Potential Ambiguity Research Articles

Ambiguity in medical concept normalization: An analysis of types and coverage in electronic health record datasets.

Normalizing mentions of medical concepts to standardized vocabularies is a fundamental component of clinical text analysis. Ambiguity-words or phrases that may refer to different concepts-has been extensively researched as part of information extraction from biomedical literature, but less is known about the types and frequency of ambiguity in clinical text. This study characterizes the distribution and distinct types of ambiguity exhibited by benchmark clinical concept normalization datasets, in order to identify directions for advancing medical concept normalization research. We identified ambiguous strings in datasets derived from the 2 available clinical corpora for concept normalization and categorized the distinct types of ambiguity they exhibited. We then compared observed string ambiguity in the datasets with potential ambiguity in the Unified Medical Language System (UMLS) to assess how representative available datasets are of ambiguity in clinical language. We found that <15% of strings were ambiguous within the datasets, while over 50% were ambiguous in the UMLS, indicating only partial coverage of clinical ambiguity. The percentage of strings in common between any pair of datasets ranged from 2% to only 36%; of these, 40% were annotated with different sets of concepts, severely limiting generalization. Finally, we observed 12 distinct types of ambiguity, distributed unequally across the available datasets, reflecting diverse linguistic and medical phenomena. Existing datasets are not sufficient to cover the diversity of clinical concept ambiguity, limiting both training and evaluation of normalization methods for clinical text. Additionally, the UMLS offers important semantic information for building and evaluating normalization methods. Our findings identify 3 opportunities for concept normalization research, including a need for ambiguity-specific clinical datasets and leveraging the rich semantics of the UMLS in new methods and evaluation measures for normalization.

Multidimensional Scientometric indicators for the detection of emerging research topics

The detection of emerging research topics (ERTs) is an important step in the promotion of potentially promising research. In this paper, we first distinguish the concept of ERT from that of common-related topics. We discuss multi-dimensional and practical bibliometric indicators to discover high-impact ERTs at a fine level of granularity. To this end, we focus on three objectives. First, we determine a method for identifying research topics from scholarly publications. Second, we developed a method for uncovering ERTs. Third, we conduct an experimental analysis to demonstrate the operationalization of our method. High-impact ERTs are selected based on the advice of field experts. Then, we divide the identified ERTs into seven patterns and propose different research and development (R&D) strategies for each topic. In general, previous studies have mainly focused on the attributes of “novelty” and “growth.” Compared with extant ERT identification analysis, this study pays more attention to the future economic and social impact of ERTs and the reduction of uncertainty. This article is the first attempt to devise an ERT detection framework by comprehensively measuring its five characteristics (radical novelty, relatively fast growth, persistence and coherence, potential high impact, and uncertainty and ambiguity reduction) and proposing feasible operational indicators and processes. Thus, different R&D layout strategies for different economic and social-impact topics are outlined herein, which contribute significantly to the development of science and technology policies. The evidence presented suggests that our methodology can be used by decision makers to evaluate emerging scientific research.

TCANet: Triple Context-Aware Network for Weakly Supervised Object Detection in Remote Sensing Images

Weakly supervised object detection (WSOD) in remote sensing images (RSI) plays an essential role in RSI understanding applications. Currently, predominant works are inclined to first activate the most discriminative region and then pursue the whole object by analyzing the context information of the activated region. However, the most discriminative region usually only covers a small crucial part. Besides, many same-class instances often appear in adjacent locations. In such a case, treating proposals of large spatial overlap as the same-class instances not only introduces potential ambiguities but also misleads the detection model to recognize multiple adjacent instances as one object instance. To address these challenges, a novel triple context-aware network (TCANet) is proposed to learn complementary and discriminative visual patterns for WSOD in RSIs. Specifically, a global context-aware enhancement (GCAE) module is first designed to activate the features of the whole object by capturing the global visual scene context. Then, a dual-local context residual (DLCR) module is further developed to capture the instance-level discriminative cues by leveraging the semantic discrepancy of the local context. Furthermore, an effective adaptive-weighted refinement loss is integrated into the DLCR module to reduce the ambiguities in the label propagating process. The collaboration of GCAE and DLCR formulates a unique TCANet that can be learned in an end-to-end manner. Comprehensive experiments are carried out on the challenging NWPU VHR-10.v2 and DIOR data sets. We achieve a 58.8% mAP and a 25.8% mAP on the NWPU VHR-10.v2 and DIOR data sets, respectively, which both significantly outperform the state of the arts.

Space, sound and sedition on the Royal Naval ship, 1756-1815

This article examines sonic forms of protest aboard British naval ships between 1756 and 1815. During this period, naval seamen murmured, muttered, cheered, hissed and chattered as they congregated below and above deck. These sounds required constant interpretation on the part of officers, and a failure to do so correctly could have severe consequences. Maritime labourers, this article finds, well understood the potential ambiguity of shipboard soundscapes as well as the acousmatic potential of the ship as a built environment, which they used to their advantage through a careful manipulation of space and sound. I analyse the orchestration of the communal soundscapes which seamen created, and consider the specific shipboard spaces in which these sounds were made from and projected to. In placing these sounds in their spatial and social contexts, it is possible to glimpse an alternative order on British naval vessels, and to better understand cultures of sonic protest during the long eighteenth century.

Deep understanding of shopper behaviours and interactions using RGB-D vision

In retail environments, understanding how shoppers move about in a store’s spaces and interact with products is very valuable. While the retail environment has several favourable characteristics that support computer vision, such as reasonable lighting, the large number and diversity of products sold, as well as the potential ambiguity of shoppers’ movements, mean that accurately measuring shopper behaviour is still challenging. Over the past years, machine-learning and feature-based tools for people counting as well as interactions analytic and re-identification were developed with the aim of learning shopper skills based on occlusion-free RGB-D cameras in a top-view configuration. However, after moving into the era of multimedia big data, machine-learning approaches evolved into deep learning approaches, which are a more powerful and efficient way of dealing with the complexities of human behaviour. In this paper, a novel VRAI deep learning application that uses three convolutional neural networks to count the number of people passing or stopping in the camera area, perform top-view re-identification and measure shopper–shelf interactions from a single RGB-D video flow with near real-time performances has been introduced. The framework is evaluated on the following three new datasets that are publicly available: TVHeads for people counting, HaDa for shopper–shelf interactions and TVPR2 for people re-identification. The experimental results show that the proposed methods significantly outperform all competitive state-of-the-art methods (accuracy of 99.5% on people counting, 92.6% on interaction classification and 74.5% on re-id), bringing to different and significative insights for implicit and extensive shopper behaviour analysis for marketing applications.

Feasibility Study for the Application of Synthetic Aperture Radar for Coastal Erosion Rate Quantification Across the Arctic

The applicability of optical satellite data to quantify coastal erosion across the Arctic is limited due to frequent cloud cover. Synthetic Aperture Radar (SAR) may provide an alternative. The interpretation of SAR data for coastal erosion monitoring in Arctic regions is, however, challenging due to issues of viewing geometry, ambiguities in scattering behaviour and inconsistencies in acquisition strategies. In order to assess SAR applicability, we have investigated data acquired at three different wavelengths (X-, C-, L-band; TerraSAR-X,Sentinel-1,ALOS PALSAR 1/2). In a first step we developed a pre-processing workflow which considers viewing geometry issues (shoreline orientation, incidence angle relationships with respect to different landcover types). We distinguish between areas with foreshortening along cliffs facing the sensor, radar shadow along cliffs facing away and traditional land-water boundary discrimination. Results are compared to retrievals from Landsat trends. Four regions which feature high erosion rates have been selected. All three wavelengths have been investigated for Kay Point (Canadian Beaufort Sea Coast). C- and L-band have been studied at all sites, including also Herschel Island (Canadian Beaufort Sea Coast), Varandai (Barents Sea Coast, Russia), and Bykovsky Peninsula (Laptev Sea coast, Russia). Erosion rates have been derived for a one-year period (2017-2018) and in case of L-band also over 11 years (2007-2018). Results indicate applicability of all wavelengths, but acquisitions need to be selected with care to deal with potential ambiguities in scattering behaviour. Furthermore, incidence angle dependencies need to be considered for discrimination of the land-water boundary in case of L- and C-band. However, L-band has the lowest sensitivity to wave action and relevant future missions are expected to be of value for coastal erosion monitoring. The utilization of trends derived from Landsat is also promising for efficient long-term trend retrieval. The high spatial resolution of TerraSAR-X staring spot light mode (<1m) also allows the use of radar shadow for cliff-top monitoring in all seasons. Derived retreat rates agree with rates available from other data sources, but the applicability for automatic retrieval is partially limited. The derived rates suggest an increase of erosion at all four sites in recent years, but uncertainties are also high.

Novel screening with two bodies: summing the ladder in disformal scalar-tensor theories

When augmenting our cosmological models or gravitational theories with an additional light scalar field, any coupling between matter and this scalar can affect the orbital motion of binary systems. Ordinarily, the new force mediated by the scalar can be naturally the same order of magnitude as the usual gravitational force and therefore is tightly constrained. We show that a disformal coupling between the scalar and matter can lead to a novel screening mechanism in which these fifth forces are suppressed by several orders of magnitude at sufficiently small separations and large relative velocities (such as solar system scales). This is a result of resumming a class of ladder diagrams, which suppresses the propagation of scalar signals between the two bodies. Moreover, we are able to relate potential ambiguities in this resummation to non-perturbative effects (which are invisible to perturbation theory). As a result, solar system tests and future gravitational wave observations can now be used to place meaningful constraints on scalar-tensor theories with disformal couplings. We exemplify this using observational bounds on the precession of planetary orbits.

Event-related potentials reveal increased dependency on linguistic context due to cognitive aging.

Whereas executive functions are known to be closely tied to successful language processing in children and younger adults, less is known about how age-related decline in these functions affects language processing in elderly adults. Because the abilities to use linguistic context and resolve potential ambiguities such as between an idiom's figurative and literal meaning depend on executive functions, we investigated this issue by examining elderly adults' processing of idioms in context. We recorded event-related potentials of 25 younger (age 18-28) and 25 elderly adults (age 61-74) while they read literal sentences and sentences containing an idiom (e.g., the Dutch idiom to walk against the lamp, meaning "to get caught"), each preceded by a neutral or predictive context sentence. Participants' use of context was hypothesized to relate to working memory capacity, while their ability to disambiguate idioms was hypothesized to depend on inhibition skills. Both groups showed facilitated processing for idioms compared with literal sentences and for sentences preceded by predictive compared with neutral contexts, indexed by a reduced N400. However, only elderly adults showed an increased P600 for literal but not idiomatic sentences preceded by a predictive context, suggesting that they rely on linguistic context when a sentence's meaning needs to be computed word by word, but not when a large part is retrieved from memory (as in idioms). Our findings suggest that in both younger and elderly adults processing literal sentences requires more cognitive effort than processing idiomatic sentences, and that cognitive aging affects language when processing is effortful. (PsycInfo Database Record (c) 2020 APA, all rights reserved).

Investigation of Neutral Losses and the Citrulline Effect for Modified H4 N-Terminal Pentapeptides.

Tandem mass spectrometry is an indispensable tool in proteomics used for protein sequencing and quantitation. On the basis of the sequential fragments usually generated from peptide ions via collision-induced dissociation, electron-transfer dissociation, or a combination of the two, probabilistic database search engines could be used for the identification of the peptides. The correct localization of posttranslational modifications (PTMs) poses a more challenging problem than the general identification of proteins. Histones are involved in the regulation of DNA transcription via the wealth of PTMs on their N-terminal tail. In this study, we analyzed the histone H4 peptide SGRGK incorporating four different posttranslational modifications: citrullination, acetylation, phosphorylation, and arginine methylation at various positions. The pentapeptides model the enzymatic cleavage of the N-terminal tail of human histone H4 protein by LysC protease. Fragmentation of the peptides was investigated using higher-energy collisional dissociation (HCD), electron-transfer dissociation (ETD), and electron-transfer higher-energy collisional dissociation (EThcD) on an ultrahigh resolution and mass accuracy instrument. We found that while all three techniques have their unique characteristics, advantages, and pitfalls, EThcD generated the most fragment ion-rich spectra. Despite potential ambiguities regarding exact fragment identities, full sequence coverage and PTM mapping may also be achievable. We also found novel neutral losses from the charge-reduced precursors characteristic to citrullination in ETD and EThcD which may be used in proteomic applications. N-Terminal acetylation and arginine methylation could also be confirmed by their characteristic neutral losses from the charge-reduced precursors.

The influence of object structure on visual short-term memory for multipart objects.

Numerous studies have shown that more visual features can be stored in visual short-term memory (VSTM) when they are encoded from fewer objects (Luck & Vogel, 1997, Nature, 390, 279-281; Olson & Jiang, 2002, Perception & Psychophysics, 64[7], 1055-1067). This finding has been consistent for simple objects with one surface and one boundary contour, but very few experiments have shown a clear performance benefit when features are organized as multipart objects versus spatially dispersed single-feature objects. Some researchers have suggested multipart object integration is not mandatory because of the potential ambiguity of the display (Balaban & Luria, 2015, Cortex, 26(5), 2093-2104; Luria & Vogel, 2014, Journal of Cognitive Neuroscience, 26[8], 1819-1828). For example, a white bar across the middle of a red circle could be interpreted as two objects, a white bar occluding a red circle, or as a single two-colored object. We explore whether an object benefit can be found by disambiguating the figure-ground organization of multipart objects using a luminance gradient and linear perspective to create the appearance of a unified surface. Also, we investigated memory for objects with a visual feature indicated by a hole, rather than an additional surface on the object. Results indicate the organization of multipart objects can influence VSTM performance, but the effect is driven by how the specific organization allows for use of global ensemble statistics of the memory array rather than a memory benefit for local object representations.

Localization in 3GPP LTE Based on One RTT and One TDOA Observation

We study the fundamental problem of fusing one round trip time (RTT) observation associated with a serving base station with one time-difference of arrival (TDOA) observation associated to the serving base station and a neighbor base station to localize a 2-D mobile station (MS). This situation can arise in 3GPP Long Term Evolution (LTE) when the number of reported cells of the mobile station is reduced to a minimum in order to minimize the signaling costs and to support a large number of devices. The studied problem corresponds geometrically to computing the intersection of a circle with a hyperbola, both with measurement uncertainty, which generally has two equally likely solutions. We derive an analytical representation of these two solutions that fits a filter bank framework that can keep track of different hypothesis until potential ambiguities have been resolved. Further, a performance bound for the filter bank is derived. The proposed filter bank is first evaluated in a simulated scenario, where the set of serving and neighbor base stations is changing in a challenging way. The filter bank is then evaluated on real data from a field test, where the result shows a precision better than 40 m 95% of the time.

Unambiguous and precise correlation receiver for binary offset carrier modulated signal

SummaryThe binary offset carrier (BOC) modulated signal can improve the positioning accuracy and increase the multipath resistance in global navigation satellite system (GNSS), and it may cause potential ambiguity in the process of signal acquisition and code tracking. In this paper, a simple but efficient unambiguous receiver is firstly proposed for multiple side‐peaks mitigation by implementing correlation of the received BOC signal with local sine wave instead of square wave used at the transmitter. Moreover, the potential degradation of sharpness of the nonlinear correlation induced by the sine wave is well compensated by optimizing the early‐to‐late spacing. The other reason leading to ambiguity is the multipath propagation, so we further propose a maximum likelihood (ML) estimator with Newton iteration method, where the received GNSS signal is modeled via the line‐of‐sight (LOS) component and the first‐arrived non‐line‐of‐sight (NLOS) component. Finally, the analytical expression of multipath propagation Cramer‐Rao bound is derived for the designed ML estimator. Simulation results indicate that compared with the conventional BOC modulation, the proposed sine wave receiver can achieve unambiguous and more precise code tracking performance and thus turns out to be more robust to multipath propagation.

MEDLL On-Strobe Correlator: A Combined Anti-multipath Technique for GNSS Signal Tracking

To reduce the operational complexity of the multipath estimating delay lock loop (MEDLL) and improve its anti-multipath performance for strobe correlators, a combination anti-multipath scheme, namely, the MEDLL on-strobe correlation technique, is proposed for global navigation satellite system (GNSS) signal processing. Short-delay multipath rays are separated from the strobe correlation function by the MEDLL mechanism; the dot product between the estimation residue and the standard correlation function or the BOC-PRN correlation function is then computed to eliminate the potential tracking ambiguity. Finally, this non-coherent combination result is sent to the loop filter to obtain anti-multipath code tracking. The proposed method is analysed via simulator data with a software receiver under different front-end bandwidth conditions. The results corroborate the better multipath mitigation capability and lower computational burden, although it is still difficult to eliminate all multipath interference, especially when the front-end bandwidth is insufficient.

Human leucocyte antigen diversity: A biological gift to escape infections, no longer a barrier for haploidentical Hemopoietic Stem Cell Transplantation.

Since the beginning of life, every multicellular organism appeared to have a complex innate immune system although the adaptive immune system, centred on lymphocytes bearing antigen receptors generated by somatic recombination, arose in jawed fish approximately 500 million years ago. The major histocompatibility complex MHC, named the Human leucocyte antigen (HLA) system in humans, represents a vital function structure in the organism by presenting pathogen-derived peptides to T cells as the main initial step of the adaptive immune response. The huge level of polymorphism observed in HLA genes definitely reflects selection, favouring heterozygosity at the individual or population level, in a pathogen-rich environment, although many are located in introns or in exons that do not code for the antigen-biding site of the HLA. Over the past three decades, the extent of allelic diversity at HLA loci has been well characterized using high-resolution HLA-DNA typing and the number of new HLA alleles, produced through next-generation sequencing methods, is even more rapidly increasing. The level of the HLA system polymorphism represents an obstacle to the search of potential compatible donors for patients affected by haematological disease proposed for a hematopoietic stem cell transplant (HSCT). Data reported in literature clearly show that antigenic and/or allelic mismatches between related or unrelated donors and patients influences the successful HSCT outcome. However, the recent development of the new transplant strategy based on the choice of haploidentical donors for HSCT is questioning the role of HLA compatibility, since the great HLA disparities present do not worsen the overall clinical outcome. Nowadays, NGS has contributed to define at allelic levels the HLA polymorphism and solve potential ambiguities. However, HLA functions and tissue typing probably need to be further investigated in the next future, to understand the reasons why in haploidentical transplants the presence of a whole mismatch haplotype between donors and recipients, both the survival rate and the incidence of acute GvHD or graft rejection are similar to those reported for unrelated HSCTs.

The discursive construction of creativity as work in a tertiary art and design environment

Central to most research in the field of creativity is the perception that creativity is an external and essentialist phenomenon. Recent studies, particularly in the area of art and design education, are beginning to question this understanding and seek alternative methods for exploring creativity. This paper takes the view that perceptions of creativity are historically and discursively constructed and that cultural shifts in the early twentieth century have more recently constituted the western understanding of creativity through a discourse of work. As an example, the paper will use a multi-perspectival analytical approach to explore the discursive construction of creativity as work in the situated context of a tertiary art and design studio environment. The paper concludes with a discussion of complications that may arise in the tertiary art and design environment as a result of the potential ambiguity created by the discourse of creativity as work.

18. An unusual PET project: large vessel vasculitis presenting as lower limb claudication in the absence of aortitis

IntroductionRheumatologists are increasingly aware of extracranial giant cell arteritis (GCA), namely large vessel vasculitis (LVV) involving the aorta and its branches. It is uncommon for patients to present with claudication as their initial complaint. We present an unusual case of femoral arteritis presenting with lower limb claudication. PET-CT demonstrated increased uptake bilaterally in the femoral arteries with typical hypoechoic haloes on Doppler ultrasound. There was no evidence of aortitis. We also illustrate the diagnostic challenge differentiating between vasculitis and atherosclerosis on PET-CT and how steroid-therapy reduces the sensitivity PET imaging.Case descriptionA 57-year-old lady with known hypertension presented to her local hospital with a 3-year history of worsening claudication in her lower limbs. Her exercise tolerance was limited to 50 metres over the past 2 months and she had rest pain. Other symptoms included widespread musculoskeletal pain, chest pain, headaches and jaw pain on mastication. Lower limb Doppler ultrasound demonstrated significant stenosis of the distal femoral arteries bilaterally with hypoechoic haloes typical for vasculitis. Immunology tests were all negative but inflammatory markers were raised (ESR 43 mm/h, CRP 14 mg/L). In view of the Doppler findings and GCA symptoms she was started on prednisolone 60mg. The prednisolone was held 2 days before a PET-CT which demonstrated mild uptake in both femoral arteries with no evidence of aortitis. Her CT angiogram showed significant diffuse atheromatous disease in the superficial femoral and popliteal arteries bilaterally. In view of this, the PET-CT uptake was thought to be in keeping with atherosclerosis rather than vasculitis. Her prednisolone was therefore stopped and she was transferred to a tertiary vascular centre for further management. The vascular team at our hospital were still concerned about the possibility of vasculitis and a second rheumatology opinion was sought. Her inflammatory markers continued to rise (ESR 76 mm/h, CRP 29 mg/L). It was felt that the PET-CT results may have been affected by high-dose prednisolone which was temporarily held. The PET-CT was therefore repeated having been off steroids for 4 weeks. This demonstrated increased uptake in the superficial femoral and profunda arteries when compared to her previous scan. All her images were reviewed and the diagnosis was felt to be in keeping with LVV. Furthermore, she had a good clinical response to 40mg prednisolone and methotrexate was subsequently added.DiscussionClassical GCA typically presents with cranial symptoms. Extracranial symptoms such claudication can occur although only 4% of patients fall into this category. In our patient, femoral arteritis presented with lower limb claudication. Peripheral limb ischaemia and/or aorta involvement is associated with a slightly younger demographic of LVV (<60 years). Initially, there was diagnostic uncertainty given her raised inflammatory markers and hypoechoic femoral artery haloes on Doppler ultrasound, yet diffuse atherosclerosis on the CT angiogram. Hypoechoic haloes and multiple short segment occlusions are more typically seen in vasculitis rather than atherosclerotic disease. Accelerated atherosclerosis is common in primary vasculitides. Despite establishing the diagnosis of LVV by ultrasound in this case, the sensitivity for this in the common femoral artery is < 17%, and PET-CT is preferred. EULAR recommendations for LVV diagnosis include ultrasound and PET-CT. PET-CT was performed twice in this patient because the initial scan was performed following temporary cessation of high-dose steroids, which can decrease the sensitivity of PET-CT. The first PET-CT showed only mild uptake in the femoral arteries which could be consistent with atherosclerosis. Interestingly, PET-CT has been used to identify plaques vulnerable to rupture bed on FDG-avidity. Recent studies have utilised PET-CT to quantify the burden of atherosclerotic disease to help risk stratify patients accurately. This potential diagnostic ambiguity between vasculitis and atherosclerosis on PET-CT reinforces the importance of remaining off steroids around the time of PET imaging where possible.Key learning pointsThis case sheds light on LVV through several interesting perspectives. Firstly, it is unusual for LVV to present with claudication in the lower limbs in the absence of aortitis, demonstrating the variety of ways in which the same pathophysiological mechanism can present clinically. We also highlight the initial diagnostic challenge, as mild uptake in the femoral arteries on PET-CT can be consistent with atherosclerosis. However, with typical findings of hypoechoic haloes on Doppler ultrasound and raised inflammatory markers, clinically this was in keeping with LVV. Interestingly, a repeat PET-CT off steroids demonstrated increased FDG-avidity in the affected areas. This is important as even holding steroids for 2 days before a PET-CT affected the results of the study. This case adds to the growing number of atypical extracranial presentations of LVV and provides useful insight for future possible cases.Conflict of interestThe authors declare no conflicts of interest.

Unlocking Radiology Reporting Data: an Implementation of Synoptic Radiology Reporting in Low-Dose CT Cancer Screening.

Cancer Care Ontario (CCO) is the clinical advisor to the Ontario Ministry of Health and Long-Term Care for the funding and delivery of cancer services. Data contained in radiology reports are inaccessible for analysis without significant manual cost and effort. Synoptic reporting includes highly structured reporting and discrete data capture, which could unlock these data for clinical and evaluative purposes. To assess the feasibility of implementing synoptic radiology reporting, a trial implementation was conducted at one hospital within CCO's Lung Cancer Screening Pilot for People at High Risk. This project determined that it is feasible to capture synoptic data with some barriers. Radiologists require increased awareness when reporting cases with a large number of nodules due to lack of automation within the system. These challenges may be mitigated by implementation of some report automation. Domains such as pathology and public health reporting have addressed some of these challenges with standardized reports based on interoperable standards, and radiology could borrow techniques from these domains to assist in implementing synoptic reporting. Data extraction from the reports could also be significantly automated to improve the process and reduce the workload in collecting the data. RadLex codes aided the difficult data extraction process, by helping label potential ambiguity with common terms and machine-readable identifiers.

An NLP approach for cross-domain ambiguity detection in requirements engineering

During requirements elicitation, different stakeholders with diverse backgrounds and skills need to effectively communicate to reach a shared understanding of the problem at hand. Linguistic ambiguity due to terminological discrepancies may occur between stakeholders that belong to different technical domains. If not properly addressed, ambiguity can create frustration and distrust during requirements elicitation meetings, and lead to problems at later stages of development. This paper presents a natural language processing approach to identify ambiguous terms between different domains, and rank them by ambiguity score. The approach is based on building domain-specific language models, one for each stakeholders’ domain. Word embeddings from each language model are compared in order to measure the differences of use of a term, thus estimating its potential ambiguity across the domains of interest. We evaluate the approach on seven potential elicitation scenarios involving five domains. In the evaluation, we compare the ambiguity rankings automatically produced with the ones manually obtained by the authors as well as by multiple annotators recruited through Amazon Mechanical Turk. The rankings produced by the approach lead to a maximum Kendall’s Tau of 88%. However, for several elicitation scenarios, the application of the approach was unsuccessful in terms of performance. Analysis of the agreement among annotators and of the observed inaccuracies offer hints for further research on the relationship between domain knowledge and natural language ambiguity.

Using consensus from experts to inform a shared understanding of subjective terms.

Consensus methods such as Delphi studies or the group nominal method have long been used in healthcare research to develop services, processes or policies and inform further research. However, concept analysis and meta-synthesis tools are used more frequently to seek a collective understanding of subjective terms. To examine the use of consensus methods to develop linguistic clarity in healthcare research. The authors argue that consensus methods are appropriate for determining linguistic clarity when researching subjective terms. The paper includes a sample research design that incorporates this approach. Consensus methods, supported by interpretive synthesis of the concept and research, can enrich our understanding of subjective terms used in healthcare research. Understanding the importance of linguistic clarity is an important step for healthcare researchers. Consensus methods, if managed effectively and conducted in line with the appropriate research guidelines, can bring a richer understanding to concepts. This paper presents a research example that incorporates the use of a consensus method and which healthcare researchers can use to reduce the potential ambiguity of subjective terms in their research.

Co-construction of metaphors in Estonian conversation

The study1 examines how metaphors are deliberately used in spoken interaction, taking into account their context and combining the analysis of conversational data with new developments in metaphor studies. In doing this, we present Estonian examples of extended metaphors co-constructed in the course of interaction. Steen's framework of deliberate metaphor theory (DMT) presents a useful paradigm to investigate the understudied area in a new way, especially in a language where deliberate metaphors have not yet been studied.In conversation, metaphorical creativity manifests itself in how metaphors are used and spontaneously adapted in the flow of talk (Cameron, 2007), often evoking humour in the process. Our second aim in the study has thus been to demonstrate how metaphor use overlaps with the use of humour in conversation. We suggest that metaphor-related words - central to the procedure of identifying deliberate metaphors (DMIP; see Steen, 2008, 2011, 2013, 2015), and understood here as contextually embedded words which bring along potential ambiguity – serve either as indicators of cross-domain mapping, as triggers of humorous effects, or sometimes as both at the same time.Since we assume such deliberate use of metaphors, at least to some extent, contributes to the cultural communication style, as defined in the introduction to this issue, we draw attention to the ways Estonian speakers employ them. This is evident through the unique language-specific references, for example metaphors built on proverbs or phraseology.