scholarly journals Robust Visual Relationship Detection towards Sparse Images in Internet-of-Things

2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Yang He ◽  
Guiduo Duan ◽  
Guangchun Luo ◽  
Xin Liu
Keyword(s):  
Image Data ◽  
Visual Features ◽  
Semantic Features ◽  
Knowledge Domain ◽  
Essential Information ◽  
Extra Information ◽  
Knowledge Based ◽  
Prominent Component ◽  
First Time ◽  
Deep Learning Model

Visual relationship can capture essential information for images, like the interactions between pairs of objects. Such relationships have become one prominent component of knowledge within sparse image data collected by multimedia sensing devices. Both the latent information and potential privacy can be included in the relationships. However, due to the high combinatorial complexity in modeling all potential relation triplets, previous studies on visual relationship detection have used the mixed visual and semantic features separately for each object, which is incapable for sparse data in IoT systems. Therefore, this paper proposes a new deep learning model for visual relationship detection, which is a novel attempt for cooperating computational intelligence (CI) methods with IoTs. The model imports the knowledge graph and adopts features for both entities and connections among them as extra information. It maps the visual features extracted from images into the knowledge-based embedding vector space, so as to benefit from information in the background knowledge domain and alleviate the impacts of data sparsity. This is the first time that visual features are projected and combined with prior knowledge for visual relationship detection. Moreover, the complexity of the network is reduced by avoiding the learning of redundant features from images. Finally, we show the superiority of our model by evaluating on two datasets.

scholarly journals UAV-Driven Structural Crack Detection and Location Determination Using Convolutional Neural Networks

Sensors ◽  
2021 ◽  
Vol 21 (8) ◽  
pp. 2650
Author(s):  
Daegyun Choi ◽  
William Bell ◽  
Donghoon Kim ◽  
Jichul Kim
Keyword(s):  
Visual Information ◽  
Crack Detection ◽  
Image Data ◽  
Image Processing Techniques ◽  
Location Determination ◽  
Aerial Vehicle ◽  
Using Data ◽  
Processing Techniques ◽  
Deep Learning Model ◽  
Structural Cracks

Structural cracks are a vital feature in evaluating the health of aging structures. Inspectors regularly monitor structures’ health using visual information because early detection of cracks on highly trafficked structures is critical for maintaining the public’s safety. In this work, a framework for detecting cracks along with their locations is proposed. Image data provided by an unmanned aerial vehicle (UAV) is stitched using image processing techniques to overcome limitations in the resolution of cameras. This stitched image is analyzed to identify cracks using a deep learning model that makes judgements regarding the presence of cracks in the image. Moreover, cracks’ locations are determined using data from UAV sensors. To validate the system, cracks forming on an actual building are captured by a UAV, and these images are analyzed to detect and locate cracks. The proposed framework is proven as an effective way to detect cracks and to represent the cracks’ locations.

STRUCTURAL AND SEMANTIC CHARACTERISTICS OF THE NAMES AND DESCRIPTIONS OF DISHES IN GERMAN RESTAURANT DISCOURSE

2021 ◽  
Vol 7 (2) ◽  
pp. 96-119
Author(s):  
Nadezhda G. KANTYSHEVA ◽  
Inna V. Solovyova
Keyword(s):  
Discourse Analysis ◽  
Semantic Features ◽  
Institutional Discourse ◽  
The World ◽  
Different Types ◽  
Complex Words ◽  
First Time ◽  
Comprehensive Study

This article is devoted to a comprehensive study of the structural and semantic features of dish names and their descriptions in German in the field of restaurant discourse. The study employs cognitive discourse analysis, elements of comparative and contextological approaches, taking into account linguocultural parameters. The relevance of the comprehensive study of the names of dishes in restaurant discourse is due to an increased interest in the parameterization of lexical units in different types of institutional discourse. The scientific novelty of this work lies in the fact that for the first time, within the framework of a restaurant menu, not only the nomination of a dish is considered, but also the structural and semantic characteristics of its description are analysed. An attempt is made to analyse a connection between the nominations of dishes and their description in the restaurant menu, as well as to determine the semantic dominants of the genre under study. It is concluded that the text of the menu as a whole presents a combination of the language for special purposes and the language of advertising. In interaction with extralinguistic factors, the nominations of dishes and their descriptions not only document the culture of food in society, but also reflect the ethnocultural picture of the world. Based on the analysis of the menu texts, it is established that structurally the names of dishes are complex words or phrases, built mainly according to the attributive model. The description of dishes performs the function of verbalizing the sensations of taste and clarifying the method of preparing dishes, characterizing the quality of dishes, their ingredients, and the intensity of taste. Evaluative parameters in descriptions are expressed at the lexical, grammatical, syntactic and stylistic levels.

scholarly journals Color Based Image Retrieval by Combining Various Features

2019 ◽  
Vol 9 (2) ◽  
pp. 454-460
Keyword(s):  
Image Retrieval ◽  
Retrieval System ◽  
Visual Features ◽  
Semantic Features ◽  
Retrieval Rate ◽  
Image Retrieval System ◽  
Mathematical Formulas ◽  
Image Set ◽  
Different Color ◽  
Image Collection

Content based image retrieval system retrieve the images according to the strong feature related to desire as color, texture and shape of an image. Although visual features cannot be completely determined by semantic features, but still semantic features can be integrate easily into mathematical formulas. This paper is focused on retrieval of images within a large image collection, based on color projection by applying segmentation and quantification on different color models and compared for good result. This method is applied on different categories of image set and evaluated its retrieval rate in different models

scholarly journals Aeromedical evacuation of a COVID-19 patient from a zonal hospital: A case report

2021 ◽  
Vol 65 ◽  
pp. 51-54
Author(s):  
S Patnaik ◽  
LK Dash ◽  
G Rajaram ◽  
C Chattophadhayay
Keyword(s):  
Armed Forces ◽  
Aeromedical Evacuation ◽  
Knowledge Based ◽  
Global Pandemic ◽  
Life Saving ◽  
Tertiary Healthcare ◽  
Airborne Rescue ◽  
Spread Of Infection ◽  
Saving Measure ◽  
First Time

Introduction: The coronavirus disease 2019 (COVID-19) pandemic has affected the whole world including many healthcare workers. In this era of ongoing global pandemic, the patient surge for aeromedical evacuation is going to increase. Case Details: A 54-year, male healthcare worker with no known co-morbidities, presented with complains of fever, myalgia, and sore throat at a zonal hospital of Indian Air Force in the northeast part of India. He was diagnosed with COVID-19 related bilateral extensive pneumonia. Despite of standard treatment, his condition deteriorated. An aeromedical evacuation of the patient was carried out to a tertiary healthcare centre at Delhi which involved 4-h of flying time. The Airborne Rescue Pod for Isolated Transportation (ARPIT) isolation pod was used to minimize the risk of contamination. Discussion: This was the first time that a COVID-19 patient was air evacuated in an isolation pod in Indian Armed Forces to the best of our knowledge. Based on our experience, we recommend that air evacuation of such a patient may be resorted to only as a life saving measure. The use of an isolation pod remains an unsettled issue; whereas, it gives absolute containment to spread of infection, it poses unique challenges in terms of handling the patient in case of an in-flight emergency. Certain modifications in the isolation pod have been recommended.

scholarly journals Experimental evidence for foraminiferal calcification under anoxia

2014 ◽  
Vol 11 (14) ◽  
pp. 4029-4038 ◽  
Author(s):  
M. P. Nardelli ◽  
C. Barras ◽  
E. Metzger ◽  
A. Mouret ◽  
H. L. Filipsson ◽  
...  
Keyword(s):  
Environmental Variability ◽  
Sediment Cores ◽  
Adult Mortality ◽  
Short Term ◽  
Essential Information ◽  
Ample Evidence ◽  
Anoxic Conditions ◽  
Inhibition Of Growth ◽  
Foraminiferal Species ◽  
First Time

Abstract. Benthic foraminiferal tests are widely used for paleoceanographic reconstructions from a range of different environments with varying dissolved oxygen concentrations in the bottom water. There is ample evidence that foraminifera can live in anoxic sediments. For some species, this is explained by a switch to facultative anaerobic metabolism (i.e. denitrification). Here we show for the first time that adult specimens of three benthic foraminiferal species are not only able to survive, but are also able to calcify under anoxic conditions, at various depths in the sediment, and with or without nitrates. In fact, several specimens of Ammonia tepida (1–4%), Bulimina marginata (8–24%) and Cassidulina laevigata (16–23%) were able to calcify at different redox fronts of sediment cores, under laboratory conditions. This demonstrates ongoing metabolic processes, even in micro-environments where denitrification is not possible. Earlier observations suggest that the disappearance of foraminiferal communities after prolonged anoxia is not due to instantaneous or strongly increased adult mortality. Here we show that it cannot be explained by an inhibition of growth through chamber addition either. Our observations of ongoing calcification under anoxic conditions mean that geochemical proxy data obtained from benthic foraminifera in settings experiencing intermittent anoxia have to be reconsidered. The analysis of whole single specimens or of their successive chambers may provide essential information about short-term environmental variability and/or the causes of anoxia.

scholarly journals SoK: Privacy-Preserving Collaborative Tree-based Model Learning

2021 ◽  
Vol 2021 (3) ◽  
pp. 182-203
Author(s):  
Sylvain Chatel ◽  
Apostolos Pyrgelis ◽  
Juan Ramón Troncoso-Pastoriza ◽  
Jean-Pierre Hubaux
Keyword(s):  
Learning Algorithm ◽  
Information Leakage ◽  
Privacy Preserving ◽  
Machine Learning Techniques ◽  
Model Learning ◽  
Protection Mechanism ◽  
Knowledge Based ◽  
Learning Techniques ◽  
Efficient Machine ◽  
First Time

Abstract Tree-based models are among the most efficient machine learning techniques for data mining nowadays due to their accuracy, interpretability, and simplicity. The recent orthogonal needs for more data and privacy protection call for collaborative privacy-preserving solutions. In this work, we survey the literature on distributed and privacy-preserving training of tree-based models and we systematize its knowledge based on four axes: the learning algorithm, the collaborative model, the protection mechanism, and the threat model. We use this to identify the strengths and limitations of these works and provide for the first time a framework analyzing the information leakage occurring in distributed tree-based model learning.

Question Answering

2012 ◽  
Author(s):  
Sanda Harabagiu ◽  
Dan Moldovan
Keyword(s):  
Language Processing ◽  
Question Answering ◽  
Document Retrieval ◽  
Semantic Features ◽  
Knowledge Based ◽  
Answer Extraction ◽  
Small Set ◽  
Processing Module ◽  
On Line ◽  
Processing Techniques

Textual Question Answering (QA) identifies the answer to a question in large collections of on-line documents. By providing a small set of exact answers to questions, QA takes a step closer to information retrieval rather than document retrieval. A QA system comprises three modules: a question-processing module, a document-processing module, and an answer extraction and formulation module. Questions may be asked about any topic, in contrast with Information Extraction (IE), which identifies textual information relevant only to a predefined set of events and entities. The natural language processing (NLP) techniques used in open-domain QA systems may range from simple lexical and semantic disambiguation of question stems to complex processing that combines syntactic and semantic features of the questions with pragmatic information derived from the context of candidate answers. This article reviews current research in integrating knowledge-based NLP methods with shallow processing techniques for QA.

scholarly journals Development and Validation of a Descriptive Cognitive Model for Predicting Usability Issues in a Low-Code Development Platform

2020 ◽  
pp. 001872082092042
Author(s):  
Carlos Silva ◽  
Joana Vieira ◽  
José C. Campos ◽  
Rui Couto ◽  
António N. Ribeiro
Keyword(s):  
Cognitive Model ◽  
Decomposition Methods ◽  
End Users ◽  
Successful Completion ◽  
Development Platform ◽  
Knowledge Based ◽  
Development And Validation ◽  
Criticality Analysis ◽  
First Time ◽  
Code Development

Objective The aim of the study was the development and evaluation of a Descriptive Cognitive Model (DCM) for the identification of three types of usability issues in a low-code development platform (LCDP). Background LCDPs raise the level of abstraction of software development by freeing end-users from implementation details. An effective LCDP requires an understanding of how its users conceptualize programming. It is necessary to identify the gap between the LCDP end-users’ conceptualization of programming and the actions required by the platform. It is also relevant to evaluate how the conceptualization of the programming tasks varies according to the end-users’ skills. Method DCMs are widely used in the description and analysis of the interaction between users and systems. We propose a DCM which we called PRECOG that combines task decomposition methods with knowledge-based descriptions and criticality analysis. This DCM was validated using empirical techniques to provide the best insight regarding the users’ interaction performance. Twenty programmers (10 experts, 10 novices) were observed using an LCDP and their interactions were analyzed according to our DCM. Results The DCM correctly identified several problems felt by first-time platform users. The patterns of issues observed were qualitatively different between groups. Experts mainly faced interaction-related problems, while novices faced problems attributable to a lack of programming skills. Conclusion By applying the proposed DCM we were able to predict three types of interaction problems felt by first-time users of the LCDP. Application The method is applicable when it is relevant to identify possible interaction problems, resulting from the users’ background knowledge being insufficient to guarantee a successful completion of the task at hand.

Altering the SightPlan knowledge-based systems

1992 ◽  
Vol 6 (1) ◽  
pp. 19-37 ◽  
Author(s):  
I. D. Tommelein ◽  
B. Hayes-Roth ◽  
R. E. Levitt
Keyword(s):  
Problem Solving ◽  
Knowledge Bases ◽  
Knowledge Based Systems ◽  
Knowledge Domain ◽  
Task Knowledge ◽  
Knowledge Based ◽  
Site Layout ◽  
Different Types ◽  
Control Knowledge ◽  
Construction Site Layout

SightPlan refers to several knowledge-based systems that address construction site layout. Five different versions were implemented and their components of expertise are described here. These systems are alterations of one another, differing either in the problems they solve, the problem-solving methods they apply, or the tasks they address. Because they share either control knowledge, domain concepts, or heuristics, and such knowledge is implemented in well-defined modular knowledge bases, these systems could easily re-use parts of one another. Experiments like those presented here may clarify the role played by different types of knowledge during problem solving, enabling researchers to gain a broader understanding of the generality of the domain and task knowledge that is embedded in KBSs and of the power of their systems.

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