = 0.03) groups exhibited significantly greater glutamine depletion than the control group. The HHS-DO group exhibited significant lysine depletion (p < 0.01) but produced more tryptophan than the control and MHS-DO groups (p = 0.02). In contrast to the control and MHS-DO groups, the HHS-DO group displayed a notably elevated level of appearance (p = 0.005) and net balance (p = 0.005) for all AAs. The findings imply that heat shock may alter the metabolism of certain AAs in CCs and DOs, thereby affecting the developmental competence of bovine oocytes.
Journal Article
Extramedullary chronic phase chronic myeloid leukaemia (CML) involving the central nervous system: A case report
Chronic myeloid leukaemia (CML) has been classically described as a disease restricted to the bone marrow with very few reports of extramedullary involvement. CNS involvement with CML has been described in the literature as an aggressive disease in the leukaemic phase either preceding or coexisting with medullary blast crisis or seen in patients with long‐term Imatinib therapy. No treatment consensus exists for this patient group and outcomes remain poor. We hereby present a very rare report of CNS involvement with chronic phase CML at diagnosis in a patient who presented with raised intracranial pressure and cranial nerve palsies.
Journal Article
A Framework Questionnaire for Diagnosing Infectious Disease Using Machine Learning Techniques
Infectious diseases weigh down the communities in the world and scientists to spend more effort via keeping tracking of evolving treatment and detecting methods. These diseases may lead to harm life of people. Early diagnosis could significantly support healthcare specialists to save more lives. Additionally, the pandemic leads to maximizing hospitals visits, medical clinics and healthcare centres. The international health organizations also have shown that there has been a rapid growth of infected cases. Therefore, correct diagnosis has become a pressing problem. Consequently, automated diagnosis becomes a sensible solution to the problem of these diagnosis challenges. This study was conducted to identify the most common infectious diseases in the Iraqi society using a well-designed questionnaire and a proposed automated diagnostic technique. Firstly, the top diseases questionnaire is distributed around the city of Baghdad to different medical clinics. The results from the preliminary analysis of the collected responses (115 responses) showed that the most common widespread diseases in the Iraqi community are diabetes, flu, and typhoid. This was followed by another questionnaire for the identification of symptoms and blood test variables for these diseases. It is worth pointing out that there are not sufficient and updated studies dealing with the diseases that attack the Iraqi community. Toward the automated diagnosis, both infectious diseases (flu and typhoid), identified symptoms are employed as feature space with one of the machine learning techniques. For the results evaluation different measures, such as accuracy, confusion matrix, and efficient verification via ROC, have been used to indicate the system performance. The result shows that typhoid disease has significant diagnosis accuracy of 98% compared to the others. While three machine learning systems named (Native Bayes, Linear discriminant, and Ensemble (subspace discriminant)) were used to diagnose flu disease. The resulting accuracy of all three models are 92% which shows good performing. Therefore, the proposed method shows precise accuracy and systematic manner for analyzing infectious diseases.
Journal Article
Acanthamoeba Spp. Detection in Contact Lens Wearers and Non-Wearers in Iraq
Background: Acanthamoeba spp. are free-living amoebae found in a broad range of environments. Acanthamoeba spp. are responsible for about 20% of keratitis infections in contact lens wearers. We aimed to detect Acanthamoeba spp. and determined the prevalence of Acanthamoeba spp. in contact lens wearers to increase health awareness of the risks of spreading it. Methods: The current study included an investigation of free-living opportunistic amoeba Acanthamoeba spp. in eye swab samples among students in the College of Sciences at the University of Thi-Qar/Iraq. Eighty-eight samples were collected from the eyes of both sexes and for both lens wearers and non-lens wearers from January to April 2024. Results: The current study results showed that the percentage of Acanthamoeba was 4.5% (4/88). All positive cases were in females who were lens wearers only, and no cases were recorded in males or females who had no contact lens. Acanthamoeba spp. were identified morphologically based on characteristics of active trophozoites and cyst forms, and molecular identified by conventional PCR using Acanthamoeba primers JPD1/ JPD2. Additionally, sequencing analysis was performed on positive samples and their alignment sequences were analyzed using BLAST. The results showed a homologous identity (100%) for four samples with the reference isolate Acanthamoeba spp. 18S ribosomal RNA gene )MK390853.1). It was registered as one isolate of Acanthamoeba spp. in gene bank with accession number (PQ661179.1). Conclusion: the current findings indicate the prevalence of Acanthamoeba spp. in contact lens wearers, which is a health risk, especially in females
Journal Article