Sequential Matching Research Articles

Subjective Homophily and the Fixtures Problem

The Stable Fixtures problem (Irving and Scott (2007)) is a generalized matching model that nests the well-known Stable Roommates, Stable Marriage, and College Admissions problems as special cases. This paper extends a result of the Stable Roommates problem to demonstrate that a class of homophilic preferences with an appealing psychological interpretation is sufficient to ensure that starting from an arbitrary matching, a decentralized process of allowing the sequential matching of randomly chosen blocking pairs will converge to a pairwise-stable matching with probability one. Strategic implications of this class of preferences are examined and further possible generalizations and directions for future research are discussed.

成人院外心停止患者に対する病院前の高度な気道確保：全国救急蘇生統計コホート研究(Pre–hospital advanced airway management for adults with out–of–hospital cardiac arrest: nationwide cohort study)

要旨【目的】院外心停止患者に対する病院前の高度な気道確保は不良な生存・神経学的アウトカムと関連することが，これまでの多くの観察研究で報告されてきた。成人院外心停止患者に対する病院前の高度な気道確保と生存との関連を明らかにすることを目的として本研究を行った。【対象】2014年1月から2016年12月までの本邦の全国救急蘇生統計（ウツタインデータ）を対象に，連続登録された院外心停止成人症例について，心電図の初回記録をもとに「電気ショック適応（心室細動または無脈性心室頻拍）」および「電気ショック非適応（無脈性電気活動または心静止）」の2つのサブコホートに分類した。時間依存性傾向スコアに基づいて同一時点（分）で心肺蘇生時処置として高度な気道確保を受けた患者と高度な気道確保を受けていない患者とを連続的にマッチングさせた。1か月後または1か月以内の退院時の生存割合を主要アウトカムとした。【結果】適格患者310,620名のうち，電気ショック適応群の患者20,516名中8,459名（41.2%）および電気ショック非適応群の患者290,104名中121,890名（42.0%）が心肺蘇生時に高度な気道確保を受けた。時間依存性傾向スコアによる連続マッチングを行った後，電気ショック適応群の患者16,114名および電気ショック非適応群の患者236,042名を同一時点（分）でそれぞれマッチングさせた。電気ショック適応群では，高度な気道確保を受けた患者と受けなかった患者の間で生存割合に差はみられず，それぞれ8,057名中1,546名（19.2%）および8,057名中1,500名（18.6%）であった（調整リスク比1.00，95%信頼区間0.93–1.07）。電気ショック非適応群では，高度な気道確保を受けた患者は受けなかった患者よりも生存割合が高く，それぞれ118,021名中2,696名（2.3%）および118,021名中2,127名（1.8%）であった（調整リスク比1.27，1.20–1.35）。【結論】成人院外心停止患者における時間依存性傾向スコア連続マッチング解析において，電気ショック適応リズムの患者では高度な気道確保と生存に関連がなかったのに対し，電気ショック非適応リズムの患者では高度な気道確保は生存と関連した。

Modified Dynamic Time Warping for Hierarchical Clustering

Time series clustering is the process of grouping sequential correspondences in similar clusters. The key feature behind clustering time series data lies on the similarity/distance function used to identify the sequential matches. Dynamic Time Warping (DTW) is one of the common distance measures that have demonstrated competitive results compared to other functions. DTW aims to find the shortest path in the process of identifying sequential matches. DTW relies on dynamic programming to obtain the shortest path where the smaller distance is being computed. However, in the case of equivalent distances, DTW is selecting the path randomly. Hence, the selection could be misguided in such randomization process, which significantly affects the matching quality. This is due to randomization may lead to the longer path which drifts from obtaining the optimum path. This paper proposes a modified DTW that aims to enhance the dynamic selection of the shortest path when handling equivalent distances. Experiments were conducted using twenty UCR benchmark datasets. Also, the proposed modified DTW result has been compared with the state of the art competitive distance measures which is based on precision, recall and f-measure including the original DTW, Minkowski distance measure and Euclidean distance measure. The results showed that the proposed modified DTW reveal superior results in compared to the standard DTW, either using Minkowski or Euclidean. This can demonstrate the effectiveness of the proposed modification in which optimizing the shortest path has enhanced the performance of clustering. The proposed modified DTW can be used for having good clustering method for any time series data.

Entropy Based Independent Learning in Anonymous Multi-Agent Settings

Efficient sequential matching of supply and demand is a problem of interest in many online to offline services. For instance, Uber, Lyft, Grab for matching taxis to customers; Ubereats, Deliveroo, FoodPanda etc for matching restaurants to customers. In these online to offline service problems, individuals who are responsible for supply (e.g., taxi drivers, delivery bikes or delivery van drivers) earn more by being at the ”right” place at the ”right” time. We are interested in developing approaches that learn to guide individuals to be in the ”right” place at the ”right” time (to maximize revenue) in the presence of other similar ”learning” individuals and only local aggregated observation of other agents states (e.g., only number of other taxis in same zone as current agent).

URSIM: Unique Regions for Sketch Map Interpretation and Matching

We present a method for matching sketch maps to a corresponding metric map, with the aim of later using the sketch as an intuitive interface for human–robot interactions. While sketch maps are not metrically accurate and many details, which are deemed unnecessary, are omitted, they represent the topology of the environment well and are typically accurate at key locations. Thus, for sketch map interpretation and matching, one cannot only rely on metric information. Our matching method first finds the most distinguishable, or unique, regions of two maps. The topology of the maps, the positions of the unique regions, and the size of all regions are used to build region descriptors. Finally, a sequential graph matching algorithm uses the region descriptors to find correspondences between regions of the sketch and metric maps. Our method obtained higher accuracy than both a state-of-the-art matching method for inaccurate map matching, and our previous work on the subject. The state of the art was unable to match sketch maps while our method performed only 10% worse than a human expert.

Re-reconsidering the role of temporal order in spoken word recognition.

Spoken word recognition models incorporate the temporal unfolding of word information by assuming that positional match constrains lexical activation. Recent findings challenge the linearity constraint. In the visual world paradigm, Toscano, Anderson, and McMurray observed that listeners preferentially viewed a picture of a target word's anadrome competitor (e.g., competitor bus for target sub) compared with phonologically unrelated distractors (e.g., well) or competitors sharing an overlapping vowel (e.g., sun). Toscano et al. concluded that spoken word recognition relies on coarse grain spectral similarity for mapping spoken input to a lexical representation. Our experiments aimed to replicate the anadrome effect and to test the coarse grain similarity account using competitors without vowel position overlap (e.g., competitor leaf for target flea). The results confirmed the original effect: anadrome competitor fixation curves diverged from unrelated distractors approximately 275 ms after the onset of the target word. In contrast, the no vowel position overlap competitor did not show an increase in fixations compared with the unrelated distractors. The contrasting results for the anadrome and no vowel position overlap items are discussed in terms of theoretical implications of sequential match versus coarse grain similarity accounts of spoken word recognition. We also discuss design issues (repetition of stimulus materials and display parameters) concerning the use of the visual world paradigm in making inferences about online spoken word recognition.

A Information Retrieval Based on Question and Answering and NER for Unstructured Information Without Using SQL

In today’s world, the availability of information in the form of unstructured data is in abundance. The unstructured information received is more often than not in the form of natural language text. For any defense establishment, the spy data or any sensitive information received may be best utilized when the information can be extracted efficiently and easily. The proposed model is applicable wherever the influx of text-heavy (unstructured data) is high like the information from the world wide web, documents related to a particular domain, or any other source where the information is in the form of natural language. The proposed Natural Language Information Interpretation and Representation System (NLIIRS) accepts the information in the form of natural language text, processes the information and allows the user to retrieve information by rendering questions in natural language. The questions thus asked by the user are responded by NLIIRS in the form of factoid or phrase based answers. In comparison to the conventional question and answering systems the proposed NLIIRS uses the advantages of both named entity recognition as well as sequential pattern matching based answer search technique. The proposed technique helps us to avoid the use of structured query language (SQL) at the back-end for information processing, storage and extraction. The conversion of user query to SQL statements and also storing the unstructured text in the form of relation tables can be avoided by using NLIIRS. By using this approach in our novel text processing algorithm, after every execution step, the pattern matching and extraction process of the answers to the queries becomes concise and faster. The whole system has been designed on natural language tool kit of Stanford University which helped us to generate parts of speech tag, tokenize the data, and forming tree structure. The novel text processing algorithm utilizes the lemmatizer, stemmer and ne_chunker to prepare the text for information retrieval via Q&A. The advantage of this system is that it does not need training. This system will enable the user to retrieve any information of his/her choice from the available unstructured information.

Does developmental prosopagnosia impair identification of other-ethnicity faces?

Current approaches to the diagnosis of developmental prosopagnosia emphasise the perception and identification of same-ethnicity faces. This convention ensures that perceptual impairment arising from developmental prosopagnosia can be distinguished from problems arising from a lack of visual experience with particular facial ethnicities – the so-called ‘Other-Ethnicity Effect’. The present study sought to determine whether the perceptual difficulties seen in developmental prosopagnosia – diagnosed using same-ethnicity faces – extend to other-ethnicity faces. First, we sought to determine whether a group of Caucasian developmental prosopagnosics (N = 15) and typical Caucasian controls (N = 30) had similar experience with same- and other-ethnicity faces during development. All participants therefore completed a contact questionnaire that enquired about their experience of Caucasian, Black, and East Asian faces, at different developmental stages. Importantly, the two groups described very similar levels of visual experience with other-ethnicity faces. Second, we administered a sequential matching task to measure participants' ability to discriminate same- (Caucasian) and other-ethnicity (Black, East Asian) faces. Relative to the experience-matched controls, the prosopagnosics were less accurate at discriminating both same- and other-ethnicity faces, and we found no evidence of disproportionate impairment for same-ethnicity faces. Given that the prosopagnosics and controls had similar opportunity to develop visual expertise for other-ethnicity faces, these results indicate that developmental prosopagnosia impairs recognition of both same- and other-ethnicity faces. The fact that developmental prosopagnosia affects the perception of both same- and other-ethnicity faces suggests that different facial ethnicities engage similar visual processing mechanisms. Our findings support the view that susceptibility to developmental prosopagnosia, and a lack of contact with other-ethnicity faces, contribute independently to the poor recognition of other-ethnicity faces.

A Sequential Matching Framework for Multi-Turn Response Selection in Retrieval-Based Chatbots

We study the problem of response selection for multi-turn conversation in retrieval-based chatbots. The task involves matching a response candidate with a conversation context, the challenges for which include how to recognize important parts of the context, and how to model the relationships among utterances in the context. Existing matching methods may lose important information in contexts as we can interpret them with a unified framework in which contexts are transformed to fixed-length vectors without any interaction with responses before matching. This motivates us to propose a new matching framework that can sufficiently carry important information in contexts to matching and model relationships among utterances at the same time. The new framework, which we call a sequential matching framework (SMF), lets each utterance in a context interact with a response candidate at the first step and transforms the pair to a matching vector. The matching vectors are then accumulated following the order of the utterances in the context with a recurrent neural network (RNN) that models relationships among utterances. Context-response matching is then calculated with the hidden states of the RNN. Under SMF, we propose a sequential convolutional network and sequential attention network and conduct experiments on two public data sets to test their performance. Experiment results show that both models can significantly outperform state-of-the-art matching methods. We also show that the models are interpretable with visualizations that provide us insights on how they capture and leverage important information in contexts for matching.

Pre-hospital advanced airway management for adults with out-of-hospital cardiac arrest: nationwide cohort study

ObjectiveTo determine survival associated with advanced airway management (AAM) compared with no AAM for adults with out-of-hospital cardiac arrest.DesignCohort study between January 2014 and December 2016.SettingNationwide, population based registry in...

Renal Transplantation and Survival Among Patients With Lupus Nephritis: A Cohort Study.

Patients with end-stage renal disease (ESRD) due to lupus nephritis (LN) have high rates of premature death. To assess the potential effect on survival of renal transplant among patients with ESRD due to LN (LN-ESRD) in the United States. Nationwide cohort study. United States Renal Data System, the national database of nearly all patients with ESRD. Patients with incident LN-ESRD who were waitlisted for a renal transplant. First renal transplant was analyzed as a time-varying exposure. The primary outcomes were all-cause and cause-specific mortality. Time-dependent Cox regression analysis was used to estimate the hazard ratio (HR) of these outcomes associated with renal transplant in the primary analysis. Sequential cohort matching was used in a secondary analysis limited to patients with Medicare, which allowed assessment of time-varying covariates. During the study period, 9659 patients with LN-ESRD were waitlisted for a renal transplant, of whom 5738 (59%) had a transplant. Most were female (82%) and nonwhite (60%). Transplant was associated with reduced all-cause mortality (adjusted HR, 0.30 [95% CI, 0.27 to 0.33]) among waitlisted patients. Adjusted HRs for cause-specific mortality were 0.26 (CI, 0.23 to 0.30) for cardiovascular disease, 0.30 (CI, 0.19 to 0.48) for coronary heart disease, 0.41 (CI, 0.32 to 0.52) for infection, and 0.41 (CI, 0.31 to 0.53) for sepsis. Unmeasured factors may contribute to the observed associations; however, the E-value analysis suggested robustness of the results. Renal transplant was associated with a survival benefit, primarily due to reduced deaths from cardiovascular disease and infection. The findings highlight the benefit of timely referral for transplant to improve outcomes in this population. National Institutes of Health.

Conditional Cooperation: Type Stability Across Games

To classify cooperation types, a sequential prisoner's dilemma and a one-shot public goods game with strategy method are convenient experimental setups. We explore the within subject stability of cooperation preferences in these two games. Our results suggest that subjects classified as conditional cooperators in the sequential prisoner's dilemma match others' contributions in the one-shot public goods game to a significantly larger degree compared to other types - indicating a substantial consistency between these two games. Regarding discrete behavioral types, our results support the claim that the sequential prisoner's dilemma performs well in identifying conditional cooperators while it is only an imperfect tool for identifying selfish types.

Left-Side Bias Is Observed in Sequential Matching Paradigm for Face Processing.

The left-side bias refers to how a chimeric face is created from the left side of a face (from the viewer’s perspective) and its mirror image are considered more similar to the original face than a chimeric face created from the right side of the same face and its mirror image. Previous studies investigated the left-side bias by using the chimeric stimuli task, where the original face and chimeric face were presented simultaneously. However, it remains unclear whether left-side bias effect is observed when the original face and chimeric face are presented sequentially. We completed two experiments using the sequential matching paradigm to investigate this issue. The results from both Experiment 1 and 2 showed that participants judged the identical proportion of the left chimeric face and original face was significantly higher than that of the right chimeric face and original face, which implies that the left-side bias effect can be observed in the sequential matching paradigm for face processing.

Investigating local and global effects of surface colours and contours in amodal completion

ABSTRACTWe studied interpretations of partly occluded shapes. Models that account for amodal completion mostly deal with local and global contour characteristics. In the current study, we were interested in the effects of colour on local and global contour completions. In our stimuli, local contour completions comprised simple linear extensions of the partly occluded contours, whereas global contour completions accounted for global shape regularities. Our stimuli were designed such that the visible surface colour could also be completed in a local or global fashion, being consistent or inconsistent with contour completions. We tested the preferred interpretations of the partly occluded shapes by using a sequential matching task. Participants had to judge whether a test shape could be a previously shown partly occluded shape. We found that interpretations of partly occluded shapes depend on both colour and contour characteristics. Additional time bin analyses revealed that for fast responses colour and contour completions already depend on the visible context of the partly occluded shapes, while for slow responses the congruency between colour and contour completions play a role as well.

Reaction Time of Erroneous Responses in the Go/No-Go Paradigm.

Reaction time (RT) of erroneous responses in go/no-go tasks tends to be shorter than RT of correct responses. An opposite difference has been reported ( Halperin, Wolf, Greenblatt, & Young, 1991 ) which could be attributed to differences in go trial probability, or to high memory demand. Two experiments aimed here to test these two explanations, a simultaneous matching task with low memory load (Experiment 1), and a sequential matching task with high memory load (Experiment 2). Go trial probability was also manipulated. Short false positive RT was obtained only in the sequential matching task with high go trial probability, while long false positive RT was obtained in the other three conditions. Low go trial probability and high memory load were both found to be sufficient, by themselves, to create long false positives attributable to confusion. Short false positives in the high go trial probability/low memory load condition were attributed to failure of response inhibition.

Holistic face perception is impaired in developmental prosopagnosia

Individuals with developmental prosopagnosia (DP) have severe difficulties recognising familiar faces. A current debate is whether these face recognition impairments derive from problems with face perception and in particular whether individuals with DP cannot utilize holistic representations of individual faces. To assess this hypothesis, we recorded event-related potentials (ERPs) during a sequential face identity matching task where successively presented pairs of upright faces were either identical or differed with respect to their internal features, their external features, or both. Participants with DP and age-matched controls reported on each trial whether the face pair was identical or different. To track the activation of cortical visual face memory representations, we measured N250r components over posterior face-selective regions. N250r components to full face repetitions were strongly attenuated for DPs as compared to control participants, indicating impaired face identity matching processes in DP. In the Control group, the N250r to full face repetitions was superadditive (i.e., larger than the sum of the two N250r components to partial repetitions of external or internal features). This demonstrates that holistic face representations were involved in identity matching processes. In the DP group, N250r components to full and partial identity repetitions were strictly additive, indicating that the identity matching of external and internal features operated in an entirely part-based fashion, without any involvement of holistic representations. In line with this conclusion, DPs also made a disproportionate number of errors on partial repetition trials, where they often failed to report a change of internal facial features. This suggests an atypical strategy for encoding external features as cues to identity in DP. These results provide direct electrophysiological and behavioural evidence for qualitative differences in the representation of face identity in the occipital-temporal face processing system in developmental prosopagnosia.

Analysis of Arbitrarily Curved Microstrip Lines for Radiated Emission

In the context of printed circuit design, microstrip interconnects pose a great challenge in terms of radiated emission, signal integrity, and intertrace interference. Curved and bent microstrip lines are integral part of such high-frequency circuit design. In this paper, internal fields of an arbitrarily curved microstrip line are calculated using a sequential mode matching technique with piecewise circular discretization. Transverse asymmetry of the electric field is observed due to unequal curvatures of the two side edges of the microstrip line. A dynamic co-ordinate system based on Serret–Frenet reference frame is developed. A simple transmission line model is formulated in this new co-ordinate system to calculate the radiated far fields from the line. The developed model is applied to compute radiation from a sinusoidal line as well as that of a planar spiral. The model is also applied to compute the radiation efficiencies from various microstrip bends and it is observed that circular bends exhibit minimum leakage amongst others. A sinusoidal line and a planar spiral are fabricated and measured. Results are shown to be in good agreement with those predicted by the analytical model.

Effective Identification of Similar Patients Through Sequential Matching over ICD Code Embedding

Evidence-based medicine often involves the identification of patients with similar conditions, which are often captured in ICD (International Classification of Diseases (World Health Organization 2013)) code sequences. With no satisfying prior solutions for matching ICD-10 code sequences, this paper presents a method which effectively captures the clinical similarity among routine patients who have multiple comorbidities and complex care needs. Our method leverages the recent progress in representation learning of individual ICD-10 codes, and it explicitly uses the sequential order of codes for matching. Empirical evaluation on a state-wide cancer data collection shows that our proposed method achieves significantly higher matching performance compared with state-of-the-art methods ignoring the sequential order. Our method better identifies similar patients in a number of clinical outcomes including readmission and mortality outlook. Although this paper focuses on ICD-10 diagnosis code sequences, our method can be adapted to work with other codified sequence data.

Music reading expertise modulates hemispheric lateralization in English word processing but not in Chinese character processing

Music notation and English word reading both involve mapping horizontally arranged visual components to components in sound, in contrast to reading in logographic languages such as Chinese. Accordingly, music-reading expertise may influence English word processing more than Chinese character processing. Here we showed that musicians named English words significantly faster than non-musicians when words were presented in the left visual field/right hemisphere (RH) or the center position, suggesting an advantage of RH processing due to music reading experience. This effect was not observed in Chinese character naming. A follow-up ERP study showed that in a sequential matching task, musicians had reduced RH N170 responses to English non-words under the processing of musical segments as compared with non-musicians, suggesting a shared visual processing mechanism in the RH between music notation and English non-word reading. This shared mechanism may be related to the letter-by-letter, serial visual processing that characterizes RH English word recognition (e.g., Lavidor & Ellis, 2001), which may consequently facilitate English word processing in the RH in musicians. Thus, music reading experience may have differential influences on the processing of different languages, depending on their similarities in the cognitive processes involved.

A robust star identification algorithm with star shortlisting

A star tracker provides the most accurate attitude solution in terms of arc seconds compared to the other existing attitude sensors. When no prior attitude information is available, it operates in “Lost-In-Space (LIS)” mode. Star pattern recognition, also known as star identification algorithm, forms the most crucial part of a star tracker in the LIS mode. Recognition reliability and speed are the two most important parameters of a star pattern recognition technique. In this paper, a novel star identification algorithm with star ID shortlisting is proposed. Firstly, the star IDs are shortlisted based on worst-case patch mismatch, and later stars are identified in the image by an initial match confirmed with a running sequential angular match technique. The proposed idea is tested on 16,200 simulated star images having magnitude uncertainty, noise stars, positional deviation, and varying size of the field of view. The proposed idea is also benchmarked with the state-of-the-art star pattern recognition techniques. Finally, the real-time performance of the proposed technique is tested on the 3104 real star images captured by a star tracker SST-20S currently mounted on a satellite. The proposed technique can achieve an identification accuracy of 98% and takes only 8.2 ms for identification on real images. Simulation and real-time results depict that the proposed technique is highly robust and achieves a high speed of identification suitable for actual space applications.