Solving the irregular strip packing problem via guided local search for overlap minimization

The irregular strip-packing problem (ISP) requires a given set of non-convex polygons to be placed without overlap within a rectangular container having a fixed width and a variable length, which is to be minimized. As a core sub-problem to solve ISP, we consider an overlap minimization problem (OMP) whose objective is to place all polygons into a container with given width and length so that the total amount of overlap between polygons is made as small as possible. We propose to use directional penetration depths to measure the amount of overlap between a pair of polygons, and present an efficient algorithm to find a position with the minimum overlap for each polygon when it is translated in a specified direction. Based on this, we develop a local search algorithm for OMP that translates a polygon in horizontal and vertical directions alternately. Then we incorporate it in our algorithm for OMP, which is a variant of the guided local search algorithm. Computational results show that our algorithm improves the best-known values of some well-known benchmark instances.     

A Bayesian solution to the multiple composite hypothesis testing for fault diagnosis in dynamic systems

This paper is concerned with model-based isolation and estimation of additive faults in discrete-time linear Gaussian systems. The isolation problem is stated as a multiple composite hypothesis testing on the innovation sequence of the Kalman filter (KF) that considers the system operating under fault-free conditions. Fault estimation is carried out, after isolating a fault mode, by using the Maximum a Posteriori (MAP) criterion. An explicit solution is presented for both fault isolation and estimation when the parameters of the fault modes are assumed to be realizations of specific random variables (RV).     

On the possible patterns of inputs for block sorting in the Burrows-Wheeler transformation

Block sorting in the Burrows-Wheeler transformation is to sort all of the n circular shifts of a string of length n lexicographically. We introduce a notion called the width of a sequence of n strings of length n and show that the values of widths are very different between the two types of sequences of strings; (1) a sequence of n randomly generated strings of length n, and (2) the sequence of n circular shifts of a randomly generated string of length n.     

Technique for anisotropic extension of organic crystals: application to temperature dependence of electrical resistance

We have developed a technique for the anisotropic extension of fragile molecular crystals. The pressure medium and the instrument, which extends the pressure medium, are both made from epoxy resin. Since the thermal contraction of our instrument is identical to that of the pressure medium, the strain applied to the pressure medium has no temperature dependence down to 2 K. Therefore, the degree of extension applied to the single crystal at low temperatures is uniquely determined from the degree of extension in the pressure medium and thermal contractions of the epoxy resin and the single crystal at ambient pressure. Using this novel instrument, we have measured the temperature dependence of the electrical resistance of metallic, superconducting, and insulating materials. The experimental results are discussed from the viewpoint of the extension (compression) of the lattice constants along the parallel (perpendicular) direction.     

Robust loss functions for boosting

Boosting is known as a gradient descent algorithm over loss functions. It is often pointed out that the typical boosting algorithm, Adaboost, is highly affected by outliers. In this letter, loss functions for robust boosting are studied. Based on the concept of robust statistics, we propose a transformation of loss functions that makes boosting algorithms robust against extreme outliers. Next, the truncation of loss functions is applied to contamination models that describe the occurrence of mislabels near decision boundaries. Numerical experiments illustrate that the proposed loss functions derived from the contamination models are useful for handling highly noisy data in comparison with other loss functions.     

A high-resolution transmission electron microscope study of a zinc oxide varistor

Investigations were made of varistor microstructure, the morphology of Bi₂O₃ at multiple ZnO grain junctions, Bi₂O₃/ZnO grain boundaries and ZnO/ZnO grain boundaries (especially whether Bi₂O₃ is present or not at the ZnO/ZnO grain boundary) by means of high-resolution transmission electron microscopy and X-ray microanalysis in the scanning transmission electron microscope. Bi₂O₃ at multiple ZnO grain junctions consists of small particles of 0.1m in diameter, and they are vitrified to some extent. It is suggested that bismuth ions dissolve into ZnO grains over a 30 nm range from a Bi₂O₃/ZnO grain boundary; however, there is no bismuth at ZnO/ZnO grain boundaries.     

Basic constructs of the SIM operating system

The basic constructs of SIMPOS (Sequential Inference Machine Programming and Operating System) are explained. SIMPOS is an operating system for a super-personal computer (SIM), based on logic programming language (a modified Prolog, called KL0). Our design principle is simplicity both in concept and structure. The entire system will be constructed using these basic constructs.     

An Extension of the Receiver Operating Characteristic Curve and AUC-Optimal Classification

While most proposed methods for solving classification problems focus on minimization of the classification error rate, we are interested in the receiver operating characteristic (ROC) curve, which provides more information about classification performance than the error rate does. The area under the ROC curve (AUC) is a natural measure for overall assessment of a classifier based on the ROC curve. We discuss a class of concave functions for AUC maximization in which a boosting-type algorithm including RankBoost is considered, and the Bayesian risk consistency and the lower bound of the optimum function are discussed. A procedure derived by maximizing a specific optimum function has high robustness, based on gross error sensitivity. Additionally, we focus on the partial AUC, which is the partial area under the ROC curve. For example, in medical screening, a high true-positive rate to the fixed lower false-positive rate is preferable and thus the partial AUC corresponding to lower false-positive rates is much more important than the remaining AUC. We extend the class of concave optimum functions for partial AUC optimality with the boosting algorithm. We investigated the validity of the proposed method through several experiments with data sets in the UCI repository.