Location Of Entities Research Articles

Centroidal Localization Game

One important problem in a network $G$ is to locate an (invisible) moving entity by using distance-detectors placed at strategical locations in $G$. For instance, the famous metric dimension of a graph $G$ is the minimum number $k$ of detectors placed in some vertices $\{v_1,\cdots,v_k\}$ such that the vector $(d_1,\cdots,d_k)$ of the distances $d(v_i,r)$ between the detectors and the entity's location $r$ allows to uniquely determine $r$ for every $r \in V(G)$. In a more realistic setting, each device does not get the exact distance to the entity's location. Rather, given locating devices placed in $\{v_1,\cdots,v_k\}$, we get only relative distances between the moving entity's location $r$ and the devices (roughly, for every $1\leq i,j\leq k$, it is provided whether $d(v_i,r) >$, $<$, or $=$ to $d(v_j,r)$). The centroidal dimension of a graph $G$ is the minimum number of devices required to locate the entity, in one step, in this setting.In this paper, we consider the natural generalization of the latter problem, where vertices may be probed sequentially (i.e., in several steps) until the moving entity is located. Roughly, at every turn, a set $\{v_1,\cdots,v_k\}$ of vertices are probed and then the relative order of the distances between the vertices $v_i$ and the current location $r$ of the moving entity is given. If it not located, the moving entity may move along one edge. Let $\zeta^* (G)$ be the minimum $k$ such that the entity is eventually located, whatever it does, in the graph $G$. We first prove that $\zeta^* (T)\leq 2$ for every tree $T$ and give an upper bound on $\zeta^*(G\square H)$ for the cartesian product of graphs $G$ and $H$. Our main result is that $\zeta^* (G)\leq 3$ for any outerplanar graph $G$. We then prove that $\zeta^* (G)$ is bounded by the pathwidth of $G$ plus 1 and that the optimization problem of determining $\zeta^* (G)$ is NP-hard in general graphs. Finally, we show that approximating (up to a small constant distance) the location of the robber in the Euclidean plane requires at most two vertices per turn.

Emotion metaphors in Spanish retain aspects of spatial meaning

AbstractPrevious work has shown that the abstract use of the spatial prepositionsinandonretains spatial meaning, such as containment and support that includes the control relationship between a located object (the figure) and a reference object (the landmark/ground) (Feist & Gentner, 2003;Talmy, 1983). We extend these ideas to the case of metaphorical descriptions of emotion in Spanish—some of them featuring the emotion as a located entity in the person’s body, others featuring emotion as the ground in which the person’s body stands. Two rating experiments show that people judge emotions in Spanish as more controllable when they are described as located entities (the figure) than when they are described as grounds. We conclude that functional elements of the spatial meaning of the prepositionenin Spanish are extended to abstract uses in metaphor, affecting the perceived controllability of emotions.

Machine learning and natural language processing on the patent corpus: Data, tools, and new measures

AbstractDrawing upon recent advances in machine learning and natural language processing, we introduce new tools that automatically ingest, parse, disambiguate, and build an updated database using U.S. patent data. The tools identify unique inventor, assignee, and location entities mentioned on each granted U.S. patent from 1976 to 2016. We describe data flow, algorithms, user interfaces, descriptive statistics, and a novelty measure based on the first appearance of a word in the patent corpus. We illustrate an automated coinventor network mapping tool and visualize trends in patenting over the last 40 years. Data and documentation can be found at https://console.cloud.google.com/launcher/partners/patents-public-data.

A Finding Aid for The Equity

Bibliothèque et Archives Nationales du Québec digitally scanned and converted to text a large collection of newspapers to create a resource of tremendous potential value to historians. Unfortunately, the text files are difficult to search reliably due to many errors caused by the optical character recognition (OCR) text conversion process. 
 This digital history project applied natural language processing in an R language computer program to create a new and useful index of this corpus of digitized content despite OCR related errors. The project used editions of The Equity, published in Shawville, Quebec since 1883. 
 The program extracted the names of all the person, location and organization entities that appeared in each edition. Each of the entities was cataloged in a database and related to the edition of the newspaper it appeared in. The database was published to a public website to allow other researchers to use it.
 The resulting index or finding aid allows researchers to access The Equity in a different way than just full text searching. People, locations and organizations appearing in the Equity are listed on the website and each entity links to a page that lists all of the issues that entity appeared in as well as the other entities that may be related to it.
 Rendering the text files of each scanned newspaper into entities and indexing them in a database allows the content of the newspaper to be interacted with by entity name and type rather than just a set of large text files.
 Website: http://www.jeffblackadar.ca/graham_fellowship/corpus_entities_equity/

Should EU VAT Apply the Recharge Method in the Place of Supply Rules for B2B Services?

An OECD working party recently assessed several approaches for dealing with the issue of where to tax B2B services and intangibles acquired by multiple location entities, i.e., taxable persons with a head office and one or more other establishments in different jurisdictions, for consumption tax purposes. Of the two main approaches identified - the direct use method and the recharge method - EU VAT applies the direct use method. In this article, I will discuss both the direct use method applied in EU VAT (section 2) and the recharge method suggested by the OECD (section 3). After comparing these two methods using an example case (section 4), I will further examine the recharge method (section 5) and conclude on what method should be applied in EU VAT (section 6).

Location detection and disambiguation from twitter messages

A remarkable amount of Twitter messages are generated every second. Detecting the location entities mentioned in these messages is useful in text mining applications. Therefore, techniques for extracting the location entities from the Twitter textual content are needed. In this work, we approach this task in a similar manner to the Named Entity Recognition (NER) task, but we focus only on locations, while NER systems detect names of persons, organizations, locations, and sometimes more (e.g., dates, times). But, unlike NER systems, we address a deeper task: classifying the detected locations into names of cities, provinces/states, and countries in order to map them into physical locations. We approach the task in a novel way, consisting in two stages. In the first stage, we train Conditional Random Fields (CRF) models that are able to detect the locations mentioned in the messages. We train three classifiers: one for cities, one for provinces/states, and one for countries, with various sets of features. Since a dataset annotated with this kind of information was not available, we collected and annotated our own dataset to use for training and testing. In the second stage, we resolve the remaining ambiguities, namely, cases when there exists more than one place with the same name. We proposed a set of heuristics able to choose the correct physical location in these cases. Our two-stage model will allow a social media monitoring system to visualize the places mentioned in Twitter messages on a map of the world or to compute statistics about locations. This kind of information can be of interest to business or marketing applications.

A neural joint model for entity and relation extraction from biomedical text

BackgroundExtracting biomedical entities and their relations from text has important applications on biomedical research. Previous work primarily utilized feature-based pipeline models to process this task. Many efforts need to be made on feature engineering when feature-based models are employed. Moreover, pipeline models may suffer error propagation and are not able to utilize the interactions between subtasks. Therefore, we propose a neural joint model to extract biomedical entities as well as their relations simultaneously, and it can alleviate the problems above.ResultsOur model was evaluated on two tasks, i.e., the task of extracting adverse drug events between drug and disease entities, and the task of extracting resident relations between bacteria and location entities. Compared with the state-of-the-art systems in these tasks, our model improved the F1 scores of the first task by 5.1% in entity recognition and 8.0% in relation extraction, and that of the second task by 9.2% in relation extraction.ConclusionsThe proposed model achieves competitive performances with less work on feature engineering. We demonstrate that the model based on neural networks is effective for biomedical entity and relation extraction. In addition, parameter sharing is an alternative method for neural models to jointly process this task. Our work can facilitate the research on biomedical text mining.

Get into the spirit of a location by mining user-generated travelogues

User-generated travelogues have contributed abundant location representative information (e.g. attracting scenic spots, activities, and local customs), which can greatly facilitate people in trip planning and destination understanding applications. Existing work on location information extraction from user-generated travelogues has primarily focused on the contents, while in this work, we resolve both the contents and structures of travelogues, as well as investigating the interplay of the two. We propose a two-part framework to mine location representative knowledge from travelogues. The first part resolves travelogues in a geographic view. It discovers real location entities subordinated to travel destinations, then decomposes travelogues to acquire corresponding descriptions for each of these entities. Built upon the results of the first part, the second part performs content resolution in a semantic view. By extracting location characterizing concepts and the relatedness among them, it can form a representative concept network for each location entity. Based on a large collection of travelogues, the proposed framework is evaluated using both objective and subjective evaluation methods and shows promising results.

What trajectors reveal about TIME metaphors

This paper is an analysis of trajectors (i.e. located entities) in language about fixed durations of TIME. More specifically, trajectors in instances including the English prepositions in or on, or their Swedish equivalents i or på, are analyzed. On the structure of the inverse Moving Observer/Moving Time metaphors (Lakoff & Johnson 1999) instances such as these should be construed relative to a Moving Observer, and trajectors people that move relative to fixed durations of TIME (as reflected in e.g. when we come to launching the 4th edition in early 1990). My analysis, however, suggests that our understanding of TIME through SPACE is more nuanced than suggested by these metaphors. In this specific context, trajectors are not typically people in motion, but rather events or processes located in, or on, unit of time landmarks. My study emphasizes the need to test the systematicity of the mappings proposed by Conceptual Metaphor Theory.

INVESTMENT ATTRACTIVENESS MEASUREMENT OF THE REGIONS VERSUS GENERAL LOCATION OF THE ENTERPRISES

The objective of the study is to analyze regions’ potential investment attractiveness and its influence on the location of enterprises. The analysis was based on a secondary study carried out regionally in 2012 for the year 2010. Spearman's rank correlation coefficient was applied in the study regarding the connection between potential investment attractiveness and enterprises’ location, measured by the number of located entities per 10 thousands residents. Correlated variables confirmed the existence of a positive connection between the variables hypothesis.

A New Method for Location Entity Recognition

Location Entity Recognition (LER) is an important part in Named Entity Recognition (NER), and it is a significant research topic in this domain to use the abundant unlabeled corpus to improve recognition performance. A new method combined Active Learning with Self-Training is proposed, which selects samples based on confidence and 2-Gram frequency, and expands the training set by annotating the unlabeled corpus manually and automatically. The experiments reveal that the F-measure of this method is 8% higher than randomized Active Learning while the annotation is only 1/3 of the latter. And using this method, only 5% of characters in the extended training set need to be labeled to acquire a similar performance with complete manual annotation.

Automatic Extraction of Place Entities and Sentences Containing the Date and Number of Victims of Tropical Disease Incidence from the Web

Many tropical disease incidences, such as leprosy, elephantiasis, malaria, dengue fever, are reported in online news portals. Online news portals are valuable data sources for creating a tropical disease repository if the information such as the location of the incidence, date of occurrence, and the number of victims can be automatically extracted from news articles. This paper describes approaches to extract that information from the Web. We introduce a rule-based algorithm to identify and extract the locations of the incidence and use Support Vector Machine (SVM) to determine the sentences containing the date of occurrence and the number of victims. Our experiments show that, the accuracy of the rule-based algorithm to identify the location entities is 99.8%, while the accuracy of the classifier to determine the sentences that contain one or more places of the incidence is 82%. The accuracy of SVM classifiers to classify the sentences that contain the date of occurrence and the number of victims are 96.41% and 93.38%, respectively.

DoMaIN: A Novel Dynamic Location Management Solution for Internet-Based Infrastructure Wireless Mesh Networks

Wireless mesh networks (WMNs) have been deployed in many areas. There is an increasing demand for supporting a large number of mobile users in WMNs. As one of the key components in mobility management support, location management serves the purpose of tracking mobile users and locating them prior to establishing new communications. Previous dynamic location management schemes proposed for cellular and wireless local area networks (WLANs) cannot be directly applied to WMNs due to the existence of multihop wireless links in WMNs. Moreover, new design challenges arise when applying location management for silently roaming mobile users in the mesh backbone. Considering the number of wireless hops, an important factor affecting the performance of WMNs, we propose a DoMaIN framework that can help mobile users to decide whether an intra- or intergateway location update (LU) is needed to ensure the best location management performance (i.e., packet delivery) among dynamic location management solutions. In addition, by dynamically guiding mobile users to perform LU to a desirable location entity, the proposed DoMaIN framework can minimize the location management protocol overhead in terms of LU overhead in the mesh backbone. Furthermore, DoMaIN brings extra benefits for supporting a dynamic hop-based LU triggering method that is different from previous dynamic LU triggering schemes proposed for cellular networks and WLANs. We evaluate the performance of DoMaIN in different case studies using OPNET simulations. Comprehensive simulation results demonstrate that DoMaIN outperforms other location management schemes and is a satisfactory location management solution for a large number of mobile users silently and arbitrarily roaming under the wireless mesh backbone.

PROJECTING NAMED ENTITY TAGS FROM A RESOURCE RICH LANGUAGE TO A RESOURCE POOR LANGUAGE

Named Entities (NE) are the prominent entities appearing in textual documents. Automatic classification of NE in a textual corpus is a vital process in Information Extraction and Information Retrieval research. Named Entity Recognition (NER) is the identification of words in text that correspond to a pre-defined taxonomy such as person, organization, location, date, time, etc. This article focuses on the person (PER), organization (ORG) and location (LOC) entities for a Malay journalistic corpus of terrorism. A projection algorithm, using the Dice Coefficient function and bigram scoring method with domain-specific rules, is suggested to map the NE information from the English corpus to the Malay corpus of terrorism. The English corpus is the translated version of the Malay corpus. Hence, these two corpora are treated as parallel corpora. The method computes the string similarity between the English words and the list of available lexemes in a pre-built lexicon that approximates the best NE mapping. The algorithm has been effectively evaluated using our own terrorism tagged corpus; it achieved satisfactory results in terms of precision, recall, and F-measure. An evaluation of the selected open source NER tool for English is also presented.

An RFID Attacker Behavior Taxonomy

A taxonomy of system attacker behavior reveals security vulnerabilities in RFID authorization and monitoring systems. RFID systems are classified by their informational goals-typically, authorization and monitoring. Authorization systems replace the more traditional approaches of granting an entity access to a particular zone, whereas monitoring systems establish an entity's location in that zone. Although their informational goals differ, the underlying hardware is identical for both types of systems; consequently, attacks at the hardware level are the same. However, because attacker behavior invalidates each subsystem's informational goals differently, RFID security requirements should consider these goals individually.

Evaluation of Localization Attacks on Power-Modulated Challenge–Response Systems

Location information should be verifiable in order to support new computing and information services. In this paper, we adapt the classical challenge-response method for authentication to the task of verifying an entity's location. Our scheme utilizes a collection of transmitters, and adapts the power allocations across these transmitters to verify a user's claimed location. This strategy, which we call a power-modulated challenge response, is able to be used with existing. wireless sensor networks. First, we propose a direct method, where some transmitters are selected to send ldquochallengesrdquo that the claimant node should be able to witness based on its claimed location, and for which the claimant node must correctly respond to in order to prove its location. Second, we reverse the strategy by presenting an indirect method, where some transmitters send challenges that the claimant node should not be able to witness. Then, we present a signal-strength-based method, where the node responds with its received signal strength and thereby provides improved location verification. To evaluate our schemes, we examine different adversarial models for the claimant, and characterize the performance of our power-modulated challenge response schemes under these adversarial models. Further, we propose a new localization attack, where a set of nodes collaborates to pretend that there is a node at the claimed location. This collusion attack can do tremendous harm to localization and the performance of the aforementined methods under collusion attack are explained. Finally, we propose the use of a rotational directional power-modulated challenge response, where directional antennas are used to defend against collusion attacks.

Malakoplakia outside the urinary tract.

Malakoplakia is a rare granulomatous disease that occurs commonly in the urinary tract. Histologically, it is defined by sheets of histiocytes (Hansemann cells) with accumulation of granular basophilic periodic acid-Schiff-positive, diastase-resistant inclusions and calcified Michaelis-Gutmann bodies, which are pathognomonic but not necessary for diagnosis. In addition to the urinary tract, malakoplakia has been reported in other organs, including the gastrointestinal tract, central nervous system, female genital tract, and the tongue. To review the literature of reported sites of malakoplakia outside the urinary tract and their variable clinical presentations, and to discuss the main diagnostic features and differential diagnoses of malakoplakia. The pathogenesis and possible etiologic factors are also presented. Data for this work were collected from the published literature, textbooks, and the Internet. It is important to be aware of the existence of this entity in abnormal locations. In many situations, malignancy can be mimicked, especially when the lesion is ulcerated and is accompanied by lymph node involvement. Misinterpreting large, rapidly growing nodules of malakoplakia as tumor might lead to overstaging. Pathologists should be also aware of the possibility of malakoplakia coexisting with other lesions, such as tuberculosis and carcinoma, in the same specimen.

A cluster of anthrax cases including meningitis

We report a common-source outbreak of anthrax. The source of infection was the carcass of a cow. Three patients developed anthrax, which affects meninx, skin and larynx. The patient with meningitis died. In all, 20 people who contacted or ate the cooked meat of the dead cow were given prophylactic tetracycline and remained well. This small outbreak calls for the increased awareness of physicians to this clinical entity in locations in which anthrax is endemic and for health education.

The Impossibility of Relations Between Non-Collocated Spatial Objects And Non-Identical Topological Spaces

I argue that relations between non-collocated spatial entities, between non-identical topological spaces, and between non-identical basic building blocks of space, do not exist. If any spatially located entities are not at the same spatial location, or if any topological spaces or basic building blocks of space are non-identical, I will argue that there are no relations between or among them. The arguments I present are arguments that I have not seen in the literature.

Multimedia and spatial information systems

Spatial information systems increasingly require incorporation of multimedia data types. Pictures, sounds, animated sequences, and unstructured text may form an integral part of geographically located entities in information systems. An example ecological application with extensive multimedia requirements illustrates how multimedia data can be integrated with spatial information systems in a generic, application-independent manner.