http://ijaers.com/ Open Access international Journal to publish research paper en-us December Hot-arid regions such as Baghdad have building typologies with high knowledge to the combination of mechanical cooling systems as well as low dependency on the environment. This study aims at countering such energy consumption in office buildings with the use of generative design AI tools. A comparative energy model was implemented and run between a standard design model (A) and a model optimized with AIs (B) through Galapagos, Ladybug, Honeybee and EnergyPlus modules in Rhino-Grasshopper. The models were assessed based on the same criteria, such as Energy Use Intensity (EUI), thermal comfort (PMV), ventilation (ACH), and solar radiation. The findings are that Model B has realized an energy saving of 25.9 %, a 177 percent better ventilation efficiency and acceptable comfort level. The findings underscore the worth of incorporating AI and generative design earlier on in the architect. http://ijaers.com/detail/harnessing-artificial-intelligence-for-sustainable-office-building-design-in-baghdad-a-comparative-analysis-of-traditional-vs-generative-environmental-approaches/ Osamah A. Al-Tameemi http://ijaers.com/uploads/issue_files/1IJAERS-1120252-Harnessing.pdf From an energy perspective, the water-particle velocity equations derived from the Euler or Navier Stokes momentum conservation formulations show an imbalance: kinetic energy changes occur through variations in velocity, but no corresponding source of potential energy is included. To supply this missing potential energy, a Momentum Equilibrium Equation is introduced, and its horizontal velocity is superimposed on the velocity from the momentum conservation equation. Three modifications are applied to the Euler momentum equation: reducing the driving force, applying a weighted Taylor series to the total acceleration, and treating the convective acceleration as a hydrodynamic force. Model results on a sloping bottom show that the approach can simulate shoaling and breaking effectively, pass through the breaking phase, and continue into shallow water. http://ijaers.com/detail/time-series-water-wave-modeling-using-a-modified-euler-momentum-conservation-equation-and-a-momentum-equilibrium-equation/ Syawaluddin Hutahaean http://ijaers.com/uploads/issue_files/2IJAERS-1220251-TimeSeries.pdf The aim of this study was to investigate age and gender as a demographic factors that correlates students’ performance in computer programming in Colleges of Education. The study was carried out in Colleges of Education. Two objectives, two research questions and two hypotheses were formulated to guide the study. The study adopted correlational survey research design. The study was carried out using government owned Colleges of Education. The population for the study was forty nine (49) computer education students (final year) from the two (2) government owned Colleges of Education in Enugu State, Nigeria. The entire population was studied due to the fact that it is manageable. Hence, total population sampling technique was adopted. The instrument that was used for the study was student’s result scores and a structured questionnaire titled “Age and Gender as a Demographic Factors that Correlates of Student’s Performance in Computer Programming (AGDFCSPCP) questionnaire”. The research instrument was subjected to face validation by three experts, two experts in the Department of Computer & Robotics Education and one from Measurement and Evaluation unit, all from University of Nigeria, Nsukka. The internal consistency of the questionnaire was determined using Cronbach’s Alpha reliability test which yielded co-efficient of 0.98 and 0.97 for clusters 1 and 2 respectively and 0.98 for the entire instrument. The instrument for data collection were administered by the researcher and two research assistants. The data collected was analyzed using Pearson Product Moment Correlation Coefficient to answer the research questions. The null hypotheses were tested using One Way Analysis of Variance (ANOVA) at .05 level of significance. The findings from the study revealed a very weak relationship among age, gender, and performance of computer education students’ in computer programming. In addition, the findings on hypothesis tested revealed that there was no statistically significant relationship among computer education students’ age, gender and their performances in computer programming course. It was therefore, recommended among others that since demographic factors don't differentiate performance, the effectiveness of teaching methods and curriculum content becomes paramount. The researcher suggested that the study should be replicated in other states of our country to investigate demographic factors as correlate students’ performance in computer programming in Colleges of Education. It is recommend that, invest in training for computer programming instructors on effective pedagogical approaches, such as problem-based learning, project-based learning, collaborative coding, and active learning strategies. Regularly review and update the computer programming curriculum to ensure it is relevant, engaging, and aligned with industry needs. http://ijaers.com/detail/age-and-gender-as-a-demographic-factors-that-correlates-students-performance-in-computer-programming-in-colleges-of-education-in-enugu-state-nigeria/ Samuel Okechukwu Nnaji, Prof. Nnenna. E. Ibezim, Nneamaka Felicia Anyalebechi, Maduabuchi Bartholomew Ikezue http://ijaers.com/uploads/issue_files/3IJAERS-1120257-Ageand.pdf In contemporary petrochemical manufacturing, the identification of defects in a substantial quantity of bearings is frequently a necessity. Conventional methods of detection, namely manual inspection and acoustic emission detection, are often plagued by deficiencies in terms of efficiency and precision. The proposed methodology integrates acoustic emission technology with the open-source deep learning algorithm YOLO-V11, facilitating rapid detection of bearing faults. Initially, five types of bearings of the same model but different varieties are selected and installed on the same shaft segment, which is then connected to an acoustic emission detection device. Acoustic emission signals are obtained for each type of bearing according to the different types of bearing fault. These signals are then visualised in two dimensions to generate vibration images, which serve as input for the model and are used to train the YOLO-V11 model. The experimental findings demonstrate that the prediction accuracy and recall rate for various defects generally exceed 80%, thus substantiating the efficacy of the proposed method for industrial production in the diagnosis and classification of bearing defects. http://ijaers.com/detail/a-classification-method-for-bearing-surface-defects-based-on-acoustic-emission-technology-and-the-yolo-v11-algorithm/ Xin Yu Guo, Liu Yi Yu, Yi Chen, Yan Zuo Chang http://ijaers.com/uploads/issue_files/4IJAERS-1020257-Aclassification.pdf Cervical cancer remains a major health concern among women worldwide, emphasizing the need for accurate and efficient diagnostic approaches. Deep learning has shown strong potential in automating medical image analysis and improving diagnostic reliability. This study aims to evaluate and compare the performance of two advanced deep learning models YOLO-v8 and Inception-v3 for the multi-class classification of cervical cancer histopathology images. A curated dataset of 225 histopathology images representing three cervical cancer subtypes (squamous cell carcinoma, adenocarcinoma, and adenosquamous carcinoma) was preprocessed using standardized resizing, normalization, and augmentation techniques. Both models were trained with optimized hyperparameters and evaluated using accuracy, precision, recall, F1-score, confusion matrices, and learning curve analysis to determine their effectiveness and generalization capability. The proposed workflow incorporates robust preprocessing, extensive augmentation, and systematic hyperparameter tuning to enhance model performance. YOLO-v8 leverages an efficient unified architecture for high-speed feature extraction, while Inception-v3 utilizes multi-scale convolutional processing to capture fine-grained morphological patterns within histopathology images. YOLO-v8 achieved an accuracy of 99.8% and Inception-v3 achieved 99.4%, demonstrating strong discriminative ability and reliable classification across all cancer subtypes. These results highlight the potential of deep learning models as effective tools for automated cervical cancer diagnosis. Despite the limited dataset size, the study provides a solid performance benchmark and establishes a foundation for future work incorporating larger datasets and multimodal diagnostic frameworks. http://ijaers.com/detail/deep-learning-based-histopathological-classification-of-cervical-cancer-using-yolo-v8-and-inception-v3-a-comparative-performance-study/ Usman Idris Ismail, Joshua C Shawulu, Mustapha Ismail, Albashir Ahmad, Sulaiman Yusuf Ali, Nuhu Abdulalim Muhammad, Saadatu Ali Jijji http://ijaers.com/uploads/issue_files/5IJAERS-1220254-DeepLearning.pdf Introduction: Total hip and knee arthroplasty is associated with significant perioperative blood loss, increasing the risk of anemia, transfusion, and prolonged hospitalization. Tranexamic acid (TXA) is widely used to minimize surgical bleeding, but the optimal route of administration remains under debate, particularly between oral and intravenous forms. Objective: To compare the efficacy of oral versus intravenous tranexamic acid regarding total blood loss and length of hospital stay in patients undergoing total hip and knee arthroplasty. Methods: This is a narrative literature review. The search was conducted in the PubMed/MEDLINE and SciELO databases using the descriptors “acid tranexamic,” “intravenous,” “oral,” and “total knee/hip arthroplasty,” combined with the Boolean operators AND and OR. Randomized clinical trials and meta-analyses published in Portuguese, English, or Spanish from 2020 onwards that directly compared oral and intravenous TXA in total arthroplasty were included. Results: The findings indicate that oral and intravenous TXA have equivalent efficacy in reducing total blood loss. No significant differences were observed in hospital stay duration or complication rates between the administration routes. The oral route demonstrated logistical advantages and lower cost. Conclusion: Oral tranexamic acid is as effective and safe as the intravenous route in hip and knee arthroplasty, representing a viable, accessible alternative with potential to reduce hospital costs. http://ijaers.com/detail/comparison-between-oral-and-intravenous-tranexamic-acid-in-total-hip-and-knee-arthroplasty/ Gislaine dos Santos Rodrigues Vieira, Amom Mendes Fernandes Rocha, Clovison Carvalho Jardim, Fabiane Montagna, Felipe Westphal Goetten, Idevaldo Galvão Costa Filho, João Guilherme Ruiz Ferreira, Fernando Costenaro http://ijaers.com/uploads/issue_files/6IJAERS-1220252-Comparison.pdf This study investigates how digitalization and sustainability are two enablers in achieving operational excellence in supply chain management and procurement in the GCC region. The study is of a quantitative study conducted through secondary data analysis, investigates particular technological innovations (i.e. artificial intelligence (AI), blockchain, automation, and data analytics), and sustainability practices (i.e. green sourcing, waste management, and ethical purchasing practices) which may occur within the GCC region, which results in improved outcomes. The study finds that digital transformation provides considerable amounts of transparency, efficiency, and the ability to make accurate decisions, while sustainable practices demonstrate increased resilience and trust from stakeholders. Furthermore, the results of digital transformation suggest that the UAE and Saudi Arabia are comparatively more mature on the basis of policy, investment, and sustainability maturity than Oman and Bahrain. The tested relationships that were both positive and significant included (1) digital transformation and operational effectiveness (r = 0.72); (2) sustainability and procurement capability (r = 0.68); and when both constructs were analyzed together, explained as much as 60 percent of the variance of operational excellence within the GCC. This study reports that incorporating sustainable practices into an organization's core strategies in addition to digital transformation will improve supply chain agility and performance and result in the ability to achieve and contribute toward world-class sustainability goals. http://ijaers.com/detail/integrating-digital-transformation-and-sustainability-for-operational-excellence-in-procurement-and-supply-chain-management-an-empirical-framework-for-the-middle-east-region/ Samir Ali Syed http://ijaers.com/uploads/issue_files/7IJAERS-1120256-Integrating.pdf Diesel generators experience continuous vibration and fluctuating forces during operation, which are transferred to the supporting canopy frame [1],[7]. If not structurally optimised, such vibration may trigger deformation, resonance, or long-term fatigue failures [1],[6],[11]. This study investigates the vibratory behaviour of a heavy-duty genset canopy frame through modal, harmonic and dynamic finite element analyses [3],[4]. A 3D structural model was developed in SOLIDWORKS and examined under multiple frequency-dependent loading scenarios [7]. Natural frequencies and mode shapes were extracted through modal analysis, while harmonic simulations assessed deformation under sinusoidal excitation typical of diesel engines [1],[9]. Additional dynamic simulations evaluated stability under varying operational frequencies [11],[12]. Results show that the frame’s natural frequencies do not coincide with the standard excitation range of generator engines, eliminating resonance risk [9],[11]. Harmonic response curves indicate low displacement amplitudes, confirming the structural rigidity of the canopy [2],[7]. The study concludes that the existing frame configuration demonstrates robust dynamic performance, suitable for industrial generator applications [10],[12]. http://ijaers.com/detail/modal-harmonic-and-dynamic-behaviour-evaluation-of-a-diesel-generator-canopy-frame-using-finite-element-techniques/ Mr. Govind Rajabhau Bhosle, Dr. N. A. Rawabawale, Dr. B. S. Allurkar, Prof. S. M. Nagure http://ijaers.com/uploads/issue_files/8IJAERS-1220253-Modal.pdf