A Nonvolatile Organic Memory Device Using ITO Surfaces Modified by Ag‐Nanodots

We report on a single‐layer organic memory device made of poly(N‐vinylcarbazole) embedded between an Al electrode and ITO modified with Ag nanodots (Ag‐NDs). Devices exhibit high ON/OFF switching ratios of 10⁴. This level of performance could be achieved by modifying the ITO electrodes with some Ag‐NDs that act as trapping sites, reducing the current in the OFF state. Temperature dependence of the electrical characteristics suggest that the current of the low‐resistance state can be attributed to Schottky charge tunnelling through low‐resistance pathways of Al particles in the polymer layer and that the high‐resistance state can be controlled by charge trapping by the Al particles and Ag‐NDs.     

Gender differences in career decision making: The content and structure of preferences.

To identify possible sources of the observed differences in the career choices of women and men, three facets of career preferences were examined: the relative importance attributed to career-related aspects, the within-aspect preferences (i.e., desirable characteristics of occupations), and the structure of aspects derived from these within-aspect preferences. The career-related preferences of 2,000 young adults who were in the process of making their career decisions were analyzed. These career-related preferences were elicited during their dialogues with a computer-assisted career guidance system. The analyses revealed (a) only small gender differences in the relative importance of the aspects, (b) considerable gender differences in the within-aspect preferences, and (c) certain gender differences in the structure of aspects. The findings and their possible theoretical and practical implications are discussed. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Zur Modellierung von Sauterdurchmesser und Hold-up beim Einsatz eines konischen Turbinenrührers zum Dispergieren gas-flüssig

By comparing the experimental data of the Sauter-mean-diameter d ₃₂ and the hold up ? with models from literature, there are presented equations for d ₃₂ and ? for the used conical turbine in gas-liquid systems. The necessary adjustment of the proportionality constants of the literature equations will be explained on the basis of fluiddynamical phenomena. It can be established by fluid-dynamical results of a former study carried out with laser-doppler-anemometry. Coalescence phenomena are taken into account in the model using an analogy to bubble columns. The analogy to bubble columns turns out to be suitable. Arguments for the necessity of considering the local fluiddynamics in the modelling of dispersions are presented.     

Developing and evaluating language courseware

The paper sets out twenty proposals for the development and evaluation of Computer Assisted Language Learning (CALL) programs. These proposals emerge from special characteristics of language instruction and of the use of computers to assist in language instruction. We combine theoretically-based assumptions with empirical findings drawn from investigation of language courseware for Hebrew speakers in Israel. We first list four unique features of language instruction: (1) the object-language-meta-language distinction; (2) computer as written medium vs. language as primary spoken medium; (3) teaching of second language skills vs. linguistics; (4) the computer as an electronic tool vs. the computer as a cognitive entity simulating the speaker. We then show how these unique characteristics of language instruction (mother-tongue and foreign language) impose special proposals on language courseware. These proposals should be observed in the development of language courseware and in the evaluation of such programs. Clearly, these proposals integrate with general courseware proposals. Michal Ephratt (Ph.D., computational linguistics) completed post-doctoral studies at the University of Rochester. She has been on the staff of the Dept. of Hebrew Linguistics, University of Haifa, since 1988. Some of her publications include Root-Pattern Array: The Main Tool of Hebrew Word Formation (Hebrew University, 1985); and What's in a Joke? in Advances in Artificial Intelligence, Natural Language and Knowledge-based Systems (Springer-Verlag, 1990).This paper is based on work the author did as a consultant in the National Courseware Evaluation Department of the Ministry of Education. I wish to thank Esther Diamant, head of the department, for making the study possible.     

Battery State-Of-Charge Based Altitude Controller for Small, Low Cost Multirotor Unmanned Aerial Vehicles

Small unmanned aerial vehicles (UAV) are typically driven by Lithium polymer batteries. The batteries have their own dynamics, which changes during discharge. Classical approaches to altitude control assume a time-invariant system and therefore fail. Adaptive controllers require an identified system model which is often unavailable. Battery dynamics can be characterized and used for a battery model-based controller. This controller is useful in situations when no feedback from actuators (such as RPM or thrust) is available. After measuring the battery dynamics for two distinct types of batteries, a controller is designed and experimentally verified, showing a consistent performance during entire discharge test and a consequent flight verification.     

Evolution of efficient real-time non-linear image filters for FPGAs

Image processing represents a research field in which high-quality solutions have been obtained using various soft computing techniques. Evolutionary algorithms constitute a class of stochastic search methods that are applicable in both optimization and design tasks. In the area of circuit design Cartesian Genetic Programming has often been utilized in combination with an algorithm of Evolutionary Strategy. Digital image filters represent a specific class of circuits whose design can be performed by means of this approach. Switching filters are advanced non-linear filtering techniques in which the main idea is to detect and filter the noise pixels while keeping the uncorrupted pixels unchanged in order to increase the quality of the resulting image. The aim of this article is to present a robust design technique based on Cartesian Genetic Programming for the automatic synthesis of switching image filters intended for real-time processing applications. The robustness of the proposed evolutionary approach is evaluated using four design problems including the removal of salt and pepper noise, random shot noise, impulse burst noise and impulse burst noise combined with random shot noise. An extensive evaluation is performed in order to compare the properties of the evolved switching filters with the best conventional solutions. The evaluation has shown that the evolved switching filters exhibit a very good trade off between the quality of filtering and the implementation cost in field programmable gate arrays.     

Effects of redox-active interlayer anions on the oxygen evolution reactivity of NiFe-layered double hydroxide nanosheets

Nickel-iron layered double hydroxide (NiFe-LDH) nanosheets have shown optimal oxygen evolution reaction (OER) performance; however, the role of the intercalated ions in the OER activity remains unclear. In this work, we show that the activity of the NiFe-LDHs can be tailored by the intercalated anions with different redox potentials. The intercalation of anions with low redox potential (high reducing ability), such as hypophosphites, leads to NiFe-LDHs with low OER overpotential of 240 mV and a small Tafel slope of 36.9 mV/dec, whereas NiFe-LDHs intercalated with anions of high redox potential (low reducing ability), such as fluorion, show a high overpotential of 370 mV and a Tafel slope of 80.8 mV/dec. The OER activity shows a surprising linear correlation with the standard redox potential. Density functional theory calculations and X-ray photoelectron spectroscopy analysis indicate that the intercalated anions alter the electronic structure of metal atoms which exposed at the surface. Anions with low standard redox potential and strong reducing ability transfer more electrons to the hydroxide layers. This increases the electron density of the surface metal sites and stabilizes their high-valence states, whose formation is known as the critical step prior to the OER process.

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Method of classifier selection using the genetic approach

Abstract: The paper presents a novel machine learning algorithm used for training a compound classifier system that consists of a set of area classifiers. Area classifiers recognize objects derived from the respective competence area. Splitting feature space into areas and selecting area classifiers are two key processes of the algorithm; both take place simultaneously in the course of an optimization process aimed at maximizing the system performance. An evolutionary algorithm is used to find the optimal solution. A number of experiments have been carried out to evaluate system performance. The results prove that the proposed method outperforms each elementary classifier as well as simple voting.     

Speeding Up HMM Decoding and Training by Exploiting Sequence Repetitions

We present a method to speed up the dynamic program algorithms used for solving the HMM decoding and training problems for discrete time-independent HMMs. We discuss the application of our method to Viterbi’s decoding and training algorithms (IEEE Trans. Inform. Theory IT-13:260–269, 1967), as well as to the forward-backward and Baum-Welch (Inequalities 3:1–8, 1972) algorithms. Our approach is based on identifying repeated substrings in the observed input sequence. Initially, we show how to exploit repetitions of all sufficiently small substrings (this is similar to the Four Russians method). Then, we describe four algorithms based alternatively on run length encoding (RLE), Lempel-Ziv (LZ78) parsing, grammar-based compression (SLP), and byte pair encoding (BPE). Compared to Viterbi’s algorithm, we achieve speedups of Θ(log n) using the Four Russians method, using RLE, using LZ78, using SLP, and Ω(r) using BPE, where k is the number of hidden states, n is the length of the observed sequence and r is its compression ratio (under each compression scheme). Our experimental results demonstrate that our new algorithms are indeed faster in practice. We also discuss a parallel implementation of our algorithms. A preliminary version of this paper appeared in Proc. 18th Annual Symposium on Combinatorial Pattern Matching (CPM), pp. 4–15, 2007. Y. Lifshits’ research was supported by the Center for the Mathematics of Information and the Lee Center for Advanced Networking. S. Mozes’ work conducted while visiting MIT.     

The joint movement of pebbles in solving the ($$N^2-1$$)-puzzle suboptimally and its applications in rule-based cooperative path-finding

The present paper deals with the problem of solving the (\(n^2 - 1\))-puzzle and cooperative path-finding (CPF) problems sub-optimally by rule-based algorithms. To solve the puzzle, we need to rearrange \(n^2 - 1\) pebbles in the \(n \times n\)-sized square grid using one vacant position to achieve the goal configuration. An improvement to the existing polynomial-time algorithm is proposed and experimentally analyzed. The improved algorithm represents an attempt to move pebbles in a more efficient way compared to the original algorithm by grouping them into so-called snakes and moving them together as part of a snake formation. An experimental evaluation has shown that the snakeenhanced algorithm produces solutions which are 8–9 % shorter than the solutions generated by the original algorithm. Snake-like movement has also been integrated into the rule-based algorithms used in solving CPF problems sub-optimally, which is a closely related task. The task in CPF consists in moving a group of abstract robots on an undirected graph to specific vertices. The robots can move to unoccupied neighboring vertices; no more than one robot can be placed in each vertex. The (\(n^2 - 1\))-puzzle is a special case of CPF where the underlying graph is a 4-connected grid and only one vertex is vacant. Two major rule-based algorithms for solving CPF problems were included in our study—BIBOX and PUSH-and-SWAP (PUSH-and-ROTATE). The use of snakes in the BIBOX algorithm led to consistent efficiency gains of around 30 % for the (\(n^2 - 1\))-puzzle and up to 50 % in for CPF problems on biconnected graphs with various ear decompositions and multiple vacant vertices. For the PUSH-and-SWAP algorithm, the efficiency gain achieved from the use of snakes was around 5–8 %. However, the efficiency gain was unstable and hardly predictable for PUSH-and-SWAP.