Optimized parameter search for large datasets of the regularization parameter and feature selection for ridge regression

In this paper we propose mathematical optimizations to select the optimal regularization parameter for ridge regression using cross-validation. The resulting algorithm is suited for large datasets and the computational cost does not depend on the size of the training set. We extend this algorithm to forward or backward feature selection in which the optimal regularization parameter is selected for each possible feature set. These feature selection algorithms yield solutions with a sparse weight matrix using a quadratic cost on the norm of the weights. A naive approach to optimizing the ridge regression parameter has a computational complexity of the order with the number of applied regularization parameters, the number of folds in the validation set, the number of input features and the number of data samples in the training set. Our implementation has a computational complexity of the order . This computational cost is smaller than that of regression without regularization for large datasets and is independent of the number of applied regularization parameters and the size of the training set. Combined with a feature selection algorithm the algorithm is of complexity and for forward and backward feature selection respectively, with the number of selected features and the number of removed features. This is an order faster than and for the naive implementation, with for large datasets. To show the performance and reduction in computational cost, we apply this technique to train recurrent neural networks using the reservoir computing approach, windowed ridge regression, least-squares support vector machines (LS-SVMs) in primal space using the fixed-size LS-SVM approximation and extreme learning machines

A school-based intervention program in promoting leisure-time physical activity: Trial protocol

Background: Regular participation in moderate-to-vigorous physical activity (MVPA) is important to manage obesity. Physical education (PE) is considered to play an important role in promoting lifelong participation in physical activity (PA) because it provides an existing network where cost-effective interventions can be implemented to produce sustainable change in health behavior. However, the association between compulsory school PA (e.g., PE lessons) and body composition levels has received mixed support in the literature. Therefore, the present study aimed to investigate whether a school-based intervention targeting salient PA benefits and barriers grounded on the theory of planned behavior would promote young people's participation in MVPA during leisure time and reduce body mass index (BMI) of overweight students. Methods/design: A total of 171 students from 3 secondary schools in Singapore underwent the control condition followed by the intervention condition. Both the conditions consisted of PE lessons twice per week over 4 weeks. In the control condition, PE teachers encouraged students to participate in PA during leisure time without providing persuasive message. While in the intervention condition, PE teachers delivered persuasive messages that targeted the salient benefits and barriers associated with PA to the students at the last 5 to 10 min of each PE lesson. PA levels over a week were measured objectively with wrist-mounted GENEActiv Original accelerometers and subjectively with self-reporting questionnaires three times (Baseline, Post 1, and Post 2) in each condition. Student's self-reported PA level was measured using the Leisure-Time Physical Activity Participation Questionnaire and the International Physical Activity Questionnaire, and their attitudes, intentions, subjective norms and perceived behavior control towards leisure-time PA were measured with a questionnaire based on the theory of planned behavior. Furthermore, students' intention, determination and willingness to engage in leisure-time PA were compared with the other activity (e.g., doing homework, shopping). Discussion: This study will provide the evidence on the effectiveness of a cost-effective school-based intervention on reducing BMI of overweight students through promoting sustained participation in leisure-time PA. It will also address methodological issues on the gaps between objective and subjective measures of PA. Trial registration: This trial is registered with the ISRCTN registry (ISRCTN73786157, 26/10/2017, retrospectively registered)

An upper limit on hypertriton production in collisions of Ar(1.76 AGeV)+KCl

A high-statistic data sample of Ar(1.76 AGeV)+KCl events recorded with HADES is used to search for a hypertriton signal. An upper production limit per centrality-triggered event of $1.04$ x $10^{-3}$ on the $3\sigma$ level is derived. Comparing this value with the number of successfully reconstructed $\Lambda$ hyperons allows to determine an upper limit on the ratio $N_{_{\Lambda}^3H}/N_{\Lambda}$, which is confronted with statistical and coalescence-type model calculations

An original look into pulsating heat pipes: Inverse heat conduction approach for assessing the thermal behaviour

A promising solution in the field of passive two-phase heat transfer devices is represented by Pulsating Heat Pipes (PHPs). These relatively new devices, which achieve resounding interest in terms of high heat transfer capability, efficient thermal control, adaptability and low cost, have been extensively studied in the last years by many researchers. Many authors have investigated the heat fluxes at the evaporator and the condenser area only in terms of the mean values. In this work a novel approach to investigate the local heat flux in PHPs is presented and tested: the temperature distributions on the external wall of the PHP acquired with a high-speed and high-resolution infrared camera were used as input data for the inverse heat conduction problem in the wall under a solution approach based on the Tikhonov regularization method. Infrared imaging is performed on a single loop PHP designed with sapphire inserts partially coated with a highly emissive paint, allowing to determine at the same time the external wall temperature and the fluid temperature. Results show that the technique is able to show when heat is transfer from the fluid to the sapphire wall, when the hot fluid is pushed from the evaporator towards the condenser; increasing the wall tube temperature. On the contrary, when a cold fluid flows back from the condenser, the tube releases the heat previously accumulated, thereby decreasing its temperature. This approach allows to analyze the thermal behavior of the device by investigating the direct interconnection between the thermo-fluid dynamic phenomena within the PHP and the local heat flux measurements. The results proposed in this work are a breakthrough for the improvement and validation of both VOF-based DNS simulations, for local physical phenomena, and 1D simulations of the global PHP behaviour

Estimation of the local instantaneous heat flux inside a pulsating heat pipe for space applications

Pulsating Heat Pipes (PHP) are promising and effective passive two-phase heat transfer devices in terms of high heat transfer capability, efficient thermal control, adaptability and low cost and therefore they have been extensively studied in the last years. Many authors have estimated the heat fluxes at the evaporator and at the condenser area only in terms of the average values based on first principle considerations. In the present study the application of an inverse analysis technique to experimental infrared temperature data is proposed to investigate the local convective heat flux for forced convection flow inside these devices along the adiabatic zone. A PHP specifically designed to be hosted on board the heat transfer host of the International Space Station was tested in microgravity during the 67th Parabolic Flight Campaign organized by the European Space Agency. The device consists of an aluminium tube closed in a loop with 14 turns in the evaporator section, 3 mm inner diameter, half filled with FC-72 fluid. The external temperatures of the device are measured in the adiabatic zone with a high-speed infrared camera (50 Hz, 1280x1024 pixels). The images are thereafter post-processed and adopted as input data for the solution of the inverse heat conduction problem in the pipe wall (Tikhonov regularisation method) to extrapolate time-varying local heat fluxes on the tube internal surface in contact with the fluid