Unpredictable Points and Chaos

It is revealed that a special kind of Poisson stable point, which we call an unpredictable point, gives rise to the existence of chaos in the quasi-minimal set. The existing definitions of chaos are formulated in sets of motions. This is the first time that description of chaos is initiated from a single motion. The theoretical results are exemplified by means of the symbolic dynamics.Comment: 9 page

Reproducibility of electrical caries measurements: A technical problem?

The currently available instrument for electrical detection of occlusal caries lesions {[}Electronic Caries Monitor (ECM)] uses a site-specific measurement with co-axial air drying. The reproducibility of this method has been reported to be fair to good. It was noticed that the measurement variation of this technique appeared to be non-random. It was the aim of this study to analyse how such a non-random reproducibility pattern arises and whether it could be observed for other operators and ECM models. Analysis of hypothetical measurement pairs showed that the pattern was related to measurements at the high and low end of the measurement range for the instrument. Data sets supplied by other researchers to a varying degree showed signs of a similar non-random pattern. These data sets were acquired at different locations, by different operators and using 3 different ECM models. The frequency distribution of measurements in all cases showed a single or double end-peaked distribution shape. It was concluded that the pattern was a general feature of the measurement method. It was tentatively attributed to several characteristics such as a high value censoring, insufficient probe contact and unpredictable probe contact. A different measurement technique, with an improved probe contact, appears to be advisable. Copyright (C) 2005 S. Karger AG, Basel

Non-Clairvoyant Batch Sets Scheduling: Fairness is Fair enough

Scheduling questions arise naturally in many different areas among which operating system design, compiling,... In real life systems, the characteristics of the jobs (such as release time and processing time) are usually unknown and unpredictable beforehand. The system is typically unaware of the remaining work in each job or of the ability of the job to take advantage of more resources. Following these observations, we adopt the job model by Edmonds et al (2000, 2003) in which the jobs go through a sequence of different phases. Each phase consists of a certain quantity of work and a speed-up function that models how it takes advantage of the number of processors it receives. We consider the non-clairvoyant online setting where a collection of jobs arrives at time 0. We consider the metrics setflowtime introduced by Robert et al (2007). The goal is to minimize the sum of the completion time of the sets, where a set is completed when all of its jobs are done. If the input consists of a single set of jobs, this is simply the makespan of the jobs; and if the input consists of a collection of singleton sets, it is simply the flowtime of the jobs. We show that the non-clairvoyant strategy EQUIoEQUI that evenly splits the available processors among the still unserved sets and then evenly splits these processors among the still uncompleted jobs of each unserved set, achieves a competitive ratio (2+\sqrt3+o(1))\frac{ln n}{lnln n} for the setflowtime minimization and that this is asymptotically optimal (up to a constant factor), where n is the size of the largest set. For makespan minimization, we show that the non-clairvoyant strategy EQUI achieves a competitive ratio of (1+o(1))\frac{ln n}{lnln n}, which is again asymptotically optimal.Comment: 12 pages, 1 figur

Linear, Deterministic, and Order-Invariant Initialization Methods for the K-Means Clustering Algorithm

Over the past five decades, k-means has become the clustering algorithm of choice in many application domains primarily due to its simplicity, time/space efficiency, and invariance to the ordering of the data points. Unfortunately, the algorithm's sensitivity to the initial selection of the cluster centers remains to be its most serious drawback. Numerous initialization methods have been proposed to address this drawback. Many of these methods, however, have time complexity superlinear in the number of data points, which makes them impractical for large data sets. On the other hand, linear methods are often random and/or sensitive to the ordering of the data points. These methods are generally unreliable in that the quality of their results is unpredictable. Therefore, it is common practice to perform multiple runs of such methods and take the output of the run that produces the best results. Such a practice, however, greatly increases the computational requirements of the otherwise highly efficient k-means algorithm. In this chapter, we investigate the empirical performance of six linear, deterministic (non-random), and order-invariant k-means initialization methods on a large and diverse collection of data sets from the UCI Machine Learning Repository. The results demonstrate that two relatively unknown hierarchical initialization methods due to Su and Dy outperform the remaining four methods with respect to two objective effectiveness criteria. In addition, a recent method due to Erisoglu et al. performs surprisingly poorly.Comment: 21 pages, 2 figures, 5 tables, Partitional Clustering Algorithms (Springer, 2014). arXiv admin note: substantial text overlap with arXiv:1304.7465, arXiv:1209.196

Unpredictable bits generation based on RRAM parallel configuration

In this letter a cell with the parallel combination of two TiN/Ti/HfO2/W resistive random access memory (RRAM) devices is studied for the generation of unpredictable bits. Measurements confirm that a simultaneous parallel SET operation in which one of the two RRAMs switches to the low resistance state (LRS) is an unpredictable process showing random properties for different sets of cells. Furthermore, given a device pair, the same device switches during subsequent write operations. The proposed cell is also analyzed under different current compliances and pulse widths with the same persistent behavior being observed. The features of the proposed cell, which provide data obfuscation without compromising reliability, pave the way for its application in Physical Unclonable Functions (PUFs) for hardware security purposes.Peer ReviewedPostprint (author's final draft

Seven Deadly Sins: Reflections on Donor Failings

In the face of continuing development challenges in the world's poorest countries, there have been new calls throughout the donor community to increase the volume of development aid. Equal attention should be given to the reform of the aid business itself, that is, the practices and processes and procedures and politics of aid. This paper sets out the shortcomings of that business on which new research has recently shed light, but which have not been adequately or explicitly incorporated into the donor community's reform agenda. It outlines seven of the worst "sins" or failings of donors, including impatience with institution building, collusion and coordination failures, failure to evaluate the results of their support, and financing that is volatile and unpredictable. It suggests possible short-term practical fixes and notes the need ultimately for more ambitious and structural changes in the overall aid architecture.development aid, donor community, aid reform