Application of MARS for the Construction of Nonparametric Models

2000 Mathematics Subject Classification: 62G08, 62P30.This paper presents the main features of the relatively new statistical technique called Multivariate Adaptive Regression Splines (MARS) and the corresponding software product. The MARS method is designed for statistical analysis of data, when standard parametric modeling by multiple regression or logistic regression methods is not applicable. A case study from the area of laser technology, especially for modeling of UV Cu+ Ne-CuBr laser is performed. The obtained results are in a good agreement with practical issues. It is shown that the constructed nonparametric MARS models can be applied in estimation and prediction of current and future experiments in order to improve the output laser power.This paper is partially supported by projects VU-MI-205, NSF of the Bulgarian Ministry of Education, Youth and Science and RS09–FMI–013, ISM-4 of NPD, Plovdiv University “Paisii Hilendarski”

Mathematical Modeling and Simulation of Radial Temperature Profile of Strontium Bromide Lasers

For metal and metal halide vapor lasers excited by high frequency pulsed discharge, the thermal effect mainly caused by the radial temperature distribution is of considerable importance for stable laser operation and improvement of laser output characteristics. A short survey of the obtained analytical and numerical-analytical mathematical models of the temperature profile in a high-powered He-SrBr2 laser is presented. The models are described by the steady-state heat conduction equation with mixed type nonlinear boundary conditions for the arbitrary form of the volume power density. A complete model of radial heat flow between the two tubes is established for precise calculating the inner wall temperature. The models are applied for simulating temperature profiles for newly designed laser. The author’s software prototype LasSim is used for carrying out the mathematical models and simulations

Using the Business Process Execution Language for Managing Scientific Processes

This paper describes the use of the Business Process Execution Language for Web Services (BPEL4WS/BPEL) for managing scientific workflows. This work is result of our attempt to adopt Service Oriented Architecture in order to perform Web services – based simulation of metal vapor lasers. Scientific workflows can be more demanding in their requirements than business processes. In the context of addressing these requirements, the features of the BPEL4WS specification are discussed, which is widely regarded as the de-facto standard for orchestrating Web services for business workflows. A typical use case of calculation the electric field potential and intensity distributions is discussed as an example of building a BPEL process to perform distributed simulation constructed by loosely-coupled services

Stress and health behavior in university setting

The research of stress sources, overall strain and health behaviour identifies differences in sex, income and accommodation conditions. The main stress factors for students are the social relationships, isolation and communication, studies, health, social environment and financial status. The amount of income increases the stress according to all studied sources, excluding the isolation and communication. Women tend to experience more overall strain and stress in result of their studies, health conditions and social environment then men. Sexual differences are observed in health behavior – men are more likely to go for sports and drink alcohol, while women tend to smoke more and are more considerable of their healthy nutrition. The risky behavior related to alcohol and drug use is directly influenced by the accommodation conditions. Исследованы источники стресса, общую напряженность и поведение здоровья у студентов, а также установленны разницы в зависимости пола, доходов и условия жилья. Выявлены основные факторы проявления стресса у студентов: социальные взаимоотношения, учеба, комуникация и изолирование, здоровье и условия среды, финансовое положение. Размер доходов повишает стресса всем исследованным факторам с исключением комуникации и изолирования. Женщины испитывают больше общую напряженность и стресс учебы и здоровья в условиях среды чем мужчины. Существуют половые разницы в отношение поведения здоровья – мужчины больше занимаются спортом, но и чаще употребляют алкоголь, а женщины курят больше, но и придают большую значимостъ здоровой пище. Поведение риска, связанное с употреблением алкоголя и наркотиков зависимо от условий жилья.Изследването е част от кроснационално изследване „Cross-national students health survey (CNSHS, 2005–2010)“ с участници Р. Миколайчик, В. Найденова, С. Майер (Университет Билефелд), Сн. Илиева (Софийски университет), У. Дуджяк (Университет Люблин)

Modeling of Output Characteristics of a UV Cu+ Ne-CuBr Laser

This paper examines experiment data for a Ne-CuBr UV copper ion laser excited by longitudinal pulsed discharge emitting in multiline regime. The flexible multivariate adaptive regression splines (MARSs) method has been used to develop nonparametric regression models describing the laser output power and service life of the devices. The models have been constructed as explicit functions of 9 basic input laser characteristics. The obtained models account for local nonlinearities of the relationships within the various multivariate subregions. The built best MARS models account for over 98% of data. The models are used to estimate the investigated output laser characteristics of existing UV lasers. The capabilities for using the models in predicting existing and future experiments have been demonstrated. Specific analyses have been presented comparing the models with actual experiments. The obtained results are applicable for guiding and planning the engineering experiment. The modeling methodology can be applied for a wide range of similar lasers and laser devices

Application of the Classification and Regression Trees for Modeling the Laser Output Power of a Copper Bromide Vapor Laser

This study examines the available experiment data for a copper bromide vapor laser (CuBr laser), emitting in the visible spectrum at 2 wavelengths—510.6 and 578.2 nm. Laser output power is estimated based on 10 independent input parameters. The CART method is used to build a binary regression tree of solutions with respect to output power. In the case of a linear model, an approximation of 98% has been achieved and 99% for the model of interactions between predictors up to the the second order with an relative error under 5%. The resulting CART tree takes into account which input quantities influence the formation of classification groups and in what manner. This makes it possible to estimate which ones are significant from an engineering point of view for the development and operation of the considered type of lasers, thus assisting in the design and improvement of laser technology

Modeling of the Radial Heat Flow and Cooling Processes in a Deep Ultraviolet Cu

An improved theoretical model of the gas temperature profile in the cross-section of an ultraviolet copper ion excited copper bromide laser is developed. The model is based on the solution of the one-dimensional heat conduction equation subject to special nonlinear boundary conditions, describing the heat interaction between the laser tube and its surroundings. It takes into account the nonuniform distribution of the volume power density along with the radius of the laser tube. The problem is reduced to the boundary value problem of the first kind. An explicit solution of this model is obtained. The model is applied for the evaluation of the gas temperature profiles of the laser in the conditions of free and forced air-cooling. Comparison with other simple models assumed constant volume power density is made. In particular, a simple expression for calculating the average gas temperature is found

Probing shells against buckling: a non-destructive technique for laboratory testing

This paper addresses testing of compressed structures, such as shells, that exhibit catastrophic buckling and notorious imperfection sensitivity. The central concept is the probing of a loaded structural specimen by a controlled lateral displacement to gain quantitative insight into its buckling behaviour and to measure the energy barrier against buckling. This can provide design information about a structure's stiffness and robustness against buckling in terms of energy and force landscapes. Developments in this area are relatively new but have proceeded rapidly with encouraging progress. Recent experimental tests on uniformly compressed spherical shells, and axially loaded cylinders, show excellent agreement with theoretical solutions. The probing technique could be a valuable experimental procedure for testing prototype structures, but before it can be used a range of potential problems must be examined and solved. The probing response is highly nonlinear and a variety of complications can occur. Here, we make a careful assessment of unexpected limit points and bifurcations, that could accompany probing, causing complications and possibly even collapse of a test specimen. First, a limit point in the probe displacement (associated with a cusp instability and fold) can result in dynamic buckling as probing progresses, as demonstrated in the buckling of a spherical shell under volume control. Second, various types of bifurcations which can occur on the probing path which result in the probing response becoming unstable are also discussed. To overcome these problems, we outline the extra controls over the entire structure that may be needed to stabilize the response.Comment: as accepted in International Journal of Bifurcation and Chaos (18 pages

Data Study Group Final Report: Roche

Data Study Groups are week-long events at The Alan Turing Institute bringing together some of the country’s top talent from data science, artificial intelligence, and wider fields, to analyse real-world data science challenges. Roche: Personalised lung cancer treatment modelling using electronic health records and genomics Cancer immunotherapy (CIT) is a promising new type of cancer treatment that uses the patient’s own immune system to fight cancer cells. CIT drugs work to stop the cancer cells from turning off the immune system’s T-cells by inhibiting the PD-L1 produced by the tumour cells (PD-L1 is a protein that binds to PD-1 receptors on T-cells and prevents the immune system from attacking the cancer cells). CIT is currently being used to treat patients with non-small cell lung cancer (NSCLC) for whom chemotherapy or other drugs have failed. CIT is also be-ing used as part of the first-line treatment in patients with advanced NSCLC (aNSCLC - stage III and higher). Theoretically, patients with high PD-L1 ex-pression levels are more likely to respond well to CIT; however, in practice, patient outcomes vary considerably. In this data study group, we investigated different approaches for predicting survival time for patients treated with CIT as first line of treatment, using both electronic health records and tumour genomic data. We also investigated the causal effects of CIT vs other oncology treatments, and studied treatment heterogeneity. The results contribute to identifying patients who are most likely to benefit from CIT