Location Names Research Articles

Mapping Imprecision: How to Geocode Data from Inaccurate Historic Maps

This paper aims to present and discuss the method of geocoding historical place names from historic maps that cannot be georeferenced in the GIS environment. This concerns especially maps drawn in the early modern period, i.e., before the common use of precise topographic surveys. Such maps are valuable sources of place names and geocoding them is an asset to historical and geographical analyses. Geocoding is a process of matching spatial data (such as place names) with reference datasets (databases, gazetteers) and therefore giving them geographic coordinates. Such referencing can be done using multiple tools (online, desktop), reference datasets (modern, historical) and methods (manual, semi-automatic, automatic), but no suitable approach to handling inaccurate historic maps has yet been proposed. In this paper, selected geocoding strategies were described, as well as the author’s method of matching place names from inaccurate cartographic sources. The study was based on Charles Perthées maps of Polish palatinates (1:225,000, 1783–1804)—maps that are not mathematically precise enough to be georeferenced. The proposed semi-automatic and curated approach results in 85% accuracy. It reflects the manual workflow of historical geographers who identify place names with their modern counterparts by analysing their location and proper name.

How does Indian news media report smokeless tobacco control? A content analysis of the gutka ban enforcement.

Smokeless tobacco (SLT) products like gutka and paan masala are a growing public health crisis in India. Despite enacting a ban-the highest form of regulation-little is known about implementation progress. The purpose of this study was to look at how enforcement of gutka ban is covered in Indian news media and if media is a reliable source of data. We conducted a content analysis of online news reports (n = 192) from 2011 to 2019. News characteristics such as name and type of publication, language, location, slant and beat coverage, visuals, and administrative focus were quantified. Similarly, news contents were inductively coded to examine dominant themes and the implementation landscape. We found that coverage was initially low but increased after 2016. Overall, news reports were in favor of the ban. Five leading English newspapers covered the majority of the ban enforcement reports. Prominent themes like consumption, health hazards, tobacco control responses, impact on livelihoods, and illicit trade were drawn from the textual analysis as the main arguments in relation to the ban. Gutka is largely seen as an issue of crime reflected by the contents, sources, and frequent use of pictures depicting law enforcement. The interconnected distribution channels of the gutka industry hindered enforcement, highlighting the need to study the complexities of regional and local SLT supply chains.

Integrating global geochemical volcano rock composition with eruption history datasets

The major element composition of volcanic rocks carries important information about the source and differentiation processes affecting the magma, the physical properties that allow it to erupt, and its eruptive style. Although global rock geochemical databases exist, these are not linked to volcanic eruption history which hampers our global understanding of the relationship between magma composition and eruption dynamics. Here, we integrate two global databases, the Geochemistry of Rocks of the Oceans and Continents (GEOROC) and the Holocene volcanoes of the world of the Global Volcanism Program (VOTW-GVP). The integration is based on matching the location name, geographic position and eruption time, which is automated by a tool called DashVolcano. The tool is open-source, accessible at https://github.com/feog/DashVolcano, and gives access to the integrated datasets via an interactive dashboard. DashVolcano is based on more than 138,000 volcanic rock samples and provides the basis for the identification of global relationships between eruption styles, volcano types, and rock composition for more than 700 volcanoes and their eruptions for the last 10,000 years. The combined record of the eruptive history and its corresponding geochemical rock composition that DashVolcano provides can be used for characterizing global geochemical differences between volcanoes, and should also prove useful for improved long-term hazard and risk evaluations.

ILabel: Revealing Objects in Neural Fields

A neural field trained with self-supervision to efficiently represent the geometry and colour of a 3D scene tends to automatically decompose it into coherent and accurate object-like regions, which can be revealed with sparse labelling interactions to produce a 3D semantic scene segmentation. Our real-time iLabel system takes input from a hand-held RGB-D camera, requires zero prior training data, and works in an ‘open set’ manner, with semantic classes defined on the fly by the user. iLabel's underlying model is a simple multilayer perceptron (MLP), trained from scratch to learn a neural representation of a single 3D scene. The model is updated continually and visualised in real-time, allowing the user to focus interactions to achieve extremely efficient semantic segmentation. A room-scale scene can be accurately labelled into 10+ semantic categories with around 100 clicks, taking less than 5 minutes. Quantitative labelling accuracy scales powerfully with the number of clicks, and rapidly surpasses standard pre-trained semantic segmentation methods. We also demonstrate a hierarchical labelling variant of iLabel and a ‘hands-free’ mode where the user only needs to supply label names for automatically-generated locations.

Implementation Reserve Geocoding on Mobile Application

Reverse geocoding is the conversion of coordinates into an address that allows you to find an address. In this study, the coordinates in question are latitude and longitude points on a mobile device that uses an Android-based operating system. The default feature of Android devices for obtaining latitude and longitude data is Assisted – GPS (Global Positioning System) while the tool for processing latitude and longitude data in order to obtain location and place names from the Assisted – GPS (Global Positioning System) data that has been obtained is the nominal API. .org. the stages of work in the research are making a flow system, designing a system with use case diagrams, designing a database, coding, implementing it on android based and web based. The results of this study are that using Cordova can be an alternative for making Android-based mobile applications without the need for the relatively heavy Android Studio program if it is run on standard or low specification hardware, 2). With this mobile absence application, it is able to make it easier for employees to take attendance when outside the office with information about working or out of town service, 3). With this application it can be a means of facilitating superiors in assessing employee performance, 4). With this application can handle the problem solved.

The Belorussian Republican Scientific Agricultural Library in the 1960s and the first half of the 1970s: activities of branches, mobile libraries, lending points

The article considers the activity of the Belorussian Republic Scientific Agricultural Library (BRSAL) in 1960-s - first half of 1970-s aimed at improving services to the readers, who have no an immediate opportunity to use its library loan and reading-room, through the provision of various forms of non-stationary services: mobile libraries, library branches, service points of literature. The definitions and the essence of such concepts as "branch library", "mobile library", and "library service point" as applied to the historical realities of the 1960s and the first half of the 1970s are revealed. The forms of non-stationary service which were used in BRSAL during the investigated period have been identified on the basis of the documents from the current archive of I.S. Lupinovich Belarus Agricultural Library of the National Academy of Sciences of Belarus. The number and location (names) of each form of non-stationary work by year has been established. Statistical indicators of the forms of nonstationary service of BRSAL on readers' record, lending, reference, bibliographic and informational work have been given.

HomeRange: A global database of mammalian home ranges

AbstractMotivationHome range is a common measure of use of space by animals because it provides ecological information that is useful for conservation applications. In macroecological studies, values are typically aggregated to species means to examine general patterns of use of space by animals. However, this ignores the environmental context in which the home range was estimated and does not account for intraspecific variation in home range size. In addition, the focus of macroecological studies on home ranges has historically been biased towards terrestrial mammals. The use of aggregated numbers and the terrestrial focus limit our ability to examine home‐range patterns across different environments, their variation in time and variation between different levels of organization. Here, we introduce HomeRange, a global database with 75,611 home‐range values across 960 different species of mammals, including terrestrial, aquatic and aerial species.Main types of variables containedThe dataset contains estimates of home ranges of mammals, species names, methodological information on data collection, method of home‐range estimation, period of data collection, study coordinates and name of location, in addition to species traits derived from the studies, such as body mass, life stage, reproductive status and locomotor habit.Spatial location and grainThe collected data are distributed globally. Across studies, the spatial accuracy varies, with the coarsest resolution being 1°.Time period and grainThe data represent information published between 1939 and 2022. Across studies, the temporal accuracy varies; some studies report start and end dates specific to the day, whereas for other studies only the month or year is reported.Major taxa and level of measurementMammalian species from 24 of the 27 different taxonomic orders. Home‐range estimates range from individual‐level values to population‐level averages.Software formatData are supplied as a comma‐delimited text file (.csv) and can be loaded directly into R using the “HomeRange” R package (https://github.com/SHoeks/HomeRange).

How the Citizen Science Platform iSpot Ensures Data Accuracy During and After Collection

How the Citizen Science Platform iSpot Ensures Data Accuracy During and After Collection

Perceiving fingerspelling via point-light displays: The stimulus and the perceiver both matter.

Signed languages such as American Sign Language (ASL) rely on visuospatial information that combines hand and bodily movements, facial expressions, and fingerspelling. Signers communicate in a wide array of sub-optimal environments, such as in dim lighting or from a distance. While fingerspelling is a common and essential part of signed languages, the perception of fingerspelling in difficult visual environments is not well understood. The movement and spatial patterns of ASL are well-suited to representation by dynamic Point Light Display (PLD) stimuli in which human movement is shown as an array of moving dots affixed to joints on the body. We created PLD videos of fingerspelled location names. The location names were either Real (e.g., KUWAIT) or Pseudo-names (e.g., CLARTAND), and the PLDs showed either a High or a Low number of markers. In an online study, Deaf and Hearing ASL users (total N = 283) watched 27 PLD stimulus videos that varied by Word Type and Number of Markers. Participants watched the videos and typed the names they saw, along with how confident they were in their response. We predicted that when signers see ASL fingerspelling PLDs, language experience in ASL will be positively correlated with accuracy and self-rated confidence scores. We also predicted that Real location names would be understood better than Pseudo names. Our findings supported those predictions. We also discovered a significant interaction between Age and Word Type, which suggests that as people age, they use outside world knowledge to inform their fingerspelling success. Finally, we examined the accuracy and confidence in fingerspelling perception in early ASL users. Studying the relationship between language experience with PLD fingerspelling perception allows us to explore how hearing status, ASL fluency levels, and age of language acquisition affect the core abilities of understanding fingerspelling.

“Africa's First Woman Press Photographer”: Mabel Cetu's Photographs in Zonk!

“Africa's First Woman Press Photographer”: Mabel Cetu's Photographs in <i>Zonk!</i>

Machine Learning Based Password Strength Analysis

Passwords, as the most used method of authentication because to its ease of implementation, allow attackers to get access to the accounts owned by others by means of cracking passwords. This is cause of the similar patterns that users use to create a password, like dictionary words, common phrases, person and location names, keyboard pattern, and so on. Multiple password cracking techniques had been introduced to predict the password offline or online, with the majority of records say the one with weak password or familiar password patterns being cracked. This suggested prototype implements numerous machine learning methods such as Decision Tree (DT), Nave Bayes (NB), Logistic Regression (LR), and Random Forest (RF) on a web application in real time to force users to choose a secure password. This results in the user’s account being logged into if particularly the password strength from more than half of the algorithms is strong.

Nested Named Entity Recognition: A Survey

With the rapid development of text mining, many studies observe that text generally contains a variety of implicit information, and it is important to develop techniques for extracting such information. Named Entity Recognition (NER), the first step of information extraction, mainly identifies names of persons, locations, and organizations in text. Although existing neural-based NER approaches achieve great success in many language domains, most of them normally ignore the nested nature of named entities. Recently, diverse studies focus on the nested NER problem and yield state-of-the-art performance. This survey attempts to provide a comprehensive review on existing approaches for nested NER from the perspectives of the model architecture and the model property, which may help readers have a better understanding of the current research status and ideas. In this survey, we first introduce the background of nested NER, especially the differences between nested NER and traditional (i.e., flat) NER. We then review the existing nested NER approaches from 2002 to 2020 and mainly classify them into five categories according to the model architecture, including early rule-based, layered-based, region-based, hypergraph-based, and transition-based approaches. We also explore in greater depth the impact of key properties unique to nested NER approaches from the model property perspective, namely entity dependency, stage framework, error propagation, and tag scheme. Finally, we summarize the open challenges and point out a few possible future directions in this area. This survey would be useful for three kinds of readers: (i) Newcomers in the field who want to learn about NER, especially for nested NER. (ii) Researchers who want to clarify the relationship and advantages between flat NER and nested NER. (iii) Practitioners who just need to determine which NER technique (i.e., nested or not) works best in their applications.

Use of Outpatient Opioids Prescribed From a Pediatric Acute Care Setting.

Deaths due to prescription opioid overdoses are at record high levels. Limiting the amount of opioid prescribed has been suggested as a prevention strategy, but little is known about how much is needed to adequately treat acutely painful conditions for outpatients. The purpose of this study was to quantify the usage of opioids prescribed from the pediatric emergency departments of a Midwestern tertiary care children's hospital system. This was a prospective descriptive study in which patients aged 0 to 17 years seen in 2 pediatric emergency departments who received a prescription for an outpatient opioid were enrolled. The main outcome was opioid doses used at home, which was obtained via phone follow-up. Additional information, including patient demographics, location, prescriber specialty, diagnosis, and opioid name and amount prescribed, was obtained via chart review. A total of 295 patients were enrolled, with 281 completing the study (95%). The median numbers of opioid doses prescribed and used were 12 and 2 doses, respectively, with 9 doses in excess. Patients with lower extremity fractures used more opioids than other diagnoses, with a median of 8 doses. The majority of families reported keeping extra doses at home. Prescribed opioid doses exceeded used doses by a factor of 6. Lower extremity fractures required more doses than other acutely painful conditions. We should consider limiting doses prescribed to decrease excess opioids available for misuse and abuse.

Understanding Social Biases Behind Location Names in Contextual Word Embedding Models

Embeddings of textual data containing location names (e.g., social media posts) have essential applications in various contexts such as marketing and disaster management. In these downstream implementations, social biases behind location names are highly prone to introduce unfair results through their embeddings; for example, emergent text messages with swapped location names might result in varied rescue responses. Hence, it is critical to address social biases encoded in location names and to seek its mitigation. Prevalent works addressing biases in embeddings mainly focus on individual attributes like gender or ethnicity. Yet, a large number of social attributes behind location names (e.g., income level and population density) makes it challenging to originate the source of biases. Existing mitigation methods based on finding attribute subspaces cannot be simply applied to address social biases. Moreover, bias mitigation tends to simultaneously remove necessary semantics from embeddings, making it difficult to achieve a balance between mitigation performance and semantics retention. In this article, we first employ the concept of counterfactual fairness to investigate the social biases encoded in training data. Then, we quantify the biases in the contextual embeddings (BERT and ELMo). We report a high correlation between biases in the training data and embeddings. Next, we introduce a novel bias mitigation algorithm that customizes bias representations for any location names. The method yields debiased location name vectors for various social attributes simultaneously. The proposed algorithm achieves a better mitigation performance on overall attributes compared with a prevalent postprocessing method, while maintaining correctness by retaining semantic information.

Gender Neutral Language in (Greater) Buenos Aires, (Greater) La Plata, and Córdoba: An Analysis of Social Context Information Using Textual and Temporal Features.

In this article, I explore Twitter data to analyze Gender Neutral Language (GNL) in (Greater) Buenos Aires, (Greater) La Plata, and Córdoba. The goal is to characterize the social context behind GNL. Social context analysis of social media data is challenging given that this data type does not contain the social characteristics of its users and the circumstances under which the tweets were written. In order to fill this gap, I will derive the social context information from textual and temporal features by analyzing the names of locations, companies, and people used in the text and relating these entities to the message of the tweet. The analysis of temporal features will give us insights into the correlation between language use and social events. Our results show that the general characterization of the social context behind GNL is associated with socio-economically rich areas in city centers. Users of GNL in the investigated areas address certain groups of people with words that express familiarity and close social relationships, such as those meaning “friends” and “neighbors” and that give them information about a political, cultural, or social event or concerning commercial products/services. The temporal analysis by month supports this characterization by showing that certain political and social events induce a higher frequency of GNL. This paper contributes to previous research on GNL in Argentina by testing existing hypotheses quantitatively. The new discovery presented here is that political activism is not the only language context in which GNL is used in social media and that GNL is not exclusively used in big cities of Argentina but also in smaller cities.

Memory and Representation of Edo through Parody. Edo sunago and Muda sunago

This paper urges consideration of eighteenth-century popular literature known as gesaku in the analysis of Edo's urban culture, through a preliminary study of Muda sunago (1786). Muda sunago is a comic book (sharebon) written as a parody of Edo topographies (chishi), mocking in its title the famous Edo sunago (1732). The paper starts by introducing the two works and the genres to which they pertain, then focuses on the structure of Muda sunago and the process through which the comical "famous places" are created. The work is interpreted as a "map" representing Edo through its entertainments, which had an important role in the formation of an urban culture, since they offered an opportunity for drawing together the diverse groups of citizens. The parody of the topography format allows a description of each location, expanding the humor already displayed in the name's location. While descriptions in topographies always included historical anecdotes, or memories, as an important part of the place, in Muda sunago jokes are disguised as historical anecdotes. An example is shown in the analysis of the "Bay of the Skipjack Tuna", which satirizes the irrational mania of Edo citizens of paying high prices to eat the season's first skipjack tuna (hatsugatsuo). If in topographies, the memory of Edo was used to evoke and create a shared past, in parodies it fulfils a similar role enforcing in the reader the sensation of sharing a common ground with the author, which is necessary for the humor to be recognized as such.

Метафорические образы пространства в русских традиционных рекрутских обрядах Удмуртии: тематика «пути-дороги»

The study aims to describe the metaphorical imagery of verbal song texts of recruitment rites in the Russian traditional culture of Udmurtia. The paper characterised the most striking literary images, specific plots, motifs related to the “on the road” themes. Scientific novelty lies in providing a comprehensive description of metaphorical images of space, using the example of song texts of recruitment rites. As a result of the study, it has been shown that geographical names of landscapes, names of army service locations, metaphorical images associated with the display of water space, with crying, tears and blood become the symbols of a recruit’s alienation, removal from his native space.

Implementasi Fuzzy Menggunakan Mamdani Pada Sistem Pendukung Keputusan Lokasi Pemasangan Iklan Calon Legislatif

The development of information technology today requires information that is fast and accurate in its implementation. The installation of prospective legislative advertising brochures that perform well with the support of a decision support system is one of the implementations of the development of information technology. Research that uses the mamdani method in this decision support system produces a decision support system application for installing banners that are commonly used in legislative candidates. The criteria used in the decision support system for installing advertising banners are: location name, strategy element, location location, rival advertisement and population. The results of this study are the location of the selected strategies from several places that have good performance that have followed the selection, and the output of the application helps decision makers (desician makers) in choosing alternatives for the location of advertisements in the form of banner candidates using desktop-based web applications

Arabic Location Named Entity Recognition for Tweets using a Deep Learning Approach

Social media sites like Twitter have emerged in recent years as a major data source utilized in a variety of disciplines, including economics, politics, and scientific study. To extract pertinent data for decision-making and behavioral analysis, one can use Twitter data. To extract event location names and entities from colloquial Arabic texts using deep learning techniques, this study proposed Named Entity Recognition (NER) and Linking (NEL) models. Google Maps was also used to obtain up-to-date details for each extracted site and link them to the geographical coordination. Our method was able to predict 40% and 48% of the locations of tweets at the regional and city levels, respectively, while the F-measure was able to reliably identify and detect 63% of the locations of tweets at a single Point of Interest.

Notes on the Karatepe Storm-god Tarhunza Usanuwami and Baal Krntryš

The Karatepe storm god has been defined in Luwian inscriptions as Tarhunza Usanuwami, and in the Phoenician version as Baal Krntryš. The meaning of the Krntryš epithet still maintains its mystery. Location names, names and adjectives with weak probability that have been proposed by some researchers do not provide a convincing explanation. The main gods of the Neo-Hittite provinces and the main features of these gods can be different, and neglecting the Karatepe reliefs and inscriptions and looking for cult characteristics outside the region can cause wrong interpretations. There is no study in which the Usanuwami and Krntryš epithet of the storm god has been investigated in all its features. In this study, suggestions having a high probability for the word Krntryš are presented in line with the iconographic features of the Karatepe storm god. These suggestions are the combination of the words for granary (Luwian karuna, Phoenician ‘qrnt) and wine and vineyard/wine warehouse (Luwian tuwarsa-tuwarisa, Phoenician trš, plural tryš).