The Smooth-Lasso and other ℓ1+ℓ2\ell_1+\ell_2-penalized methods

We consider a linear regression problem in a high dimensional setting where the number of covariates $p$ can be much larger than the sample size $n$. In such a situation, one often assumes sparsity of the regression vector, \textit i.e., the regression vector contains many zero components. We propose a Lasso-type estimator $\hat{\beta}^{Quad}$ (where '$Quad$' stands for quadratic) which is based on two penalty terms. The first one is the $\ell_1$ norm of the regression coefficients used to exploit the sparsity of the regression as done by the Lasso estimator, whereas the second is a quadratic penalty term introduced to capture some additional information on the setting of the problem. We detail two special cases: the Elastic-Net $\hat{\beta}^{EN}$, which deals with sparse problems where correlations between variables may exist; and the Smooth-Lasso $\hat{\beta}^{SL}$, which responds to sparse problems where successive regression coefficients are known to vary slowly (in some situations, this can also be interpreted in terms of correlations between successive variables). From a theoretical point of view, we establish variable selection consistency results and show that $\hat{\beta}^{Quad}$ achieves a Sparsity Inequality, \textit i.e., a bound in terms of the number of non-zero components of the 'true' regression vector. These results are provided under a weaker assumption on the Gram matrix than the one used by the Lasso. In some situations this guarantees a significant improvement over the Lasso. Furthermore, a simulation study is conducted and shows that the S-Lasso $\hat{\beta}^{SL}$ performs better than known methods as the Lasso, the Elastic-Net $\hat{\beta}^{EN}$, and the Fused-Lasso with respect to the estimation accuracy. This is especially the case when the regression vector is 'smooth', \textit i.e., when the variations between successive coefficients of the unknown parameter of the regression are small. The study also reveals that the theoretical calibration of the tuning parameters and the one based on 10 fold cross validation imply two S-Lasso solutions with close performance

On Volumes of Permutation Polytopes

This paper focuses on determining the volumes of permutation polytopes associated to cyclic groups, dihedral groups, groups of automorphisms of tree graphs, and Frobenius groups. We do this through the use of triangulations and the calculation of Ehrhart polynomials. We also present results on the theta body hierarchy of various permutation polytopes.Comment: 19 pages, 1 figur

Towards mobile learning deployment in higher learning institutions : a report on the qualitative inquiries conducted in four universities in Tanzania

Over the past two decades, mobile learning (m-learning) has been a purposeful area of research among educational technologists, educators and instructional designers whereby doubts and controversies over its relevancy and applicability have been keenly addressed. This paper explores stakeholders’ perceptions of m-learning deployment in Higher Learning Institutions (HLIs). Spe- cifically, we examine the potential of m-learning for HLIs in Tanzania and the challenges that hinder successful m-learning deployment. We adopt a comparative qualitative case study design in which four HLIs in Tanzania were purposefully selected. The study uses a combination of de- sign science research approach and qualitative methods including grounded theory, document re- views, and observation. The respondents included university lecturers, students and ICT experts, who were selected for the interviews through theoretical sampling. The transcripts were loaded, coded and analyzed in NVIVO software. The results indicate that mobiles (smartphone, tablets, laptops, feature-phones etc.) are widely used in the HLIs. Stakeholders perceive that m-learning deployment is important and useful because it improves the quality of the learning experience. The results further indicate that there are financial, pedagogical, technological, infrastructural, individuals – and policy – related challenges that hinder successful deployment of m-learning in HLIs in Tanzania, such as limited network coverage, some students ́ inability to afford mobiles, lack of qualified staff for preparation of mobile content and administration, gaps in the exist- ing policies, and faulty course design. However, our results show that participants are optimistic about the potential of m-learning in the HLIs of Tanzania. They expect that m-learning will im- prove access to learning resources, teacher-student and student-student interaction without being restricted by time or place. Thus, m-learning is considered to have the potential to address issues of crowded classrooms, expertise, access to learning materials, flexibility of the learners as well as remote connectivity.
 We recommend that HLIs should prioritize m-learning and commit resources to the success of the related projects. We also recommend that the governments and stakeholders provide policy interventions, subsidize mobile technologies, expand network coverage, build capacity within and outside HLIs, and improve digital literacy by integrating ICT education at all levels of education

Pilot evaluation of the Index Based Flood Insurance in Bihar, India: Lessons of experiences

The Government of Bihar (GOB) with the help of Government of India (GOI) introduced and implemented various crop insurance programs, to provide protection against losses caused by fluctuations in the output of a crop from one year to another or from one crop season to another. Traditional agricultural insurances are designed to make compensation to client farmers affected by various disasters and natural calamities based on individual yield losses or damage to crops and livestock (Ahmed, 2013; Swain and Patnaik, 2016). For developing countries like India, with large numbers of smallholder farmers, measuring such individual losses would incur enormous costs for insurance companies. The index-based insurance offers an alternative in which individual assessment is not necessary. Advances in satellite technology and data analysis were integrated to develop index insurance products, which were piloted in different countries throughout the world such as India, Ethiopia, Senegal, and United States. The index insurance products help minimize the high transaction costs and have the potential to expand the reach of insurance policies to rural areas that were previously considered uninsurable (Swain and Patnaik, 2016; Smith and Watts, 2019). The International Water Management Institute (IWMI) has developed an Index-Based Flood Insurance (IBFI) product integrating hi-tech modeling and satellite imagery (Amarnath and Sikka, 2018; Matheswaran et al. 2019). The product was pilot tested among 200 farmers in six villages of the Gaighat Block of Muzaffarpur District, Bihar during the Khariff season, 2017. This report presents the findings of the IBFI ex-post evaluation undertaken in the pilot areas in Muzaffarpur. The findings of this study provide lessons on how index-based insurance schemes can be made more inclusive, and inform any development of a scheme for future upscaling by IWMI. The findings are based on the qualitative assessment made in April 2018 and a household survey conducted in July 2018

FPGA-based implementation of the back-EMF symmetric-threshold-tracking sensorless commutation method for brushless DC-machines

The operation of brushless DC permanent-magnet machines requires information of the rotor position to steer the semiconductor switches of the power-supply module which is commonly referred to as Brushless Commutation. Different sensorless techniques have been proposed to estimate the rotor position using current and voltage measurements of the machine. Detection of the back-electromotive force (EMF) zero-crossing moments is one of the methods most used to achieve sensorless control by predicting the commutation moments. Most of the techniques based on this phenomenon have the inherit disadvantage of an indirect detection of commutation moments. This is the result of the commutation moment occurring 30 electrical degrees after the zero-crossing of the induced back-emf in the unexcited phase. Often, the time difference between the zero crossing of the back-emf and the optimal current commutation is assumed constant. This assumption can be valid for steady-state operation, however a varying time difference should be taken into account during transient operation of the BLDC machine. This uncertainty degrades the performance of the drive during transients. To overcome this problem which improves the performance while keeping the simplicity of the back-emf zero-crossing detection method an enhancement is proposed. The proposed sensorless method operates parameterless in a way it uses none of the brushless dc-machine parameters. In this paper different aspects of experimental implementation of the new method as well as various aspects of the FPGA programming are discussed. Proposed control method is implemented within a Xilinx Spartan 3E XC3S500E board