bluuebunny/crossref_metadata_2025 huggingface dataset:
La representación de la desigualdad social en la obra de Roberto Bolaño
Authors: Witthaus Jan-Henrik
Published: September 2020

The article deals with the issue of social inequality represented in two narratives of the Chilean writer Roberto Bolaño, the fourth chapter »The part of the crimes« of the novel 2666 (2004) and A Little Lumpen Novelita (2002). It is shown that the perspectivism of literary representation is well compatible with certain sociological approaches and concepts, which for instance in the case of the term ›relative deprivation‹ (Runciman) include subjectivities, points of view, and comparisons. Thus, whereas statistics indicate the existence of social inequality only through numbers and coefficients, literature turns out to be an adequate medium to analyze its social effects. As a closer look at »The part of the crimes« reveals, the stories told in this chapter make visible not only the conditions of perception of inequality, but also the ignorance and the general invisibility of social emergency. Moreover, the article shows that social inequality represents a theme that frequently appears in the narrative prose of Roberto Bolaño and which therefore could enrich the reception of his work.
How Puzzles of Petitionary Prayer Solve Themselves: Divine Omnirationality, Interest-Relative Explanation, and Answered Prayer
Authors: Johnson Daniel M.
Published: September 2020

Some have seen in the divine attribute of omnirationality, identified by Alexander R. Pruss, the promise of a dissolution of the usual puzzles of petitionary prayer. Scott Davison has challenged this line of thought with a series of example cases. I will argue that Davison is only partially correct, and that the reasons for this reveal an important new way to approach the puzzles of petitionary prayer. Because explanations are typically interest-relative, there is not one correct account of “answered prayer” but many, corresponding to a variety of reasons to care whether God might answer our prayers. It follows from this that the omnirationality solution can be vindicated and that puzzles of petitionary prayer that are not dissolved thereby will typically contain within themselves the seeds of their own solutions.
Elliot Sober: The Design Argument
Authors: Keller John A.
Published: September 2020

The Design Argument, by Elliot Sober. Cambridge University Press, 2018. Pp. 94. $18.00 (paperback).
Blake Hereth and Kevin Timpe, eds.: The Lost Sheep in Philosophy of Religion: New Perspectives on Disability, Gender, Race, and Animals
Authors: Arlig Andrew W.
Published: September 2020

The Lost Sheep in Philosophy of Religion: New Perspectives on Disability, Gender, Race, and Animals, edited by Blake Hereth and Kevin Timpe. Routledge, 2020. Pp. xiii + 400. $155.00 (hardcover), $28.98 (e-book).
John H. McClendon III: Black Christology and the Quest for Authenticity: A Philosophical Appraisal
Authors: Yadav Sameer
Published: September 2020

Black Christology and the Quest for Authenticity: A Philosophical Appraisal, by John H. McClendon III. Lexington Books, 2019. Pp. viii + 207. $95.00 (hardcover).
Brain Tumor Extraction from MRI Images Using MATLAB
Authors: Rangne Pranay , Bhombe Prof. R.M. , Welankiwar Prof. A.S.
Published: September 2020

Computerized or Automatic detection of tumors in medical images is motivated by the necessity of high accuracy when dealing with a human life. The computer assistance is also demanded in medical institutions because it could improve the results of disease identification and negative cases should be very low. So, the Processing of Magnetic Resonance Imaging (MRI) images is one of the techniques to diagnose the brain tumor. This paper describes the strategy to detect and extract brain tumor from patient’s MRI scanned images. In this the Steps includes are pre-processing, segmentation, morphological operation, watershed segmentation and calculation of the tumor area and determination of the tumor location and this Application is Developed using Matrix Laboratory (MATLAB)
DOES DEFAULT RISK MATTER FOR INVESTORS IN REITS
Authors: Sha Yezhou , Wang Zilong , Bu Ziwen , Mansley Nick
Published: September 2020

We investigate the relationship between default risk and REIT stock returns. A default risk long-short investment strategy generates a return of 15% per annum. We also evaluate a large number of potential explanations for the negative relationship between default risk and subsequent stock returns. We do not find robust evidence that the default risk premium can be explained by firm size, book-to-market equity, asset growth and idiosyncratic volatility. However, CAPM beta shows some promise in explaining the default risk premium. Our results shed further light on the role of default risk in investment in REITs.
Origins of Mass Segregation in Stellar Clusters within the STARFORGE Simulations
Authors: Markey Carleen , Guszejnov Dávid , Offner Stella S. R.
Published: September 2020

Stellar clusters formed within Giant Molecular Clouds are mass segregated. This is either because massive stars are born at the center of the clusters, or because they migrate to the center due to gravitational interactions. We analyze a run from the STARFORGE simulation suite to identify what role the above processes play in determining mass segregation. We find that clusters begin as inversely- or non-mass segregated but contain separate mass-segregated star formation sites. As the cluster evolves, these substructures merge, and the overall cluster becomes more mass segregated due to gravitational interactions.
A Reader Friendly Formalism for the Circumstellar Material-supernova Ejecta Interaction Model
Authors: Liu Liang-Duan , Wang Ling-Jun , Gao He
Published: September 2020

The interaction of a SN ejecta with a pre-existing circumstellar material (CSM) is one of the most promising energy sources for a variety of optical transients. Recently, a semi-analytic method developed by Chatzopoulos et al. (2012, hereafter CWV12) has been commonly used to describe the optical light curve behaviors under such a scenario. We find that the expressions for many key results in CWV12 are too complicated for readers to make order of magnitude estimation or parameter dependency judgement. Based on the same physical picture, here we independently re-derive all the formulae and re-establish a set of reader friendly formula expressions. Nevertheless, we point out and correct some minor errors or typos existing in CWV12.
Review of Machine Learning Technologies and Neural Networks in Drug Synergy Combination pharmacological research
Authors: Ter-Levonian Artur S. , Koshechkin Konstantin A.
Published: September 2020

Introduction: Nowadays an increase in the amount of information creates the need to replace and update data process­ing technologies. One of the tasks of clinical pharmacology is to create the right combination of drugs for the treatment of a particular disease. It takes months and even years to create a treatment regimen. Using machine learning (in silico) allows predicting how to get the right combination of drugs and skip the experimental steps in a study that take a lot of time and financial expenses. Gradual preparation is needed for the Deep Learning of Drug Synergy, starting from creating a base of drugs, their characteristics and ways of interacting.

Aim: Our review aims to draw attention to the prospect of the introduction of Deep Learning technology to predict possible combinations of drugs for the treatment of various diseases.

Materials and methods: Literary review of articles based on the PUBMED project and related bibliographic resources over the past 5 years (2015–2019).

Results and discussion: In the analyzed articles, Machine or Deep Learning completed the assigned tasks. It was able to determine the most appropriate combinations for the treatment of certain diseases, select the necessary regimen and doses. In addition, using this technology, new combinations have been identified that may be further involved in preclinical studies.

Conclusions: From the analysis of the articles, we obtained evidence of the positive effects of Deep Learning to select “key” combinations for further stages of preclinical research.
Patrimonialisation « sauvage » et archéologie industrielle de la musique yéménite
Authors: Lambert Jean , al-Akouri Rafik
Published: September 2020

Les premiers enregistrements commerciaux de musique yéménite furent réalisés à Aden, à la fin des années 1930, à l’époque de la colonie britannique. Ces disques 78 tours furent d’abord édités par une compagnie étrangère, Odeon, puis par plusieurs compagnies locales, dont Aden Crown, Jafferphon et Tahaphon. Rapidement, c’est l’ensemble des traditions musicales urbaines du Yémen, ṣanʿānī, laḥǧī, ḥaḍramī, etc., qui furent ainsi reconnues et diffusées dans l’ensemble du pays, entre 1935 et 1960. On évalue ces premiers enregistrements à plusieurs milliers de disques. Cependant, ils sont encore très mal connus, et il est difficile d’en établir une chronologie, les divers documents disponibles n’étant jamais datés. Dès lors, cette recherche doit recourir à une sorte d’« archéologie industrielle et musicale » tentant de délimiter des fourchettes de dates, des périodes et des corrélations temporelles de manière approximative. Simultanément, l’actuelle « patrimonialisation sauvage » de ces musiques sur la Toile permet un accès aisé à beaucoup d’enregistrements sonores sur les plateformes grand public, en particulier YouTube. Ceci représente un progrès immense pour le processus d’inventaire, mais aussi une solution de stockage très aléatoire que la recherche doit essayer de compenser par un effort accru de documentation, notamment par l’élaboration d’une base de données. La réception des disques par la société yéménite durant ces vingt-cinq années prolifiques du xxe siècle nous montre que ces disques eurent une influence importante sur la pratique musicale, ainsi que sur un aspect plus subtil de la musique yéménite : la définition des genres régionaux qui eut une grande importance dans la construction de l’identité culturelle des Yéménites même à une époque plus récente.
Aziz El‑Shawan
Authors: Castelo‑Branco Salwa El‑Shawan
Published: September 2020

This article proposes a politically and culturally situated preliminary reading of the biographical and artistic trajectory of Aziz El‑Shawan (1916–1993), a cosmopolitan and nationalist Egyptian composer. The article characterizes the two cosmopolitan cultural formations in Cairo in which he partook and their impact on his career and music: a «modernist capitalist» formation which developed within the framework of colonial rule and the Egyptian monarchy from the late nineteenth century up to the 1952 Egyptian revolution; and a «modernist socialist» formation, partly configured by Soviet political and cultural influence, from the late 1950s up to the early 1970s. The article describes how Aziz El‑Shawan became a composer, the phases of his artistic and professional career and his musical style.
Recording Culture
Authors: Puig Nicolas
Published: September 2020

Halim el-Dabh (1921-2017) est un collecteur et pionnier des musiques électroniques qui fait aujourd’hui l’objet d’une redécouverte par une nouvelle génération de musiciens égyptiens qui voient en lui un précurseur national. El‑Dabh proposa en effet dès 1944 l’une des premières compositions mondiales électroniques à partir de sons sélectionnés et transformés, à partir de son propre enregistrement effectué dans sa ville natale du Caire. Cette œuvre, avec d’autres du même genre, et le parcours de ce musicien éclectique à la fois compositeur et universitaire, éclaire d’un jour inédit la production et la restitution des savoirs anthropologiques. Ces savoirs ne sont pas tant élaborés à partir d’une « écriture des cultures » que dans l’acte et l’art de les enregistrer et de les restituer sous différentes formes, y compris artistiques. Ce texte s’intéresse à la jeunesse de Halim El‑Dabh pour restituer autant que possible son itinéraire dans un moment technologique et culturel égyptien, tout en le rapportant à des dynamiques plus globales. Car, à l’instar d’autres figures du xxe siècle, Halim El‑Dabh développe des articulations inédites entre collecte, recherche et création qui questionnent les dynamiques coloniales et néocoloniales de conservation et restitution des musiques, et plus largement de production des savoirs.
Archives sauvages et bootleggers des musiques arabes
Authors: France Pierre
Published: September 2020

Pour quiconque tenterait de compléter et mettre à jour une liste des archives des musiques arabes, la tâche nécessite désormais autant un travail dans les bibliothèques et les archives (publiques mais surtout privées), qu’une capacité à interroger le web et ses usages par de nouveaux entrepreneurs de patrimonialisation, et plus encore sur de nouveaux types de musique. Retraçant l’histoire de ces sites qui ont de fait numérisé et proposé à la diffusion des musiques arabes jusque‑là jamais écoutées au-delà d’un certain cercle (social ou national), ou bien facilité la diffusion de grands classiques autrement impossibles à acheter ou écouter légalement, cet article vise à dégager les formes de cet espace social (et de ses clivages), mais aussi à proposer une réflexion sur les pratiques et le type de patrimonialisation qui s’y joue, qualifiée ici de « sauvage » à la suite des travaux de Cyril Isnart (2009), et où l’on peut distinguer une catégorie spécifique d’acteurs proches des bootleggers d’habitude associés à la musique pop‑rock.
جوانب جديدة عن أصحاب خراج مصر في القرنين 2-3هـ/8-9م من خلال برديات الأشمونين
Authors: كمال أحمد
Published: September 2020

Despite the importance of the financial administrators of Egypt (aṣḥāb al-ḫarāǧ) and their basic role in the administration system in the early Islamic period, historical sources don't provide sufficient information about them. On the other hand, hundreds of papyri from ­al-Ušmūnayn province still exist. These papyri, especially tax receipts, contain many names and some information about the financial directors of Egypt during the 2nd-3rd/8th-9th centuries. Some of the financial directors are not mentioned in other historical sources, but al-Ušmūnayn Arabic papyri provide some new information about known directors and introduce new ones.
عقدا زواج ولواحقهما في وثيقة غير منشورةمن وثائق الحرم القدسي الشريف
Authors: الرحمن محمد نصر عبد , أنس أشرف محمد
Published: September 2020

Documents from the Ḥaram Šarīf are considered to be among the most important historical sources from the Mamluk Jerusalem society because they provide much documentary evidence covering all aspects of life in this community during that era. Among the most important documents included in this collection; documents on the cases of marriage and divorce in the community of Jerusalem. The document being studied (No. 646) belongs to this group, and includes two marriage contracts and two divorce contracts for a former slave named Zumurrud, who lived in Jerusalem at the end of the 8th century of the Islamic calendar/14th century. Since the case of Zumurrud is one of the few cases of the lower classes that can trace a large part of its family history thanks to the existence of this document, which includes marriage and divorce contracts, in addition to another document registering a third marriage for her, this study attempts to discuss the case of Zumurrud through the publication and discussion of document 646, which appears to be rich in details revealing important aspects of the life of women in Jerusalem during the Mamluk era.
بيض النعام
Authors: الشوكي أحمد
Published: September 2020

Ostrich eggs held great importance among the Arabs before Islam. Their importance also continued after the emergence of Islam, with various uses such as hanging them in religious establishments like mosques, mosuleums or civil buildings such as houses. The eggs were decorated in different ways: inscriptions, paintings and multi-level engravings on their surfaces. These decorations made them valuable gifts for Kings and Caliphs. In this paper, I am studying Ostrich eggs on different levels, from their functional uses to their religious aspects. I am relying on Egyptian museums’ collections which contain unpublished Ostrich eggs. I am also using historical sources which provide important information that has not yet been taken into account.
Chronic Kidney Disease Prediction Using Data Mining Algorithms
Authors: Srivastava Devesh Kumar , Tiwari Pradeep Kumar
Published: September 2020

In today's contemporary world, it is important to know about the odds of having a disease because of changing living standards of the population overall in the continent. The disease on which the authors are working is chronic kidney disease. Once the person gets chronic kidney disease (CKD), his working capability decreases along with other adverse effects. It is possible to get rid of diseases like CKD with new methodologies that will help us to predict the stage of kidney disease at an early stage. Under big data analytics, data may be structured, unstructured, quasi- or semi-structured. The CKD detected and predicted by applying classification models: support vector machine (SVM), K-nearest neighbor (KNN), and logistic regression algorithm. It helps in predicting the likelihood of occurrence of disease on various different features. The two algorithms KNN and SVM are compared to find the algorithm that gives better accuracy. Further regression technique has been used to detect the disease based on, which the stages are classified by using GFR (glomerular filtration rate) formula.
Application of Machine Learning to Analyse Biomedical Signals for Medical Diagnosis
Authors: Kumar Upendra , Yadav Shashank
Published: September 2020

Interest in research involving health-medical information analysis based on artificial intelligence has recently been increasing. Most of the research in this field has been focused on searching for new knowledge for predicting and diagnosing disease by revealing the relation between disease and various information features of data. However, still needed are more research and interest in applying the latest advanced artificial intelligence-based data analysis techniques to bio-signal data, which are continuous physiological records, such as EEG (electroencephalography) and ECG (electrocardiogram). This study presents a survey of ECG classification into arrhythmia types. Early and accurate detection of arrhythmia types is important in detecting heart diseases and choosing appropriate treatment for a patient.
Artificial Intelligence Approaches to Detect Neurodegenerative Disease From Medical Records
Authors: Gupta Abhranil
Published: September 2020

This chapter gives a brief overview of the state of the art of machine learning approaches in detection of the neurodegenerative disease from medical records (brain scans, etc.). It starts with an understanding of the sub-field of artificial intelligence, machine learning, then goes to understand neurodegenerative disease, with a focus on four major diseases and then goes on to giving an overview of how such diseases are detected using machine learning. In the end, it discusses the future areas of research that needs to be done in order to improve the field of research.
Pre-Clustering Techniques for Healthcare System
Authors: Srinivasulu Asadi
Published: September 2020

This chapter presents a comparative study of the proposed approaches (i.e., extended dark block extraction [EDBE], extended cluster count extraction [ECCE], and extended co-VAT approaches). This chapter evaluates pre-clustering and post-clustering algorithms on real-time data and synthetic datasets. Unlike traditional clustering algorithms, pre-clustering algorithms provide a prior clustering on different datasets. Simulation studies are carried out using datasets having both class-labeled and unlabeled information. Comparative studies are performed between results of existing pre-clustering and proposed pre-clustering approaches. A simulated RDI-based preprocessing method is also applied for data diversification. Extensive simulation on real and synthetic datasets shows that pre-clustering algorithms with simulated RDI-based pre-processing performs better compared to conventional post-clustering algorithms.
Texture Segmentation and Features of Medical Images
Authors: Yadav Ashwani Kumar , Vaishali  , Kumar Raj , Kumar Archek Praveen
Published: September 2020

Texture analysis is one of the basic aspects of human visual system by which one can differentiate the objects and homogenous areas in an image. Manual diagnosis is not possible for huge database of images. Automatic diagnosis is required for greater accuracy in a shorter time. Texture analysis is required for effective diagnosis of medical images like functional MRI (magnetic resonance image) and diffusion tensor MRI, where only visualization is not sufficient to get the pathological information. This chapter explains the basic concepts of texture analysis and features available for analysis of medical images. Specifically, the intense review of texture segmentation and texture feature extraction and entropy measures of medical images have been done. The chapter also explores the available techniques for it. Common findings, comparative analysis, and gaps identified have also been mentioned on both issues.
Towards Integrating Data Mining With Knowledge-Based System for Diagnosis of Human Eye Diseases
Authors: Mishra Nilamadhab , Samuel Johny Melese
Published: September 2020

The eye is the most important sensory organ of vision function. But some eye diseases can lead to vision loss, so it is important to identify and treat eye disease as early as possible. Eye care professionals can help protect their patients from vision loss or blindness by recognizing common eye diseases and recommending for an eye exam. Eye diseases with early detection, treatment, and appropriate follow-up care, vision loss, and blindness from eye disease can be prevented or delayed. In this study, rule-based eye disease identification and advising the knowledge-based system are projected. The projected system is targeting using hidden knowledge extracted by employing the extraction algorithm of data mining. To identify the best prediction model for the diagnosis of eye disease, four experiments for four classification algorithms were performed. Finally, the researchers decided to use the rules of the J48 pruned classification algorithm for further use in the development of a knowledge base of KBS because it exhibited better performance with a 98.5% evaluation result.
ACO_NB-Based Hybrid Prediction Model for Medical Disease Diagnosis
Authors: Kumar Amit , Kumar Manish , R. Nidhya
Published: September 2020

In recent years, a huge increase in the demand of medically related data is reported. Due to this, research in medical disease diagnosis has emerged as one of the most demanding research domains. The research reported in this chapter is based on developing an ACO (ant colony optimization)-based Bayesian hybrid prediction model for medical disease diagnosis. The proposed model is presented in two phases. In the first phase, the authors deal with feature selection by using the application of a nature-inspired algorithm known as ACO. In the second phase, they use the obtained feature subset as input for the naïve Bayes (NB) classifier for enhancing the classification performances over medical domain data sets. They have considered 12 datasets from different organizations for experimental purpose. The experimental analysis advocates the superiority of the presented model in dealing with medical data for disease prediction and diagnosis.
Soft Skills vs. Hard Skills in Tourism
Authors: Moura Andreia Antunes , Mira Maria do Rosário Campos , Costa Vânia Natércia
Published: September 2020

This chapter presents a qualitative study, resulting from a systematic literature review using a text analysis technique through the NVivo software, version 10.0. This technique involves grouping words that reveal semantic similarity to each other and results indicate that considerations around soft and hard skills in tourism have been different over time. In short, it might be said that it is hard skills that lead people to job interviews, but it is soft skills that allow them to be recruited for employment. Hence, it is the combination of the two skill types that enables people to have a job in the tourism industry, manage a career, and contribute to the differentiation of tourism companies in the tourism global marketplace that tends to be increasingly competitive.
Great Expectations
Authors: Silva Susana , Silva Cândida , Soares Gisela
Published: September 2020

Skills are understood as key issues in the labour market and conceptualised as individual attributes needed to perform competent work. The distinction between hard and soft skills is one of the most used theoretical conceptualization – hard skills being understood as technical skills, required of professionals, and soft skills being seen as personal traits which are not specifically related to the function. One hundred years after the publication of Mann's A Study of Engineering Education (1918), and as employers expect a new level of readiness from new hires, the focus is on bridging the soft skills gap. However, most of the literature delves into mismatched expectations of both industry and educators, and little documentation can be found regarding the skills that future employees believe their employers will require.
Company Internships
Authors: Vila Noelia Araújo , Toubes Diego R. , Filipe de Araújo Arthur , Brea Jose Antonio Fraiz
Published: September 2020

Practical experience has increasingly become an important component of university training. Institutions have made efforts to provide students with the opportunity to experience business reality. To many students, a curricular internship is the first contact with the work market. The present work analyses this discipline in the context of the Master in Tourism Planning and Management of the University of Vigo. The research universe encompasses 182 internships, which took place from 2008 to 2014. Data was collected through structured questionnaires, which aimed to obtain information on the students' specific areas of interest within the tourism industry, their level of satisfaction with the internship program and whether they were hired by the host company afterwards. The findings show that both parts—students and companies—are highly satisfied with the experience in great majority of cases, and that curricular internships have been an indispensable tool for preparing these students to the demanding tourism industry labor market.
Designing Entrepreneurial Ecosystems to Support Resource Management in the Tourism Industry
Authors: Ryan Leah , Catena Manuel , Ros Pablo , Stephens Simon
Published: September 2020

The primary aim of this chapter is to review the literature on entrepreneurial ecosystems as it relates to the tourism sector. The authors do this in order to develop an understanding of the needs of the human resource management needs of tourism entrepreneurs. The experience of tourism entrepreneurs is documented in the academic literature. Jaafar and Rasoolimanesh report that the tourism industry is an important catalyst for regional economic activity. Therefore, the importance of this sector has caught the attention of policy makers and academics. However, research has identified that the area lacks the presence of effective and evidence-based theory. In this chapter, the authors review the literature on entrepreneurial ecosystems as it relates to the tourism industry. They provide recommendations for customizing entrepreneurial supports and ecosystems to maximize the success of human resource management and human capital development amongst tourism entrepreneurs.
Natural Language Interfaces to Databases
Authors: Pazos-Rangel Rodolfo A. , Rivera Gilberto , Martínez F. José A. , Gaspar Juana , Florencia-Juárez Rogelio
Published: September 2020

This chapter consists of an update of a previous publication. Specifically, the chapter aims at describing the most decisive advances in NLIDBs of this decade. Unlike many surveys on NLIDBs, for this chapter, the NLIDBs will be selected according to three relevance criteria: performance (i.e., percentage of correctly answered queries), soundness of the experimental evaluation, and the number of citations. To this end, the chapter will also include a brief review of the most widely used performance measures and query corpora for testing NLIDBs.
Mispronunciation Detection and Diagnosis Through a Chatbot
Authors: Martinez Marcos E. , López-Orozco Francisco , Olmos-Sánchez Karla , Sánchez-Solís Julia Patricia
Published: September 2020

The interaction between humans and machines has evolved; thus, the idea of being able to communicate with computers as we usually do with other people is becoming increasingly closer to coming true. Nowadays, it is common to come across intelligent systems named chatbots, which allow people to communicate by using natural language to hold conversations related to a specific domain. Chatbots have gained popularity in different kinds of sectors, such as customer service, marketing, sales, e-commerce, e-learning, travel, and even in education itself. This chapter aims to present a chatbot-based approach to learning English as a second language by using computer-assisted language learning systems.
Two New Challenging Resources to Evaluate Natural Language Interfaces to Databases Generated Based on Geobase and Geoquery
Authors: González-Barbosa Juan Javier , Frausto Solís Juan , Sánchez-Hernández Juan Paulo , Sanchez-Solís Julia Patricia
Published: September 2020

Databases and corpora are essential resources to evaluate the performance of Natural Language Interfaces to Databases (NLIDB). The Geobase database and the Geoquery corpus (Geoquery250 and Geoquery880) are among the most commonly used. In this chapter, the authors analyze both resources to offer two elaborate resources: 1) N-Geobase, which is a relational database, and 2) the corpus Geoquery270. The former follows the standard normalization procedure, then N-Geobase has a schema similar to enterprise databases. Geoquery270 consists of 270 queries selected from Geoquery880, preserving the same kind of natural language problems as Geoquery880, but with more challenging issues for an NLIDB than Geoquery250. To evaluate the new resources, they compared the performance of the NLIDB using Geoquery270 and Geoquery250. The results indicated that Geoquery270 was the harder corpus, while Geoquery250 is the easier one. Consequently, this chapter offers a broader range of resources to NLIDB designers.
Issues in the Syntactic Parsing of Queries for a Natural Language Interface to Databases
Authors: Gelbukh Alexander , Martínez F. José A. , Verastegui Andres , Ochoa Alberto
Published: September 2020

In this chapter, an exhaustive parser is presented. The parser was developed to be used in a natural language interface to databases (NLIDB) project. This chapter includes a brief description of state-of-the-art NLIDBs, including a description of the methods used and the performance of some interfaces. Some of the general problems in natural language interfaces to databases are also explained. The exhaustive parser was developed, aiming at improving the overall performance of the interface; therefore, the interface is also briefly described. This chapter also presents the drawbacks discovered during the experimental tests of the parser, which show that it is unsuitable for improving the NLIDB performance.
News Classification to Notify About Traffic Incidents in a Mexican City
Authors: Requejo Flores Alejandro , Ruiz Alejandro , López Abraham , Porras Raul
Published: September 2020

The primary objective of this chapter is to analyze the content retrieved from an RSS newspaper report written in the Spanish language and determine if it describes a traffic incident. The real-world case study occurs in a Mexican city with 1.5 million inhabitants, and its purpose is to offer an application to inform in real-time about traffic incidents that happen in the town, gathering its information from the reports published by a local newspaper. However, to do so, the authors first need to classify the articles and ignore those whose content does not imply any kind of road accident.
Geospatial Situation Analysis for the Prediction of Possible Cases of Suicide Using EBK
Authors: Ramirez López Carlos Manuel , Montes Rivera Martín , Ochoa Alberto , Ponce Gallegos Julio César , Guzmán Mendoza José Eder
Published: September 2020

This research presents the application of Empirical Bayesian Kriging, a geostatistical interpolation method. The case study is about suicide prevention. The dataset is composed of more than one million records, obtained from the report database of the Emergency Service 911 of the Mexican State of Aguascalientes. The purpose is to get prediction surfaces, probability, and standard error prediction for completed suicide cases. Here, the variations in the environment of suicide cases are relative to and dependent on economic, social, and cultural phenomena.
A Wrinkle in the Promise of Scrum
Authors: Chandrasekharan Aruna
Published: September 2020

Jeff Sutherland worked on the first Scrum project in 1993, but the framework as we know it now was formally coined by Jeff and Ken Schwaber in 1995. Since then IT divisions have seen the growing adoption of Scrum within their organization. However, this growth has been peppered with poor examples of adoption leading to lackluster results. This chapter explores why there is such a prevalence of “Bad” Scrum and the impact it has on the culture of the organization. This chapter explores the impact of poorly led transformations and will also provide some ways to reconsider how transformations should pivot.
An Agile Method to Support Students With Special Educational Needs in Regular Education After COVID-19 Contingency
Authors: González Alfredo Mendoza , Muñoz-Arteaga Jaime
Published: September 2020

In Mexico there are units of consultants that help schools to make students with special needs be included in regular education they provide the necessary help to enhance the learning process. Their work implies adapting the learning methodology, complementing the planned academic activities, adapting learning goals to the students' needs, providing specific technological tools, analyze the knowledge acquisition, etc. Additionally, there are many factors that can affect these goals and complicate the whole intervention process. The COVID-19 pandemic is making attitudinal changes of students, together with the long academic brake, and the forced on-line learning. Together, consultants, teachers, parents, and scientists have analyzed gaps in the intervention process of the supporting units, related with collaboration, teamwork, adaptations in activities and knowledge acquisition, and proposed a solution to it. In this chapter, the authors present Scrum process as a feasible solution, making easy and stronger the collaboration, role definition, and goals prioritization.
Using Data Mining Techniques to Discover Patterns in an Airline's Flight Hours Assignments
Authors: Martín Francisco Javier Villar , Sequera Jose Luis Castillo , Huerga Miguel Angel Navarro
Published: September 2020

The quality of a company's information system is essential and also its physical data model. In this article, the authors apply data mining techniques in order to generate knowledge from the information system's data model, and also to discover and understand hidden patterns within data that regulate the planning of flight hours of pilots and copilots in an airline. With this objective, they use Weka free software which offers a set of algorithms and visualization tools geared to data analysis and predictive modeling of information systems. Firstly, they apply clustering to study the information system and analyze data model; secondly, they apply association rules to discover connection patterns in data; and finally, they generate a decision tree to classify and extract more specific patterns. The authors suggest conclusions according these information system's data to improve future decision making in an airline's flight hours assignments.
Modeling of Aircraft and RPAS Data Transmission via Satellites
Authors: Grekhov Andrii Mikhailovich
Published: September 2020

This chapter is devoted to the modeling of aircraft data transmission via low-orbit satellites. Satellite communication channel models were designed, which allow to investigate BER dependencies on the type of signal modulation, information transfer rate, signal power, antenna diameters, and nonlinearity of a high power amplifier. Impact of a modulation type (BPSK, QPSK, 8PSK, 16QAM), Eb / N0, satellite transponder amplifier gain without and with coding on a BER was investigated. Effectiveness of error detection and correction was analyzed using classic linear block and convolutional codes. Free space path loss, AWGN, and radio frequency satellite channels were considered. MIMO 2 × 1 and 3 × 2 fading uplink/downlink channels with antenna diversity were analyzed. Results were compared with AWGN uplink/downlink channels. On the base of these models, channels integrity was investigated.
Modeling With Colored Petri Nets
Authors: Zaitsev Dmitry A. , Shmeleva Tatiana R.
Published: September 2020

Aviation and aerospace systems are complex and concurrent and require special tools for their specification, verification, and performance evaluation. The tool in demand should be easily integrated into the standard loop of model-driven development. Colored Petri nets represent a combination of a Petri net graph and a functional programming language ML that makes it powerful and convenient tool for specification of real-life system and solving both tasks: correctness proof i.e. verification and performance evaluation. This chapter studies basic and advanced features of CPN Tools – a powerful modeling system which uses graphical language of colored Petri nets. Starting with a concept of colored hierarhical timed Petri net, it goes through declaration of color sets and functions to peculiarities of hierarchical design of complex models and specification of timed characteristics. The authors accomplish the chapter with a real-life case study of performance evaluation for switched Ethernet network.
Simulators as an Essential Tool for Shaping the Competence of the Aviation Personnel
Authors: Kozuba Jarosław , Sładkowski Aleksander
Published: September 2020

The implementation of the aviation tasks, including the preparatory ones, is a difficult, complex task requiring from the aviation personnel a high level of general, technical, and specialist knowledge and a wide range of skills, appropriate to the type of technical tools and systems being at the disposal of the aviation personnel as well as the complexity and difficulty of their tasks. Particular importance is currently attached to the development of training devices used in the basic training and in-service training of the aviation personnel. The authors have referred to the role of simulators in achieving the desired level of specialist competence by flight personnel, including, among others, such issues as aircraft simulators development, and their application in the aviation training; aircraft simulators classification in accordance with current aviation regulations; essential functions performed by aviation simulators; flight simulator is an essential tool for basic and in-service training of the aviation personnel.
Development Specifics of the Tower Controller Intelligent Training System
Authors: Piliponok Oksana , Dzhuma Liudmyla
Published: September 2020

The activity of the tower controller is connected with the implementation of a rather complex set of measures to ensure takeoff and landing operations. In connection with this, the aviation specialist should possess the number of professional competencies, which are formed by mastering the theoretical material and consolidating it in practice. Frequently, the initial consolidation in practice is performed by using automated training systems, especially intelligent training systems are in a great demand. Therefore, this chapter is devoted to the specifics of the development of such type aviation-focused system, which are given on the example of the intelligent training system “Tower Controller.” The prototype of this system was developed at Flight Academy of the National Aviation University, Ukraine. Its key differential peculiarity is focused on major stages of the decision-making process of the tower controller instead of visualization from the tower window.
GNSS Positioning Enhancement Based on NLOS Multipath Biases Estimation Using Gaussian Mixture Noise
Authors: Bassma Guermah , Tayeb Sadiki , Hassan El Ghazi
Published: September 2020

Global navigation satellite systems (GNSS) have been widely used in many applications where positioning plays an important role. However, the performances of these applications can be degraded in urban canyons, due to Non-Line-Of-Sight (NLOS) and Multipath interference affecting GNSS signals. In order to ensure high accuracy positioning, this article proposes to model the NLOS and Multipath biases by Gaussian Mixture noise using Expectation Maximization (EM) algorithm. In this context, an approach to estimate the Multipath and NLOS biases for real time positioning is presented and statistical tests for searching the probability distribution of NLOS and Multipath biases are illustrated. Furthermore, a hybrid approach based on PF (Particle Filter) and EM algorithm for estimating user position in hard environment is presented. Using real GPS (Global Positioning System) signal, the efficiency of the proposed approach is shown, and a significant improvement of the positioning accuracy over the simple PF estimation is obtained.
Performance Efficiency Measurement of Airports
Authors: Kumar Anil , Dash Manoj Kumar , Sahu Rajendra
Published: September 2020

This article describes how to improve the overall efficiency and effectiveness of the aviation sector and also to source extra funding, the Government of India has paved the way for private investors through to a Public Private Partnership (PPP) model since the 1980s. This liberalization step in the Indian aviation market has minimized the institutional barriers which have hindered the freedom and flexibility of air transport operations among private investors. Now, competition within the aviation sector has become fiercer; the Airports Authority of India (AAI) and Public Private Partnership (PPP) in Indian airports are not only providing varied services, but also attracting consumers with new infrastructure and full modern facilities. The importance of this article is because after privatization, no studies have been conducted to examine the efficiency of Indian airports by using Data Envelopment Analysis (DEA). An output-oriented DEA model is employed to determine the efficiency score of airports by taking a sample of 15 airports, including airports run by PPP, for comparison. Output-oriented DEA calculates the efficiency by maximizing the outputs for a given level of inputs. Therefore, this article contributes to the existing literature on Indian airports. Based on available data, three variables - length of runways, terminal size and number of check-in counters, are used as inputs and two variables - passenger movement and aircraft movement, are used as outputs.
An Adult-Learner Approach to the Learning Design of Safety Management System Training in Aviation
Authors: Torrisi-Steele Geraldine , Carim Jr. Guido
Published: September 2020

The goal of training is to improve employee performance, and ultimately support organizational success. However, training does not always effectively transfer to workplaces to positively affect work practices, particularly because of disconnect between behaviourist approaches and contemporary work arrangements. The transfer of training to the workplace remains problematic. The present article is motivated by the need to challenge the status quo of training design and draw greater attention to learning design, beyond the confines of behaviourism. The aim of the article is to provoke critical discussion around learning theories and training design. We propose Knowles' adult learning principles and Mezirow's transformative learning theory, useful guide for the learning design of training. The learning design of a university-based safety management systems training course in aviation is discussed from the vantage point of the proposed guiding philosophy. Six specific strategies are presented supported by the evaluation of the course effectiveness conducted after the first iteration.
Study of Mechanical Properties and EMI Shielding Behaviour of Al6061 Hybrid Metal Matrix Composites
Authors: Gireesh Ch Hima , Ramji Koona , Prasad K.G Durga , Srinu Budumuru
Published: September 2020

In the present technological environment, the aerospace industry needs cutting-edge materials not only to meet the requirements such as lower weight and higher values of strength and stiffness, but also to protect against electromagnetic interference. In this article, an attempt has been made to prepare Al6061 hybrid metal matrix composites reinforced with varying percentages of SiC, Al2O3, and fly ash particulates through a stir-casting route. As per ASTM standards, various tests have been conducted to know the density, tensile strength, yield strength, and hardness. Simultaneously, all the prepared composites are tested for electromagnetic interference (EMI) shielding effectiveness (SE) under the X band frequency with the help of a vector network analyzer. In order to identify the composite possessing good mechanical properties, as well as shielding effectiveness, a TOPSIS methodology has been employed in this work. The present study reveals that the proposed hybrid composite contains 5% of each reinforcement material which shows better mechanical properties as well as good shielding effectiveness.
Dynamic Resource Management in High Throughput Satellite with Multi Port Amplifier (MPA)
Authors: Panthi Sunil , Eltawil Ahmed M.
Published: September 2020

The demand for data capacity has been growing, especially in the aviation and maritime industries and is expected to continue to grow in the foreseeable future. The satellite industry is moving to High Throughput Satellite (HTS) that are characterized by large numbers of small spot beams, frequency reuse, higher Equivalent Isotropically Radiated Power (EIRP) and higher Gain to Noise Temperature (G/T) to meet growing capacity demand. Multi-Port Amplifiers (MPA) increase the flexibility of HTS systems by allowing capacity to be allocated dynamically based on changing demand. This will allow capacity requirements to be planned based on the sum of the requirements across all beams rather than the peaks in each HTS beam. The authors propose a ground based solution that will maximize resource utilization of an HTS with an MPA and deliver the capacity dynamically based on demand. Maritime, commercial aviation, satellite based cellular backhaul, and disaster recovery services are the main applications that can benefit from the solution they propose. The authors' results show significant reduction in the overall capacity requirements because of the more efficient utilization of the satellite resources.
Information Technology for the Coordinated Control of Unmanned Aerial Vehicle Teams Based on the Scenario-Case Approach
Authors: Sherstjuk Vladimir , Zharikova Maryna
Published: September 2020

The authors present a dynamic scenario-case approach to coordinated control of heterogeneous ensembles of unmanned aerial vehicles, which use coordination patterns of activity in similar situations described as spatial configurations affected by observed events. The method of obtaining deviations for approximate spatial configurations, which allows obtaining elements of the safe vehicle's trajectories. The method of qualitative safety assessment is presented. It uses a soft level topology to obtaining blurred boundaries of dynamic safety domains using fuzzy soft level sets and allows finding suitable compensations of vehicles' activity scenarios that can both keep the spatial configuration and satisfy all safety restrictions. The authors demonstrate that the proposed approach significantly reduces the computational complexity of problem solving and provides the acceptable performance.