Sparse sufficient dimension reduction with heteroscedasticity

Heteroscedasticity often appears in the high-dimensional data analysis. In order to achieve a sparse dimension reduction direction for high-dimensional data with heteroscedasticity, we propose a new sparse sufficient dimension reduction method, called Lasso-PQR. From the candidate matrix derived from the principal quantile regression (PQR) method, we construct a new artificial response variable which is made up from top eigenvectors of the candidate matrix. Then we apply a Lasso regression to obtain sparse dimension reduction directions. While for the “large [Formula: see text] small [Formula: see text]” case that [Formula: see text], we use principal projection to solve the dimension reduction problem in a lower-dimensional subspace and projection back to the original dimension reduction problem. Theoretical properties of the methodology are established. Compared with several existing methods in the simulations and real data analysis, we demonstrate the advantages of our method in the high dimension data with heteroscedasticity.

A Multi-Objective Approach for Test Suite Reduction During Testing of Web Applications

During the development and maintenance phases of evolving software, new test cases would be needed for the verification of the accuracy of the modifications as well as for new functionalities leading to an increase in the size of the test suite. Various related objectives are to be kept in mind while reducing the original test suite by removing redundancy and generating a practical representative set of the unique test cases, some of which may need to be maximized and the remaining ones minimized. This paper presents a multi-objective approach for the test suite reduction problem in which one objective is to be minimized and the remaining two maximized. In this study, experiments were performed on diverse versions of four web applications. Various state-of-the-art algorithms and their updated versions were compared with non-dominated sorting genetic algorithm-II (NSGA-II) for performance evaluation. Based on experimental findings, it was concluded that NSGA-II outperforms all other algorithms; moreover, the algorithm attempts to satisfy all the objectives without compromising coverage.

Acts that Kill and Acts that Do Not

In response to recent debates on the need to abandon the Dead Donor Rule (DDR) to facilitate vital-organ transplantation, I claim that, through a detailed philosophical analysis of the Uniform Determination of Death Act (UDDA) and the DDR, some acts that seem to violate DDR in fact do not, thus DDR can be upheld. The paper consists of two parts. First, standard apparatuses of the philosophy of language, such as sense, referent, truth condition, and definite description are employed to show that there exists an internally consistent and coherent interpretation of UDDA which resolves the Reduction Problem and the Ambiguity Problem that allegedly threaten the UDDA framework, and as a corollary, the practice of Donation after the Circulatory Determination of Death (DCDD) does not violate DDR. Second, an interpretation of the DDR, termed ‘No Hastening Death Rule’ (NHDR), is formulated so that, given that autonomy and non-maleficence principles are observed, the waiting time for organ procurement can be further shortened without DDR being violated.

Stability Analysis of a Weathered-Basalt Soil Slope Using the Double Strength Reduction Method

Slope stability analysis of the mountain landforms in southwestern China has always been an important problem in the field of geotechnical engineering. The large landslide occurs in Jichang Town, Shuicheng County, Guizhou Province, China, on July 23, 2019, as the engineering background. Based on the nonlinear relationship between the soil water content, cohesion, and friction angle measured in laboratory tests, the finite element reduction problem of the double-strength parameters is only transformed into a reduction problem of water content. Then, based on the redevelopment platform in the ABAQUS finite element software, a user subroutine to specify predefined field variables (UFIELD) was written to numerically simulate the stability of the Jichang slope before the landslide. The results show that the Jichang slope is mainly composed of basalt-weathered red clay mixed with gravel of various particle sizes. The underlying bedrock is primarily the Permian Emeishan basalt with strong-to-weak weathering and a small amount of argillaceous siltstone. Due to the increase in water content caused by heavy rainfall, the strength of the soil decreased continuously. Once the critical stress state of the slope was exceeded, the plastic sliding block slipped at high speed over a long distance along the rock-soil layer interface, and along the way, it scraped out and carried away the original loose topsoil and gravel blocks, which finally piled up in the form of a debris flow. In addition, the attenuations of the cohesion and friction angle are different. When the water content is less than 25%, the reduction coefficient of the friction angle is greater than the cohesion, which shows that the attenuation of the friction angle is stronger than that of the cohesion. The opposite is true when the water content is greater than 25%. The new method of double-strength finite element reduction presented in this paper is reasonable and feasible and is more in line with the actual situation of weathered-basalt soil slope instability in heavy rainfall areas.

The Relationship between the Unicost Set Covering Problem and the Attribute Reduction Problem in Rough Set Theory

The unicost set covering problem and the attribute reduction problem are NP-complete problems. In this paper, the relationship between these two problems are discussed. Based on the transformability between attribute reductions and minimal solutions in unicost set covering models, two methods are provided. One is to induce an information table from a given unicost set covering model. With no doubt, it shows that the unicost set covering problem can be investigated by rough set theory. The other is to induce a unicost set covering model from a given information table. Similarly, it shows that the attribute reduction problem can be studied by set covering theory. As an application of the proposed theoretical results, a rough set heuristic algorithm is presented for the unicost set covering problem.

Reducing Passenger Delays by Rolling Stock Rescheduling

Delays are a major nuisance to railway passengers. The extent to which a delay propagates, and thus affects the passengers, is influenced by the assignment of rolling stock. We propose to reschedule the rolling stock in such a way that the passenger delay is minimized and such that objectives on passenger comfort and operational efficiency are taken into account. We refer to this problem as the passenger delay reduction problem. We propose two models for this problem, which are based on two dominant streams of literature for the traditional rolling stock rescheduling problem. The first model is an arc formulation of the problem, whereas the second model is a path formulation. We test the effectiveness of these models on instances from Netherlands Railways (Nederlandse Spoorwegen). The results show that the rescheduling of rolling stock can significantly decrease passenger delays in the system. Especially, allowing flexibility in the assignment of rolling stock at terminal stations turns out to be effective in reducing the delays. Moreover, we show that the arc formulation–based model performs best in finding high-quality solutions within the limited time that is available in the rescheduling phase.