Minimum entropy density method for the time series analysis

The entropy density is an intuitive and powerful concept to study the complicated nonlinear processes derived from physical systems. We develop the minimum entropy density method (MEDM) to detect the structure scale of a given time series, which is defined as the scale in which the uncertainty is minimized, hence the pattern is revealed most. The MEDM is applied to the financial time series of Standard and Poor’s 500 index from February 1983 to April 2006. Then the temporal behavior of structure scale is obtained and analyzed in relation to the information delivery time and efficient market hypothesis.     

Effect of gamma irradiation on polypropylene yarns under air and water

Journal of Radioanalytical and Nuclear Chemistry - Polypropylene (PP) filters are used for the treatment of radioactive liquid waste containing gamma nuclides such as Co-60, and filter physical and...     

A MAP-modulated fluid flow model with multiple vacations

We consider a MAP-modulated fluid flow queueing model with multiple vacations. As soon as the fluid level reaches zero, the server leaves for repeated vacations of random length V until the server finds any fluid in the system. During the vacation period, fluid arrives from outside according to the MAP (Markovian Arrival Process) and the fluid level increases vertically at the arrival instance. We first derive the vector Laplace–Stieltjes transform (LST) of the fluid level at an arbitrary point of time in steady-state and show that the vector LST is decomposed into two parts, one of which the vector LST of the fluid level at an arbitrary point of time during the idle period. Then we present a recursive moments formula and numerical examples.     

How Preservice Teachers Interpret and Respond to Student Geometric Errors

Recognizing and responding to students' thinking is essential in teaching mathematics, especially when students provide incorrect solutions. This study examined, through a teaching scenario task, elementary preservice teachers' interpretations of and responses to a student's work on a task involving reflective symmetry. Findings revealed that a majority of preservice teachers identified the student's errors from conceptual aspects of reflection rather than from procedural aspects. However, when they responded to the student's errors, preservice teachers tried to cope with them by invoking procedural knowledge. This study also revealed the three types of responses and two different forms of address by preservice teachers to student errors; these categories might provide insight into the difficulties arising in communication between students and teachers.     

Monolayer Co3O4 Inverse Opals as Multifunctional Sensors for Volatile Organic Compounds

Monolayers of periodic porous Co₃O₄ inverse opal (IO) thin films for gas‐sensor applications were prepared by transferring cobalt‐solution‐dipped polystyrene (PS) monolayers onto sensor substrates and subsequent removal of the PS template by heat treatment. Monolayer Co₃O₄ IO thin films having periodic pores (d≈500 nm) showed a high response of 112.9 to 5 ppm C₂H₅OH at 200 °C with low cross‐responses to other interfering gases. Moreover, the selective detection of xylene and methyl benzenes (xylene+toluene) could be achieved simply by tuning the sensor temperature to 250 and 275 °C, respectively, so that multiple gases can be detected with a single chemiresistor. Unprecedentedly high ethanol response and temperature‐modulated control of selectivity with respect to ethanol, xylene, and methyl benzenes were attributed to the highly chemiresistive IO nanoarchitecture and to the tuned catalytic promotion of different gas‐sensing reactions, respectively. These well‐ordered porous nanostructures could have potential in the field of high‐performance gas sensors based on p‐type oxide semiconductors.