Retrieval Mechanism Research Articles

Improving Spatial Coverage for Aqua MODIS AOD using NDVI-Based Multi-Temporal Regression Analysis

The Moderate Resolution Imaging Spectroradiometer (MODIS) provides widespread Aerosol Optical Depth (AOD) datasets for climatological and environmental health research. Since MODIS AOD clearly lacks coverage in orbit-scanning gaps and cloud obscuration, some applications will benefit from data recovery using multi-temporal AOD. Aimed at qualitatively describing the relationship between multi-temporal AOD, AOD loadings and Normalized Difference Vegetation Index (NDVI) have been considered based on the mechanism of satellite AOD retrieval. Accordingly, the NDVI-based Weighted Linear Regression (NWLR) has been proposed to recover AOD by synthetically weighing AOD similarity, spatial proximity, and NDVI similarity. To evaluate the performance of AOD recovery, simulated experiments applying gap and window masks were conducted in South Asia and Beijing, respectively. The evaluation results demonstrated that the linear regression R2 achieved 0.8 and the absolute relative errors remained steady. Further validation was conducted between the recovered and actual AODs using 56 Aerosol Robotic Network (AERONET) sites in East and South Asia from 2013 to 2015, which demonstrated that over 41% of recovered AODs fell within the expected error (EE) envelope. Additional validation conducted in South Asia and Beijing showed that recovery by NWLR did not expand satellite-derived AOD errors, and the accuracy of recovered AOD was consistent with the accuracy of the original Aqua MODIS Deep Blue (DB) AOD. The recovery results illustrated that AOD coverage was improved in most regions, especially in North China, Mongolia, and South Asia, which could provide better support in aerosol spatio-temporal analysis and aerosol data assimilation.

A compact multiband antenna using λ/4 rectangular stub loaded with metamaterial for IEEE 802.11N and IEEE 802.16E

ABSTRACTThis research article describes a compact multiband antenna using λ/4 rectangular stub, loaded with metamaterial for the frequency bands 2.4, 3.5, and 5.8 GHz allocated to IEEE 802.11n (WLAN) and IEEE 802.16e (WiMAX) standards in wireless communication. Compactness, multiband, and impedance matching operations in the proposed design are accomplished by utilizing a rectangular microstrip patch, a novel metamaterial based split ring resonator (SRR), a λ/4 rectangular stub and a ground plane. The proposed SRR negative permeability retrieval mechanism is explained in detail. The electrical dimensions of the designed antenna are 0.206 λ0 × 0.174 λ0 (25 × 22 mm2) at lower resonating band (2.4 GHz) and fabricated on a widely available FR4 substrate having 4.4 as dielectric constant and 1.6 mm as thickness. The average gain of 2.58 dBi, good impedance matching, stable radiation characteristics with high co‐polarization value and return loss bandwidth of 13.7% (2.26–2.57 GHz), 10.09% (3.27–3.60 GHz) and 5.09% (5.69–5.98 GHz) are observed at the bands of operation when the antenna is fabricated and tested. © 2017 Wiley Periodicals, Inc. Microwave Opt Technol Lett 59:1000–1006, 2017

A Lightweight CUDA-Based Parallel Map Reprojection Method for Raster Datasets of Continental to Global Extent

Geospatial transformations in the form of reprojection calculations for large datasets can be computationally intensive; as such, finding better, less expensive ways of achieving these computations is desired. In this paper, we report our efforts in developing a Compute Unified Device Architecture (CUDA)-based parallel algorithm to perform map reprojections for raster datasets on personal computers using Graphics Processing Units (GPUs). This algorithm has two unique features: a) an output-space-based parallel processing strategy to handle transformations more rigorously, and b) a chunk-based data decomposition method for projected space in conjunction with an on-the-fly data retrieval mechanism to avoid memory overflow. To demonstrate the performance of our CUDA-based map reprojection approaches, we have conducted tests between this method and the traditional serial version using the Central Processing Unit (CPU). The results show that speedup ratios range from 10 times to 100 times in all test scenarios. The lessons learned from the tests are summarized.

Flexible retrieval: When true inferences produce false memories.

Episodic memory involves flexible retrieval processes that allow us to link together distinct episodes, make novel inferences across overlapping events, and recombine elements of past experiences when imagining future events. However, the same flexible retrieval and recombination processes that underpin these adaptive functions may also leave memory prone to error or distortion, such as source misattributions in which details of one event are mistakenly attributed to another related event. To determine whether the same recombination-related retrieval mechanism supports both successful inference and source memory errors, we developed a modified version of an associative inference paradigm in which participants encoded everyday scenes comprised of people, objects, and other contextual details. These scenes contained overlapping elements (AB, BC) that could later be linked to support novel inferential retrieval regarding elements that had not appeared together previously (AC). Our critical experimental manipulation concerned whether contextual details were probed before or after the associative inference test, thereby allowing us to assess whether (a) false memories increased for successful versus unsuccessful inferences, and (b) any such effects were specific to after compared with before participants received the inference test. In each of 4 experiments that used variants of this paradigm, participants were more susceptible to false memories for contextual details after successful than unsuccessful inferential retrieval, but only when contextual details were probed after the associative inference test. These results suggest that the retrieval-mediated recombination mechanism that underlies associative inference also contributes to source misattributions that result from combining elements of distinct episodes. (PsycINFO Database Record

Novel Mechanism for In-Pipe Robot Based on a Multiaxial Differential Gear Mechanism

This paper presents a mechanism for an in-pipe robot, called the Multifunctional Robotic crawler for In-pipe inspection VII (MRINSPECT VII), which is under development for the inspection of gas pipelines. Applicable pipeline diameters are from 150 to 200 mm. The robot is based on a multiaxial differential gear mechanism and designed to adapt to the varying inside geometries of pipelines, such as elbows, by mechanically modulating the velocities of active wheels without any control effort. In addition to the differential gear mechanism, the MRINSPECT VII is equipped with an active adhesion mechanism for improving traction ability and a rescue mechanism for easy retrieval of the robot in the case of trouble inside pipelines. In this paper, the multiaxial differential gear mechanism is mainly explained, and the construction of the robot mechanism is detailed. Finally, the effectiveness of the mechanism is experimentally demonstrated with the MRINSPECT VII.

The neurocognitive basis of borrowed context information

Falsely remembered items can be accompanied by episodic context retrieval. This finding is difficult to explain because there is no episode that binds the remembered item to the experimenter-controlled context features. The current study examines the neural correlates of false context retrieval when the context features can be traced to encoding episodes of semantically-similar items. Our neuroimaging results support a “dissociated source” mechanism for context borrowing in false memory. We found that parahippocampal cortex (PHc) activation, thought to indicate context retrieval, was greater during trials that involved context borrowing (an incorrect, but plausible source decision) than during baseline correct context retrieval. In contrast, hippocampal activation, thought to indicate retrieval of an episodic binding, was stronger during correct source retrieval than during context borrowing. Vivid context retrieval during false recollection experiences was also indicated by increased activation in visual perceptual regions for context borrowing as compared to other incorrect source judgments. The pattern of findings suggests that context borrowing can arise when unusually strong activation of a semantically-related item's contextual features drives relatively weak retrieval of the associated episodic binding with failure to confirm the item information within that binding. This dissociated source retrieval mechanism suggests that context-driven episodic retrieval does not necessarily lead to retrieval of specific item details. That is, source information can be retrieved in the absence of item memory.

Reflexive attraction in comprehension is selective

Abstract Many studies have shown that attraction effects are consistently found for linguistic dependencies like subject-verb agreement, e.g., * The key to the cabinets are on the table . However, not all dependencies are equally susceptible to attraction. A parade case involves reflexive-antecedent dependencies, which rarely show attraction effects. The contrast between agreement and reflexives with respect to attraction has motivated various proposals regarding the memory architecture for the parser, including the use of qualitatively different access mechanisms or the selective use of morphological features as retrieval cues for different dependencies. In this paper, we show how to systematically induce attraction effects for reflexives in three eye-tracking experiments. Furthermore, we show based on computational simulations that it is possible to derive both the presence and absence of reflexive attraction from the same retrieval mechanism, based on the ACT-R architecture. We then propose an account of why agreement and reflexives are differentially susceptible to attraction, based on the predictability of the dependency.

AN OBJECT PROPERTIES FILTER FOR MULTI-MODALITY ONTOLOGY SEMANTIC IMAGE RETRIEVAL

Ontology is a semantic technology that provides the possible approach to bridge the issue on semantic gap in image retrieval between low-level visual features and high-level human semantic. The semantic gap occurs when there is a discrepancy between the information that is extracted from visual data and the text description. In other words, there is a difference between the computational representation in machine and human natural language. In this paper, an ontology has been utilized to reduce the semantic gap by developing a multi-modality ontology image retrieval with the enhancement of a retrieval mechanism by using the object properties filter. To achieve this, a multi-modality ontology semantic image framework was proposed, comprising of four main components which were resource identification, information extraction, knowledge-based construction and retrieval mechanism. A new approach, namely object properties filter is proposed by customizing the semantic image retrieval algorithm and the graphical user interface to facilitate the user to engage with the machine i.e. computers, in order to enhance the retrieval performance. The experiment results showed that the proposed approach delivered better results compared to the approach that did not use the object properties filter based on probability precision measurement.

Real-Time Control System for Improved Precision and Throughput in an Ultrafast Carbon Fiber Placement Robot Using a SoC FPGA Extended Processing Platform

We present an architecture for accelerating the processing and execution of control commands in an ultrafast fiber placement robot. The system consists of a robotic arm designed by Coriolis Composites whose purpose is to move along a surface, on which composite fibers are deposed, via an independently controlled head. In first system implementation, the control commands were sent via Profibus by a PLC, limiting the reaction time and thus the precision of the fiber placement and the maximum throughput. Therefore, a custom real-time solution was imperative in order to ameliorate the performance and to meet the stringent requirements of the target industry (avionics, aeronautical systems). The solution presented in this paper is based on the use of a SoC FPGA processing platform running a real-time operating system (FreeRTOS), which has enabled an improved comamnd retrieval mechanism. The system’s placement precision was improved by a factor of 20 (from 1 mm to 0.05 mm), while the maximum achievable throughput was 1 m/s, compared to the average 30 cm/s provided by the original solution, enabling fabricating more complex and larger pieces in a significant fraction of the time.

A Survey of Information Retrieval Techniques

The explosive growth of resources stored in various forms and transmitted over the internet has necessitated researches into information retrieval technologies. The major information retrieval mechanisms commonly employed include vector space model, Boolean model, Fuzzy Set model, and probabilistic retrieval model. These models are used to find similarities between the query and the documents to retrieve documents that reflect the query. These approaches are based on key-word, which uses lists of keywords to describe the information content. In this paper, a survey of these models is provided in order to understand their working mechanisms and shortcomings. This understanding is vital as it facilitates the choice of an information retrieval technique, based on the underlying requirements. The results of this survey revealed that the current information retrieval models fall short of the expectations in one way or the other. As such, they are not ideal for high precision information retrieval applications.

A Hill-Climbing based Information Retrieval Mechanism for Formal Concept Analysis in Folksonomies

Folksonomies are a means by which communities of people annotate resources with tags. The information contributed by this action can be used to effectively search for an object. A method is required to represent and categorize objects based on their tags and search them effectively by providing words that are relevant to any object. Few existing systems use lattice structure that conceptually groups tagged objects into nodes. The lattice structure facilitates fast search and creates relations between groups of objects. In order to search objects existing statistical and mathematical measures solely take into account a few factors such as the co-occurrence of two tags rather than their meanings to determine their similarity. Hence, when searching for an object based on a user query in a lattice structure there is a need for semantic similarity measure for comparing the meaning of each query with the tags at each lattice node. Also, existing search algorithms like breadth first search process more number of concepts than necessary and so there is a need for a mechanism that performs a narrower search through the lattice. The proposed system represents and categorizes objects with a lattice structure and specifies an optimized search technique based on semantic similarity. Semantic similarity is found by extracting synonyms of the user's query and mapping them to the tags of the object in the lattice structure. In order to achieve an optimized top-down search a novel hill-climbing approach is performed over the lattice that processes minimal number of lattice nodes. Experimental results show the efficiency of the search algorithm along with the similarity measures with near accurate results to the user's query.

Implicit Prosody and Cue-based Retrieval: L1 and L2 Agreement and Comprehension during Reading.

This project focuses on structural and prosodic effects during reading, examining their influence on agreement processing and comprehension in native English (L1) and Spanish–English bilingual (L2) speakers. We consolidate research from several distinct areas of inquiry—cognitive processing, reading fluency, and L1/L2 processing—in order to support the integration of prosody with a cue-based retrieval mechanism for subject-verb agreement. To explore this proposal, the experimental design manipulated text presentation to influence implicit prosody, using sentences designed to induce subject-verb agreement attraction errors. Materials included simple and complex relative clauses with head nouns and verbs that were either matched or mismatched for number. Participants read items in one of three presentation formats (whole sentence, word-by-word, or phrase-by-phrase), rated each item for grammaticality, and responded to a comprehension probe. Results indicated that while overall, message comprehension was prioritized over subject-verb agreement computation, presentation format differentially affected both measures in the L1 and L2 groups. For the L1 participants, facilitating the projection of phrasal prosody onto text (phrase-by-phrase presentation) enhanced performance in agreement processing, while disrupting prosodic projection via word-by-word presentation decreased comprehension accuracy. For the L2 participants, however, phrase-by-phrase presentation was not significantly beneficial for agreement processing, and additionally resulted in lower comprehension accuracy. These differences point to a significant role of prosodic phrasing during agreement processing in both L1 and L2 speakers, additionally suggesting that it may contribute to a cue-based retrieval agreement model, either acting as a cue directly, or otherwise scaffolding the retrieval process. The discussion and results presented provide support both for a cue-based retrieval mechanism in agreement, and the function of prosody within such a mechanism, adding further insight into the interaction of retrieval processes, cognitive task load, and the role of implicit prosody.

Micro Finance Model of Agriculture in Supporting Economic Growth in Aceh

The general objective of this study was to analyze the model of micro-financing of agriculture in order to develop the rural economy and support economic growth in Aceh. The specific purpose of this study is to identify and analyze the social and economic profile of households recipient farmer agricultural credit and micro enterprises in Aceh, to evaluate the performance of credit financing to the Government Bank Sector Micro Farms, identify prospects, challenges and constraints of microfinance institutions in microfinance lending farming in Aceh and analyze the sustainability of microfinance models of agriculture in Aceh, and formulate policies appropriate agricultural micro-financing in supporting economic growth in Aceh. Financing system analysis conducted qualitative description, including ease of access to credit, credit suitability, filing and retrieval mechanism of credit, smoothness, obstacles and constraints in lending, loan interest rate and loan repayment system including congestion anticipation loans. Determination of the effectiveness of microcredit agriculture Scoring is done via method. The effectiveness of agricultural micro-credit schemes assessed through monitoring and evaluation of the performance of some aspects of inputs, processes, outputs, outcomes, benefits and impact. Analysis of the sustainability of credit schemes analyzed based on financial viability, institutional viability (managerial), and the viability of the participants, Results of studies in which micro-financing system for farming and still there has been no financial institution that helps, financing done still in the form of government assistance to the farmers and there is no oversight of government ranging from distribution, so that harvesting and collection processes, outputs, outcomes, benefits and can not feel the impact in the community

The Parallel Episodic Processing (PEP) model 2.0: A single computational model of stimulus-response binding, contingency learning, power curves, and mixing costs

The current paper presents an extension of the Parallel Episodic Processing model. The model is developed for simulating behaviour in performance (i.e., speeded response time) tasks and learns to anticipate both how and when to respond based on retrieval of memories of previous trials. With one fixed parameter set, the model is shown to successfully simulate a wide range of different findings. These include: practice curves in the Stroop paradigm, contingency learning effects, learning acquisition curves, stimulus-response binding effects, mixing costs, and various findings from the attentional control domain. The results demonstrate several important points. First, the same retrieval mechanism parsimoniously explains stimulus-response binding, contingency learning, and practice effects. Second, as performance improves with practice, any effects will shrink with it. Third, a model of simple learning processes is sufficient to explain phenomena that are typically (but perhaps incorrectly) interpreted in terms of higher-order control processes. More generally, we argue that computational models with a fixed parameter set and wider breadth should be preferred over those that are restricted to a narrow set of phenomena.

On Decoding Grid Cell Population Codes Using Approximate Belief Propagation.

Neural systems are inherently noisy. One well-studied example of a noise reduction mechanism in the brain is the population code, where representing a variable with multiple neurons allows the encoded variable to be recovered with fewer errors. Studies have assumed ideal observer models for decoding population codes, and the manner in which information in the neural population can be retrieved remains elusive. This letter addresses a mechanism by which realistic neural circuits can recover encoded variables. Specifically, the decoding problem of recovering a spatial location from populations of grid cells is studied using belief propagation. We extend the belief propagation decoding algorithm in two aspects. First, beliefs are approximated rather than being calculated exactly. Second, decoding noises are introduced into the decoding circuits. Numerical simulations demonstrate that beliefs can be effectively approximated by combining polynomial nonlinearities with divisive normalization. This approximate belief propagation algorithm is tolerant to decoding noises. Thus, this letter presents a realistic model for decoding neural population codes and investigates fault-tolerant information retrieval mechanisms in the brain.

Memory Retrieval Has a Dynamic Influence on the Maintenance Mechanisms That Are Sensitive to ζ-Inhibitory Peptide (ZIP).

Memory retrieval and the molecular mechanisms that are sensitive to ζ-inhibitory peptide (ZIP) are the few manipulations that have been shown to effect memory maintenance. Although much is known about their effect on maintenance separately, it is unknown how they interact. Here, we describe a model for the interaction between memory retrieval and ZIP-sensitive mechanisms, showing that retrieval trials briefly (i.e., for 45 h) interrupt these mechanisms. ZIP sensitivity emerges across a similar time window after memory acquisition and retrieval; the maintenance mechanisms that follow acquisition and retrieval differ, however, in the latency with which the impact of ZIP is expressed.

Systematic Identification of Coordination Gaps in Pediatric Care

In the United States, the status of coordination among pediatric care services is not well understood. Through the use of quality improvement (QI) techniques, coordination gaps were systematically identified in the interagency network of pediatric services in Kalamazoo MI. Gaps were found in transportation resources, follow-up procedures, awareness of services, interagency communication, insurance limitations, population behaviors, and resource utilization. This preliminary study reveals the need for (1) protocols for intraand inter-agency communication, (2) mechanisms for easy and fast retrieval of pediatric resources, and (3) health information exchange.

Proust - the Scientist

Abstract Proust was not only a French writer, but - based on his incredible scientific knowledge and descriptions in his novel - to some extent, a neurologist and psychologist. Far ahead of his time, Proust illustrated in his masterpiece In Search of Lost Time a link between personal memories and sensory stimuli. In his novels, he explains the mechanism of memory retrieval after perceiving a sensation. Without a doubt the most famous scene of In Search of Lost Time remains the moment when the taste of a French pastry, called “madeleine,” rekindles the childhood memories of the narrator Marcel in the first volume Swann’s Way. Similarly, listening to Vinteuil’s Sonata triggers and maintains Swann’s love for Odette and its expression in the second volume of the masterpiece In Search of Lost Time. His descriptions reveal that human senses are not only linked to personal memories, but may also trigger them. Moreover, contemporary studies in the biological field have shown that there are correlations between stimuli and intangible feelings and states of mind, such as love, hatred, and sympathy, primarily located in the amygdala of the human brain. Reading Proust’s masterpiece In Search of Lost Time through the lens of current neurological studies opens an interesting and innovative perspective on the subject of memory retrieval and shows that he was not “only” a writer, but also an observational scientist.

Application of the dual-component model of working memory to ADHD:Greater secondary memory deficit despite confounded cognitive differences

ABSTRACTThe dual-component model postulates that working memory capacity consists of two dissociable components: maintenance in primary memory (PM) and retrieval from secondary memory (SM). Recent application of this model to attention-deficit/hyperactivity disorder (ADHD) has revealed that the SM component is more deficient than the PM component across both verbal and spatial modalities. The present study attempts to strengthen this conclusion by addressing two weaknesses in the previous study. First, the present study shows that the SM component continues to be more deficient than the PM component across both modalities under conditions in which (1) all participants were instructed to use the same recall strategy (resulting in the exclusion of fewer participants); and, (2) individual differences in this strategy were controlled. Second, the present study also documents a group difference in word reading efficiency that is confounded with diagnostic status and that might have influenced estimates of PM and SM capacities in the verbal modality. However, although the SM component is more deficient than the PM component in the ADHD group, the magnitude of this interaction does not vary as a function task modality. These findings are interpreted to suggest that the pattern of WM deficiencies observed are part of a causal pathway that can lead to the symptoms of ADHD, as well as to impairments in reading (and intelligence) due to overlapping cue-dependent retrieval mechanisms. These findings provide additional support for the notion that the SM component of WM is an important and neglected target for treatment.

The Neural Basis of Recollection Rejection: Increases in Hippocampal-Prefrontal Connectivity in the Absence of a Shared Recall-to-Reject and Target Recollection Network.

Recollection rejection or "recall-to-reject" is a mechanism that has been posited to help maintain accurate memory by preventing the occurrence of false memories. Recollection rejection occurs when the presentation of a new item during recognition triggers recall of an associated target, a mismatch in features between the new and old items is registered, and the lure is correctly rejected. Critically, this characterization of recollection rejection involves a recall signal that is conceptually similar to recollection as elicited by a target. However, previous neuroimaging studies have not evaluated the extent to which recollection rejection and target recollection rely on a common neural signal but have instead focused on recollection rejection as a postretrieval monitoring process. This study utilized a false memory paradigm in conjunction with an adapted remember-know-new response paradigm that separated "new" responses based on recollection rejection from those that were based on a lack of familiarity with the item. This procedure allowed for parallel recollection rejection and target recollection contrasts to be computed. Results revealed that, contrary to predictions from theoretical and behavioral literature, there was virtually no evidence of a common retrieval mechanism supporting recollection rejection and target recollection. Instead of the typical target recollection network, recollection rejection recruited a network of lateral prefrontal and bilateral parietal regions that is consistent with the retrieval monitoring network identified in previous neuroimaging studies of recollection rejection. However, a functional connectivity analysis revealed a component of the frontoparietal rejection network that showed increased coupling with the right hippocampus during recollection rejection responses. As such, we demonstrate a possible link between PFC monitoring network and basic retrieval mechanisms within the hippocampus that was not revealed with univariate analyses alone.