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Applications of reliability theory include the assessment of system and equipment reliability, failure analysis, and forecasting. Technological failures and operator errors are assessed to help improve safety and optimize operational processes.

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Probabilistic modeling of meteorological extremes, climate change impacts, and rare events is performed using advanced statistical analysis, extreme value theory, and data integration methods.

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Professional dosimetry services for radiation therapy and diagnostics, including precise measurements, treatment plan verification, quality assurance, and expert consulting to ensure safe and effective patient irradiation.

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We develop and characterize radiation-sensitive dosimetric gels and indicators, including polymer structure fabrication, composition optimization, and performance evaluation for medical, industrial, and research applications.

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Risk and uncertainty analysis helps assess system security, model sensitivity, and data uncertainty. This service allows you to identify risk scenarios, reduce their likelihood, and make effective, data-driven decisions.

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We manufacture customized dosimetric phantoms, boluses, and immobilization devices using 3D printing and patient imaging data to ensure precise dose control and reliable radiation treatment.

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We develop and test protective materials and shielding solutions against mixed radiation and provide consulting on safe facility and structural design for medical, industrial, and research applications.

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We perform radiation safety assessments, dose measurements, and risk analysis, deliver accredited training, and provide expert consulting to ensure compliance and safe operation with radiation sources.

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AI, data analytics, and data science services, including task automation, predictive modeling, natural language processing, computer vision, recommendation systems, big data analysis, optimization, risk and fraud detection, and the creation of customized solutions, are provided.

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Smart information integration tools are being developed and applied for the synthesis of data from different sources, the aggregation of expert knowledge, and the automated modeling of information flows.

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Analysis of the uncertainty and sensitivity of modeling results helps to assess the accuracy of models, identify parameters that influence results, and define the limits of forecast reliability for more accurate risk assessment and better decision-making.

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Failure and longevity data are analyzed, and system reliability, uncertainty, and sensitivity of results are evaluated. This helps identify risk factors, predict failures more accurately, and optimize maintenance and operational decisions.