scholarly journals Generating Artificial Outliers in the Absence of Genuine Ones — A Survey

2021 ◽  
Vol 15 (2) ◽  
pp. 1-37
Author(s):  
Georg Steinbuss ◽  
Klemens Böhm
Keyword(s):  
Experimental Study ◽  
Outlier Detection ◽  
Problem Formulation ◽  
Generative Models ◽  
Detection Algorithms ◽  
Research Fields ◽  
Wide Range ◽  
Further Development ◽  
Relevant Work

By definition, outliers are rarely observed in reality, making them difficult to detect or analyze. Artificial outliers approximate such genuine outliers and can, for instance, help with the detection of genuine outliers or with benchmarking outlier-detection algorithms. The literature features different approaches to generate artificial outliers. However, systematic comparison of these approaches remains absent. This surveys and compares these approaches. We start by clarifying the terminology in the field, which varies from publication to publication, and we propose a general problem formulation. Our description of the connection of generating outliers to other research fields like experimental design or generative models frames the field of artificial outliers. Along with offering a concise description, we group the approaches by their general concepts and how they make use of genuine instances. An extensive experimental study reveals the differences between the generation approaches when ultimately being used for outlier detection. This survey shows that the existing approaches already cover a wide range of concepts underlying the generation, but also that the field still has potential for further development. Our experimental study does confirm the expectation that the quality of the generation approaches varies widely, for example, in terms of the dataset they are used on. Ultimately, to guide the choice of the generation approach in a specific context, we propose an appropriate general-decision process. In summary, this survey comprises, describes, and connects all relevant work regarding the generation of artificial outliers and may serve as a basis to guide further research in the field.

scholarly journals Stroke Biomarkers: Progress and Challenges for Diagnosis, Prognosis, Differentiation, and Treatment

2010 ◽  
Vol 56 (1) ◽  
pp. 21-33 ◽  
Author(s):  
Amy K Saenger ◽  
Robert H Christenson
Keyword(s):  
Point Of Care ◽  
Clinical Settings ◽  
Acute Setting ◽  
Wide Range ◽  
Novel Biomarkers ◽  
Further Development ◽  
Improve Patient ◽  
Single Set ◽  
Neuroimaging Techniques

Abstract Background: Stroke is a devastating condition encompassing a wide range of pathophysiological entities that include thrombosis, hemorrhage, and embolism. Current diagnosis of stroke relies on physician clinical examination and is further supplemented with various neuroimaging techniques. A single set or multiple sets of blood biomarkers that could be used in an acute setting to diagnosis stroke, differentiate between stroke types, or even predict an initial/reoccurring stroke would be extremely valuable. Content: We discuss the current classification, diagnosis, and treatment of stroke, focusing on use of novel biomarkers (either solitary markers or multiple markers within a panel) that have been studied in a variety of clinical settings. Summary: The current diagnosis of stroke remains hampered and delayed due to lack of a suitable mechanism for rapid (ideally point-of-care), accurate, and analytically sensitive biomarker-based testing. There is a clear need for further development and translational research in this area. Potential biomarkers identified need to be transitioned quickly into clinical validation testing for further evaluation in an acute stroke setting; to do so would impact and improve patient outcomes and quality of life.

scholarly journals Rola funduszy UE w promowaniu inkluzji cyfrowej w polskich regionach

2021 ◽  
Vol 66 (2) ◽  
pp. 52-66
Author(s):  
Małgorzata Dziembała ◽  
Keyword(s):  
Financial Support ◽  
Social Groups ◽  
Digital Inclusion ◽  
Wide Range ◽  
Its Regions ◽  
Ict Development ◽  
Digital Exclusion ◽  
Further Development

The digitalisation process implies many benefits for its active participants. However, some companies, individuals and social groups are excluded from this process, which leads to digital inequalities. The aim of the article is to evaluate Polish regions (NUTS 2) in terms of their digital inclusion and to indicate the importance of EU funds in supporting digital inclusion in Poland. It is claimed that the role of external financial support from EU funds is important in promoting digital inclusion in Polish regions. Support for ICT development is becoming very important in Poland and its regions. In the perspective of 2014–2020, an operational programme dedicated to promoting the development and use of ICT was developed: Digital Poland 2014–2020 Operational Programme. Also within the framework of regional operational programmes implemented in the regions of Poland, including Silesia, priorities or undertakings related to the support for ICT development were identified. This requires the implementation of a wide range of projects, from the improvement of access to the Internet, through the improvement of accessibility and quality of public e-services, to further development of digital competences. Without prompt actions in this regard, the problem of digital exclusion in Poland and its regions will further intensify.

scholarly journals Centroid-Based Clustering with αβ-Divergences

Entropy ◽  
2019 ◽  
Vol 21 (2) ◽  
pp. 196 ◽  
Author(s):  
Auxiliadora Sarmiento ◽  
Irene Fondón ◽  
Iván Durán-Díaz ◽  
Sergio Cruces
Keyword(s):  
Real Data ◽  
Practical Applications ◽  
Theoretical Contribution ◽  
Closed Form Solutions ◽  
Research Fields ◽  
Wide Range ◽  
The Family ◽  
Two Parameters ◽  
Range Of Values

Centroid-based clustering is a widely used technique within unsupervised learning algorithms in many research fields. The success of any centroid-based clustering relies on the choice of the similarity measure under use. In recent years, most studies focused on including several divergence measures in the traditional hard k-means algorithm. In this article, we consider the problem of centroid-based clustering using the family of α β -divergences, which is governed by two parameters, α and β . We propose a new iterative algorithm, α β -k-means, giving closed-form solutions for the computation of the sided centroids. The algorithm can be fine-tuned by means of this pair of values, yielding a wide range of the most frequently used divergences. Moreover, it is guaranteed to converge to local minima for a wide range of values of the pair ( α , β ). Our theoretical contribution has been validated by several experiments performed with synthetic and real data and exploring the ( α , β ) plane. The numerical results obtained confirm the quality of the algorithm and its suitability to be used in several practical applications.

Developments in Security Mechanism Standards

2011 ◽  
pp. 185-246
Author(s):  
Chris Mitchell
Keyword(s):  
International Standards ◽  
Security Mechanism ◽  
Interested Reader ◽  
Research Papers ◽  
Wide Range ◽  
Quality Of Products ◽  
Cryptographic Techniques ◽  
Relevant Work

However, despite this wide range of standardisation activity, the ISO/IEC JTC1/SC27 work is unique in being both truly international and also aimed at general applications. As such, while we mention the relevant work of other standards bodies, the main focus of this chapter is the work of ISO/IEC JTC1/SC27. The main purpose of this chapter is to bring the international standards for cryptographic techniques to the widest possible audience. Adoption of these standards, which have received detailed scrutiny from experts worldwide, can only help to improve the quality of products incorporating security features. Note that much of the work described in this chapter is based on recent research. For brevity, references to research papers are not included here. For further information the interested reader should consult the bibliographies in the quoted standards, or the excellent encyclopaedic work (Menezes, van Oorschot and Vanstone, 1997).

scholarly journals Effects of sampling rate on automated fatigue recognition in surface EMG signals

2015 ◽  
Vol 1 (1) ◽  
pp. 80-84 ◽  
Author(s):  
Lorenz Kahl ◽  
Marcus Eger ◽  
Ulrich G. Hofmann
Keyword(s):  
Sampling Rate ◽  
Approximate Entropy ◽  
Surface Emg ◽  
Median Frequency ◽  
Spectral Moment ◽  
Detection Algorithms ◽  
Moment Ratio ◽  
Wide Range ◽  
Fatigue Detection

AbstractThis study investigated the effects different sampling rates may produce on the quality of muscle fatigue detection algorithms. sEMG signals were obtained from isometric contractions of the arm. Subsampled signals resulting in technically relevant sampling rates were computationally deduced from the original recordings. The spectral based fatigue recognition methods mean and median frequency as well as spectral moment ratio were included in this investigation, as well as the sample and the fuzzy approximate entropy. The resulting fatigue indices were evaluated with respect to noise and separability of different load levels. We concluded that the spectral moment ratio provides the best results in fatigue detection over a wide range of sampling rates.

scholarly journals Formation of roadside service facilities in Belarus: problem formulation and solutions

Vestnik MGSU ◽  
2019 ◽  
pp. 1505-1522
Author(s):  
Anzhelika V. Evstratenko
Keyword(s):  
Network Formation ◽  
Problem Formulation ◽  
Transport Infrastructure ◽  
Infrastructure Development ◽  
Service Network ◽  
Literary Sources ◽  
Wide Range ◽  
Scientific Papers ◽  
Theoretical Generalization ◽  
Further Development

Introduction. The article analyzes the domestic and foreign papers devoted to the study of the transport infrastructure of motor roads and recommendations for its further development. A special place is given to the issues of architectural and construction formation of roadside service network facilities due to the insufficient elaboration of the problem and the almost complete lack of implementation of the available research results. The research object is the structure and content of scientific papers on the most important aspects of forming the roadside infrastructure. The study aims to provide insight to the current situation in the arrangement of major motor roads in Belarus, reveal the most significant domestic and foreign research in accordance with the selected topics, and define the promising areas of building up a service system based on the gained experience and elaborated recommendations . Materials and methods. The study used systematization, structural and comparative analysis, the theoretical generalization of the data obtained in the detailed study of literary sources of domestic and foreign authors. Results. A review of a wide range of studies on the roadside service formation and development in Belarus and abroad was performed. The paper substantiated the need for developing theoretical and practical science-based recommendations based on the results achieved in several important areas. Conclusions. The paper considered and systematized the papers devoted to various aspects of roadside service network formation. The problem issues of infrastructure development and possible ways of solving urgent problems were identified. The most researched aspects of forming the roadside service objects were established. Issues of architectural and construction development of the network closely related to other areas require further studying. The study revealed that matters of motor road equipment with necessary facilities attract the attention of many researchers. Solving the problem of motor road infrastructural development on the quantitative and qualitative levels would assist in settling a whole series of economic, social, and engineering tasks.

Deep-learning-based image registration for nano-resolution tomographic reconstruction

2021 ◽  
Vol 28 (6) ◽  
Author(s):  
Tianyu Fu ◽  
Kai Zhang ◽  
Yan Wang ◽  
Jizhou Li ◽  
Jin Zhang ◽  
...  
Keyword(s):  
Deep Learning ◽  
Image Registration ◽  
High Efficiency ◽  
Tomographic Reconstruction ◽  
3D Structure ◽  
Correction Method ◽  
Full Field ◽  
Research Fields ◽  
Wide Range

Nano-resolution full-field transmission X-ray microscopy has been successfully applied to a wide range of research fields thanks to its capability of non-destructively reconstructing the 3D structure with high resolution. Due to constraints in the practical implementations, the nano-tomography data is often associated with a random image jitter, resulting from imperfections in the hardware setup. Without a proper image registration process prior to the reconstruction, the quality of the result will be compromised. Here a deep-learning-based image jitter correction method is presented, which registers the projective images with high efficiency and accuracy, facilitating a high-quality tomographic reconstruction. This development is demonstrated and validated using synthetic and experimental datasets. The method is effective and readily applicable to a broad range of applications. Together with this paper, the source code is published and adoptions and improvements from our colleagues in this field are welcomed.

scholarly journals Exploration of Outliers in If-Then Rule-Based Knowledge Bases

Entropy ◽  
2020 ◽  
Vol 22 (10) ◽  
pp. 1096
Author(s):  
Agnieszka Nowak-Brzezińska ◽  
Czesław Horyń
Keyword(s):  
Outlier Detection ◽  
Domain Knowledge ◽  
Clustering Algorithms ◽  
Knowledge Bases ◽  
Detection Methods ◽  
Complex Data ◽  
Rule Based ◽  
Detection Algorithms ◽  
The Subject

The article presents both methods of clustering and outlier detection in complex data, such as rule-based knowledge bases. What distinguishes this work from others is, first, the application of clustering algorithms to rules in domain knowledge bases, and secondly, the use of outlier detection algorithms to detect unusual rules in knowledge bases. The aim of the paper is the analysis of using four algorithms for outlier detection in rule-based knowledge bases: Local Outlier Factor (LOF), Connectivity-based Outlier Factor (COF), K-MEANS, and SMALLCLUSTERS. The subject of outlier mining is very important nowadays. Outliers in rules If-Then mean unusual rules, which are rare in comparing to others and should be explored by the domain expert as soon as possible. In the research, the authors use the outlier detection methods to find a given number of outliers in rules (1%, 5%, 10%), while in small groups, the number of outliers covers no more than 5% of the rule cluster. Subsequently, the authors analyze which of seven various quality indices, which they use for all rules and after removing selected outliers, improve the quality of rule clusters. In the experimental stage, the authors use six different knowledge bases. The best results (the most often the clusters quality was improved) are achieved for two outlier detection algorithms LOF and COF.

Application of TEM to Deformation, Wear, and Fracture of Ceramics

1974 ◽  
Vol 32 ◽  
pp. 472-473
Author(s):  
B. J. Hockey
Keyword(s):  
Wear Resistance ◽  
High Temperature ◽  
Mechanical Behavior ◽  
Brittle Materials ◽  
High Temperature Strength ◽  
Wide Range ◽  
Corrosive Environments ◽  
Further Development

Ceramics, such as Al2O3 and SiC have numerous current and potential uses in applications where high temperature strength, hardness, and wear resistance are required often in corrosive environments. These materials are, however, highly anisotropic and brittle, so that their mechanical behavior is often unpredictable. The further development of these materials will require a better understanding of the basic mechanisms controlling deformation, wear, and fracture.The purpose of this talk is to describe applications of TEM to the study of the deformation, wear, and fracture of Al2O3. Similar studies are currently being conducted on SiC and the techniques involved should be applicable to a wide range of hard, brittle materials.

Cognitive Health Counseling 40+

2013 ◽  
Vol 21 (1) ◽  
pp. 24-33 ◽  
Author(s):  
Anne Eschen ◽  
Franzisca Zehnder ◽  
Mike Martin
Keyword(s):  
Outcome Variable ◽  
Pilot Phase ◽  
Subjective Memory ◽  
Cognitive Health ◽  
Health Counseling ◽  
Agents Of Change ◽  
Main Outcome Variable ◽  
Further Development

This article introduces Cognitive Health Counseling 40+ (CH.CO40+), an individualized intervention that is conceptually based on the orchestration model of quality-of-life management ( Martin & Kliegel, 2010 ) and aims at improving satisfaction with cognitive health in adults aged 40 years and older. We describe the theoretically deduced characteristics of CH.CO40+, its target group, its multifactorial nature, its individualization, the application of subjective and objective measures, the role of participants as agents of change, and the rationale for choosing participants’ satisfaction with their cognitive health as main outcome variable. A pilot phase with 15 middle-aged and six older adults suggests that CH.CO40+ attracts, and may be particularly suitable for, subjective memory complainers. Implications of the pilot data for the further development of the intervention are discussed.

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