Ultra-flexible nonvolatile memory based on donor-acceptor diketopyrrolopyrrole polymer blends

Flexible memory cell array based on high mobility donor-acceptor diketopyrrolopyrrole polymer has been demonstrated. The memory cell exhibits low read voltage, high cell-to-cell uniformity and good mechanical flexibility, and has reliable retention and endurance memory performance. The electrical properties of the memory devices are systematically investigated and modeled. Our results suggest that the polymer blends provide an important step towards high-density flexible nonvolatile memory devices.

Memory-based reasoning approach for pattern recognition of binary images

Template matching is concerned with measuring the similarity between patterns of two objects. This paper proposes a memory-based reasoning approach for pattern recognition of binary images with a large template set. It seems that memory-based reasoning intrinsically requires a large database. Moreover, some binary image recognition problems inherently need large template sets, such as the recognition of Chinese characters which needs thousands of templates. The proposed algorithm is based on the Connection Machine, which is the most massively parallel machine to date, using a multiresolution method to search for the matching template. The approach uses the pyramid data structure for the multiresolution representation of templates and the input image pattern. For a given binary image it scans the template pyramid searching the match. A binary image of N × N pixels can be matched in O(log N) time complexity by our algorithm and is independent of the number of templates. Implementation of the proposed scheme is described in detail.

High performance non-volatile ferroelectric copolymer memory based on a ZnO nanowire transistor fabricated on a transparent substrate

A high performance ferroelectric non-volatile memory device based on a top-gate ZnO nanowire (NW) transistor fabricated on a glass substrate is demonstrated. The ZnO NW channel was spin-coated with a poly (vinylidenefluoride-co-trifluoroethylene) (P(VDF-TrFE)) layer acting as a top-gate dielectric without buffer layer. Electrical conductance modulation and memory hysteresis are achieved by a gate electric field induced reversible electrical polarization switching of the P(VDF-TrFE) thin film. Furthermore, the fabricated device exhibits a memory window of ∼16.5 V, a high drain current on/off ratio of ∼105, a gate leakage current below ∼300 pA, and excellent retention characteristics for over 104 s. © 2014 AIP Publishing LLC.

Write-Once Read-Many-Times Memory Based on a Single Layer of Pentacene

We realized an organic electrical memory device with a simple structure based on single-layer pentacene film embedded between Al and ITO electrodes. The optimization of the thickness and deposition rate of pentacene resulted in a reliable device with an on/off current ratio as high as nearly 10(6), which was two orders of magnitude higher than previous results, and the storage time was more than 576 h. The current transition process is attributed to the formation and damage of the Interface dipole at different electric fields, in which the current conduction showed a transition from ohmic conductive current to Fowler-Nordheim tunneling current. After the transition from ON- to OFF-state, the device tended to remain in the OFF-State even when the applied voltage was removed, which indicated that the device was very promising for write-once read-many-times memory.

A memory-based model of posttraumatic stress disorder: evaluating basic assumptions underlying the PTSD diagnosis.

In the mnemonic model of posttraumatic stress disorder (PTSD), the current memory of a negative event, not the event itself, determines symptoms. The model is an alternative to the current event-based etiology of PTSD represented in the Diagnostic and Statistical Manual of Mental Disorders (4th ed., text rev.; American Psychiatric Association, 2000). The model accounts for important and reliable findings that are often inconsistent with the current diagnostic view and that have been neglected by theoretical accounts of the disorder, including the following observations. The diagnosis needs objective information about the trauma and peritraumatic emotions but uses retrospective memory reports that can have substantial biases. Negative events and emotions that do not satisfy the current diagnostic criteria for a trauma can be followed by symptoms that would otherwise qualify for PTSD. Predisposing factors that affect the current memory have large effects on symptoms. The inability-to-recall-an-important-aspect-of-the-trauma symptom does not correlate with other symptoms. Loss or enhancement of the trauma memory affects PTSD symptoms in predictable ways. Special mechanisms that apply only to traumatic memories are not needed, increasing parsimony and the knowledge that can be applied to understanding PTSD.

Application of different heuristic classes in memory-based and stimulus-based decisions

This paper studies the drivers of heuristic application in different decision types. The study compares differences in frequencies of heuristic classes' such as recognition, one-reason choice and trade-off applied in, respectively, memory-based and stimulus-based choices as well as in high and low involvement decisions. The study has been conducted online among 205 participants from 28 countries.

Memory-based Embodied Cognition: a computational architecture

At its most fundamental, cognition as displayed by biological agents (such as humans) may be said to consist of the manipulation and utilisation of memory. Recent discussions in the field of cognitive robotics have emphasised the role of embodiment and the necessity of a value or motivation for autonomous behaviour. This work proposes a computational architecture – the Memory-Based Cognitive (MBC) architecture – based upon these considerations for the autonomous development of control of a simple mobile robot. This novel architecture will permit the exploration of theoretical issues in cognitive robotics and animal cognition. Furthermore, the biological inspiration of the architecture is anticipated to result in a mobile robot controller which displays adaptive behaviour in unknown environments.

Towards a developmental memory-based and embodied cognitive architecture

A novel memory-based embodied cognitive architecture is introduced – the MBC architecture. It is founded upon neuropsychological theory, and may be applied to investigating the interplay of embodiment, autonomy, and environmental interaction as related to the development of cognition.

Using an individual-based model to select among alternative foraging strategies of woodpigeons: data support a memory-based model with a flocking mechanism

Population modelling is increasingly recognised as a useful tool for pesticide risk assessment. For vertebrates that may ingest pesticides with their food, such as woodpigeon (Columba palumbus), population models that simulate foraging behaviour explicitly can help predicting both exposure and population-level impact. Optimal foraging theory is often assumed to explain the individual-level decisions driving distributions of individuals in the field, but it may not adequately predict spatial and temporal characteristics of woodpigeon foraging because of the woodpigeons’ excellent memory, ability to fly long distances, and distinctive flocking behaviour. Here we present an individual-based model (IBM) of the woodpigeon. We used the model to predict distributions of foraging woodpigeons that use one of six alternative foraging strategies: optimal foraging, memory-based foraging and random foraging, each with or without flocking mechanisms. We used pattern-oriented modelling to determine which of the foraging strategies is best able to reproduce observed data patterns. Data used for model evaluation were gathered during a long-term woodpigeon study conducted between 1961 and 2004 and a radiotracking study conducted in 2003 and 2004, both in the UK, and are summarised here as three complex patterns: the distributions of foraging birds between vegetation types during the year, the number of fields visited daily by individuals, and the proportion of fields revisited by them on subsequent days. The model with a memory-based foraging strategy and a flocking mechanism was the only one to reproduce these three data patterns, and the optimal foraging model produced poor matches to all of them. The random foraging strategy reproduced two of the three patterns but was not able to guarantee population persistence. We conclude that with the memory-based foraging strategy including a flocking mechanism our model is realistic enough to estimate the potential exposure of woodpigeons to pesticides. We discuss how exposure can be linked to our model, and how the model could be used for risk assessment of pesticides, for example predicting exposure and effects in heterogeneous landscapes planted seasonally with a variety of crops, while accounting for differences in land use between landscapes.

A Balanced Memory-Based Collaborative Filtering Similarity Measure.

Collaborative filtering recommender systems contribute to alleviating the problem of information overload that exists on the Internet as a result of the mass use of Web 2.0 applications. The use of an adequate similarity measure becomes a determining factor in the quality of the prediction and recommendation results of the recommender system, as well as in its performance. In this paper, we present a memory-based collaborative filtering similarity measure that provides extremely high-quality and balanced results; these results are complemented with a low processing time (high performance), similar to the one required to execute traditional similarity metrics. The experiments have been carried out on the MovieLens and Netflix databases, using a representative set of information retrieval quality measures.

Memory-Based Attentional Guidance: A Window to the Relationship between Working Memory and Attention

Attention, the cognitive means by which we prioritize the processing of a subset of information, is necessary for operating efficiently and effectively in the world. Thus, a critical theoretical question is how information is selected. In the visual domain, working memory (WM)—which refers to the short-term maintenance and manipulation of information that is no longer accessible by the senses—has been highlighted as an important determinant of what is selected by visual attention. Furthermore, although WM and attention have traditionally been conceived as separate cognitive constructs, an abundance of behavioral and neural evidence indicates that these two domains are in fact intertwined and overlapping. The aim of this dissertation is to better understand the nature of WM and attention, primarily through the phenomenon of memory-based attentional guidance, whereby the active maintenance of items in visual WM reliably biases the deployment of attention to memory-matching items in the visual environment. The research presented here employs a combination of behavioral, functional imaging, and computational modeling techniques that address: (1) WM guidance effects with respect to the traditional dichotomy of top-down versus bottom-up attentional control; (2) under what circumstances the contents of WM impact visual attention; and (3) the broader hypothesis of a predictive and competitive interaction between WM and attention. Collectively, these empirical findings reveal the importance of WM as a distinct factor in attentional control and support current models of multiple-state WM, which may have broader implications for how we select and maintain information.

Efficient two-step digit-set-restricted modified signed-digit algorithm based on optoelectronic shared content-addressable memory

A two-step digit-set-restricted modified signed-digit (MSD) adder based on symbolic substitution is presented. In the proposed addition algorithm, carry propagation is avoided by using reference digits to restrict the intermediate MSD carry and sum digits into {(1) over bar ,0} and {0, 1}, respectively. The algorithm requires only 12 minterms to generate the final results, and no complementarity operations for nonzero outputs are involved, which simplifies the system complexity significantly. An optoelectronic shared content-addressable memory based on an incoherent correlator is used for experimental demonstration. (c) 2005 Society of Photo-Optical Instrumentation Engineers.

Efficient two-step digit-set-restricted modified signed-digit algorithm based on optoelectronic shared content-addressable memory

A two-step digit-set-restricted modified signed-digit (MSD) adder based on symbolic substitution is presented. In the proposed addition algorithm, carry propagation is avoided by using reference digits to restrict the intermediate MSD carry and sum digits into {(1) over bar ,0} and {0, 1}, respectively. The algorithm requires only 12 minterms to generate the final results, and no complementarity operations for nonzero outputs are involved, which simplifies the system complexity significantly. An optoelectronic shared content-addressable memory based on an incoherent correlator is used for experimental demonstration. (c) 2005 Society of Photo-Optical Instrumentation Engineers.

Novel nonvolatile memory with multibit storage based on a ZnO nanowire transistor.

We demonstrate a room temperature processed ferroelectric (FE) nonvolatile memory based on a ZnO nanowire (NW) FET where the NW channel is coated with FE nanoparticles. A single device exhibits excellent memory characteristics with the large modulation in channel conductance between ON and OFF states exceeding 10(4), a long retention time of over 4 × 10(4) s, and multibit memory storage ability. Our findings provide a viable way to create new functional high-density nonvolatile memory devices compatible with simple processing techniques at low temperature for flexible devices made on plastic substrates.