Meta-heuristic algorithms have been significantly applied in addressing various real-world prediction problem, including in disease prediction. Having a reliable disease prediction model benefits many parties in providing proper preparation for prevention purposes. Hence, the number of cases can be reduced. In this study, a relatively new meta-heuristic algorithm namely Barnacle Mating Optimizer (BMO) is proposed for short term dengue outbreak prediction. The BMO prediction model is realized over real dengue cases data recorded in weekly frequency from Malaysia. In addition, meteorological data sets were also been employed as input. For evaluation purposes, error analysis relative to Mean Absolute Percentage Error (MAPE), Mean Square Error (MSE), and Mean Absolute Deviation (MAD) were employed to validate the performance of the identified algorithms which includes the comparison between BMO against Moth Flame Optimizer (MFO) and Grey Wolf Optimizer (GWO) algorithms. Upon simulation, the superiority is in favour to BMO by producing lower error rates.
This aim of this study is to assess the Tigris River sediments and utilize them as a new abrasive for the preparation of polished surface of magnetite ore to be studied under reflected light ore microscope. Such polishing process was tested using 250, 125, 71, 45, 25 and 18μm grain sizes of the river sediments. For the completion of the polishing and to obtain a glossy perfect polished surface, the 7 and 2.5 μm sized standard diamond pastes were used. After each polishing stage, the reflectance and roughness of these surfaces were measured as an evaluation step for the polishing efficiency. The reflectance values (R%) of the magnetite surface were found to be reversely proportioned to the abrasive grain size; while the surface roughnes
... Show MoreThe cozy partitions achieved more creativity by emerging with many topics in representation theory and mathematical relations. We find the precise number of cozy tableaux in the case with any number of and . Specifically, we use the MATLAB programme that coincided with the mathematical solution in giving precision to these numbers in this case.
AIM: To analyse our experiences in the management of traumatic retroperitoneal hematoma (RPH), highlighting the various challenges faced and to report on the outcome of these patients. METHODS: From May 2014 to May 2017, all patients with traumatic RPH who underwent surgical treatment were retrospectively analysed. The kind of injury, intraoperative findings, sites of hematoma, postoperative morbidity and the overall outcomes were recorded. RESULTS: Ninety-six patients; 53 with blunt trauma and 43 with penetrating injury, were included in this study. The centre-medial hematoma was observed in 24 (25%) patients, lateral hematoma in 46 (47.9%) patients, pelvic hematoma in 19 (19.8%) patients, and multiple zone hematomas in
... Show MoreBackground: dorsal spine intervertebral disc prolapse (IVDP) not a very common entity compared with cervical & lumbar region usually treated surgically.
Patients & method: 22 patients studied in the specialized surgical hospital neurosurgical department from Jan 2002 till Jan. 2006. the study included age, gender, cases. clinical features, diagnoses & surgical management.
Results: 22 patients were studied 76% of the patients are at the age of 30-60 with slight male predominance, all diagnosed by MRI & or CT scan, all managed surgically by laminectomy the results are compared with other studies.
Conclusion: posterior thoracic laminectomy at the dorsal region is a safe, simple procedure with good res
... Show MoreDiabetes is one of the increasing chronic diseases, affecting millions of people around the earth. Diabetes diagnosis, its prediction, proper cure, and management are compulsory. Machine learning-based prediction techniques for diabetes data analysis can help in the early detection and prediction of the disease and its consequences such as hypo/hyperglycemia. In this paper, we explored the diabetes dataset collected from the medical records of one thousand Iraqi patients. We applied three classifiers, the multilayer perceptron, the KNN and the Random Forest. We involved two experiments: the first experiment used all 12 features of the dataset. The Random Forest outperforms others with 98.8% accuracy. The second experiment used only five att
... Show MoreBackground: P53 is an important tumor marker in many malignancies, the P53 gene is a tumor suppressor gene that plays a key role in the regulation of the cell cycle.
PDBN Rashid, International Journal of Professional Studies, 2023
At present, the ability to promote national economy by adjusting to political, economic, and technological variables is one of the largest challenges faced by organization productivity. This challenge prompts changes in structure and line productivity, given that cash has not been invested. Thus, the management searches for investment opportunities that have achieved the optimum value of the annual increases in total output value of the production line workers in the laboratory. Therefore, the application of dynamic programming model is adopted in this study by addressing the division of investment expenditures to cope with market-dumping policy and to strive non-stop production at work.
Many economic entities working in multiple industrial fields suffer fromlow techniques in using modern administrative means in their works. The mostused tool in measuring required procedures is to adopt and use quality costs. inspite of complications and bronchial of operations in construction projects, Theresearcher was able to find a structure to quality costs according to traditionclassification (prevention, Appraisal, failure) which enables the calculation ofthese costs and then analyze results and setting standards which can beimplemented in evaluating strategic performance for targeted project. and theforge research in theoretical fly to quality and costs concerning it inconstruction section , as well as strategically performance a
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