INTRODUCTION: A range of tools and technologies are at disposal for the purpose of defect detection. These include but are not limited to sensors, Statistical Process Control (SPC) software, Artificial Intelligence (AI) and machine learning (ML) algorithms, X-ray systems, ultrasound systems, and eddy current systems. OBJECTIVES: The determination of the suitable instrument or combination of instruments is contingent upon the precise production procedure and the category of flaw being identified. In certain cases, defects may necessitate real-time monitoring and analysis through the use of sensors and SPC software, whereas more comprehensive analysis may be required for other defects through the utilization of X-ray or ultrasound systems. METHODS: The utilization of AI and ML algorithms has gained significant traction in the realm of defect detection. This is attributed to their ability to process vast amounts of data and discern patterns that may have otherwise eluded detection. The aforementioned tools have the capability to anticipate potential flaws and implement pre-emptive measures to avert their occurrence. RESULTS: The detection of defects in automated manufacturing systems is a continuous process that necessitates meticulous observation and examination to guarantee prompt and effective identification and resolution of defects. CONCLUSION: The utilization of suitable tools and technologies is imperative for manufacturers to guarantee optimal production quality and operational success.
Copper electrodeposition by electrorefining process in acidic sulfate media contains 40 g/l of cupric ions and 160 g/l of sulfuric acid was achieved to study the influence of the operating parameters on cathode purity, surface morphology, deposition rate, current efficiency and power consumption. These operating parameters and there ranges are: current density 200, 300 and 400 A/m2, electrolyte temperature 35, 50 and 65 oC, electrodes spacing 15, 30 and 45 mm and electrolyte residence time 6, 4 and 2 h were utilized. XRF, SEM and EDX analyses were attained to clarify the properties of the produced cathode.
Objective: Evaluation of women's knowledge about risk factors and early detection of breast cancer at
Ibn Rushd college of education in Baghdad University.
Methodology: The study sample included (184) women in the Ibn Rushd College / University of
Baghdad, whose age ranged between (17-58) years. Data were collected through a structured
questionnaire prepared by the National Cancer Research Center which were answered during a scientific
symposium about breast cancer. The score was calculated by correcting the results of the answer, giving
one score for each correct answer and then estimating the level of knowledge and inputting all data in a
statistical program.
Results: The results showed limited level of women's
Introduction and Aim: Pseudomonas aeruginosa is a nosocomial infection with an ability to develop high levels of antibiotic resistance. The efflux pump system is one of the mechanisms that is linked to multidrug resistance in P. aeruginosa. In this study, we employed siRNA loaded on gold nanoparticles against the MexA efflux pump gene to decrease the MexA gene expression in P. aeruginosa and estimated antibiotic resistance after gene silencing. Materials and Methods: This study examined four strains of P. aeruginosa isolated from patients in various hospitals in Baghdad. Bacteria isolated were identified by biochemical tests and Vitek compact 2 system. Single-stranded siRNA (33bp) designed in this study was loaded onto gold
... Show MoreEvolutionary algorithms are better than heuristic algorithms at finding protein complexes in protein-protein interaction networks (PPINs). Many of these algorithms depend on their standard frameworks, which are based on topology. Further, many of these algorithms have been exclusively examined on networks with only reliable interaction data. The main objective of this paper is to extend the design of the canonical and topological-based evolutionary algorithms suggested in the literature to cope with noisy PPINs. The design of the evolutionary algorithm is extended based on the functional domain of the proteins rather than on the topological domain of the PPIN. The gene ontology annotation in each molecular function, biological proce
... Show MoreBy definition, the detection of protein complexes that form protein-protein interaction networks (PPINs) is an NP-hard problem. Evolutionary algorithms (EAs), as global search methods, are proven in the literature to be more successful than greedy methods in detecting protein complexes. However, the design of most of these EA-based approaches relies on the topological information of the proteins in the PPIN. Biological information, as a key resource for molecular profiles, on the other hand, acquired a little interest in the design of the components in these EA-based methods. The main aim of this paper is to redesign two operators in the EA based on the functional domain rather than the graph topological domain. The perturb
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