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)     

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.     

Modeling time criticality of information

In this paper, we continue the research on formal treatment of attributes of information, based on the computational approach. In this scenario, the usefulness of advisory information is measured by the decrease in complexity of a problem we need to solve. We propose to model the time criticality via usefulness of a piece of information which is received during the computation. As a modeling tool, we use deterministic finite automata.     

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.     

Massenspektrometrische Untersuchung von dimeren Fettsäuren aus einem thermisch und oxydativ belasteten Bratfett

Mass Spectrometric Investigation of Dimeric Fatty Acids from Frying Fats Subjected to Thermal and Oxidative Action Methyl esters of dimers from peanut oil subjected to thermal and oxidative action in an industrial frying plant were isolated by column chromatography and investigated by mass spectrometry. Di-unsaturated bicyclic and tetra-unsaturated acyclic structures were found to be the main components of the dimers. Dimers of very similar composition were synthesized. The mechanism of dimer formation is discussed.     

Analysis of Alkylbenzenes by Capillary Gas Chromatography

Suitable operating conditions are shown for GC separation of linear alkylbenzene (AB) samples on capillary columns. Retention data on SE-30 of n-phenylalkanes C₉-C₁₆ were measured and separation factors for n-phenylalkanes isomers were calculated. For quantitative evaluation from peaks areas of n-phenylalkanes, correction coefficients were calculated. By statistical evaluation of errors, standard deviations and further statistical parameters were calculated, showing GC method as sufficiently accurate and reliable. From results of collaborative testing of the GC procedure for quantitative AB analysis, some recommendations followed, esp. for application of capillary columns with apolar thermostable stationary phase only, with advantage under temperature programming, applying reduced sample volume at limited FID attenuation. It must be pointed out, this method is strictly limited for linear AB.     

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.     

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.