Multicriteria decision frontiers for prescription anomaly detection over time

2021 ◽  
pp. 1-21
Author(s):  
Babak Zafari ◽  
Tahir Ekin ◽  
Fabrizio Ruggeri
Keyword(s):  
Anomaly Detection ◽  
Multicriteria Decision ◽  
Over Time

scholarly journals Anomaly detection in server metrics with use of one-sided median algorithm

2017 ◽  
Vol 9 (1) ◽  
pp. 5-22
Author(s):  
Szymon Zacher ◽  
Przemysław Ryba
Keyword(s):  
Time Series ◽  
Anomaly Detection ◽  
Detection Rate ◽  
Short Description ◽  
Algorithm Performance ◽  
Mail Service ◽  
Over Time ◽  
Simple Production ◽  
Good Detection

AbstractIn this paper we consider the problem of anomaly detection over time series metrics data took from one of corporate grade mail service cluster. We propose the algorithm based on one-sided median concept and present some results of experiments showing impact of parameters settings on algorithm performance. In addition we present short description of classes of anomalies discovered in monitored system. Proposed one-sided median based algorithm shows great robustness and good detection rate and can be considered as possible simple production ready solution.

Toward a Deeper Understanding of Personnel Anomaly Detection

2011 ◽  
pp. 206-215
Author(s):  
Shuyuan Mary Ho
Keyword(s):  
Anomaly Detection ◽  
Behavioral Outcomes ◽  
Sensitive Information ◽  
Potential Threat ◽  
Insider Threats ◽  
Internal Resources ◽  
Corporate Security ◽  
Systems Perspective ◽  
Individual Privacy ◽  
Over Time

Recent threats to prominent organizations have greatly increased social awareness of the need for information security. Many measures have been designed and developed to guard against threats from outsider attacks. Technologies are commonly implemented to actively prohibit unauthorized connection and/or limit access to corporate internal resources; however, threats from insiders are even more subtle and complex. Personnel whom are inherently trusted have valuable internal corporate knowledge that could impact profits or organizational integrity. They are often a source of potential threat within the corporation, through leaking or damaging confidential and sensitive information—whether intentionally or unintentionally. Identifying and detecting anomalous personnel behavior and potential threats are concomitantly important. It can be done by observation and evaluation of communicated intentions and behavioral outcomes of the employee over time. While human observations are subject to fallibility and systems statistics are subject to false positives, personnel anomaly detection correlates observations on the change of personnel trustworthiness to provide for both corporate security and individual privacy. In this paper, insider threats are identified as one of the significant problems to corporate security. Some insightful discussions of personnel anomaly detection are provided, from both a social and a systems perspective.

scholarly journals Semi-Supervised Time Series Anomaly Detection Based on Statistics and Deep Learning

2021 ◽  
Vol 11 (15) ◽  
pp. 6698
Author(s):  
Jehn-Ruey Jiang ◽  
Jian-Bin Kao ◽  
Yu-Lin Li
Keyword(s):  
Time Series ◽  
Deep Learning ◽  
Anomaly Detection ◽  
Stationary Time Series ◽  
Test Time ◽  
Pearson Product Moment Correlation ◽  
Novel Technologies ◽  
Univariate Time Series ◽  
Comparison Results ◽  
Over Time

Thanks to the advance of novel technologies, such as sensors and Internet of Things (IoT) technologies, big amounts of data are continuously gathered over time, resulting in a variety of time series. A semi-supervised anomaly detection framework, called Tri-CAD, for univariate time series is proposed in this paper. Based on the Pearson product-moment correlation coefficient and Dickey–Fuller test, time series are first categorized into three classes: (i) periodic, (ii) stationary, and (iii) non-periodic and non-stationary time series. Afterwards, different mechanisms using statistics, wavelet transform, and deep learning autoencoder concepts are applied to different classes of time series for detecting anomalies. The performance of the proposed Tri-CAD framework is evaluated by experiments using three Numenta anomaly benchmark (NAB) datasets. The performance of Tri-CAD is compared with those of related methods, such as STL, SARIMA, LSTM, LSTM with STL, and ADSaS. The comparison results show that Tri-CAD outperforms the others in terms of the precision, recall, and F1-score.

Multicriteria Decision Support Model for Selection of Tinplate Suppliers

2020 ◽  
pp. 111-138
Author(s):  
Rafaela Ribeiro Pinho ◽  
Ana Paula Lopes
Keyword(s):  
Decision Support ◽  
Evaluation Process ◽  
Supplier Evaluation ◽  
Decision Support Model ◽  
Ahp Method ◽  
Multicriteria Decision ◽  
Promethee Method ◽  
Multicriteria Decision Support ◽  
Over Time ◽  
Selection Of

The evaluation and selection of suppliers has been an issue of great strategic importance over time. In this way, a structured evaluation is crucial, considering several criteria. This work reviews several multicriteria decision support methodologies explored in the literature to solve the supplier evaluation process based on CAN company specifications, strategies, and requirements. Considering the characteristics of each supplier and a set of criteria with different weights, the AHP method and the PROMETHEE method are applied to establish a ranking according to the performance in the selected criteria. In addition, to help the company make the best decision, an analysis of ranking stability is performed by varying the weights assigned to the criteria. The study and models developed were easy to apply and understand, meeting the specified objectives.

scholarly journals Explainable Anomaly Detection in Videos Based on the Description of Atomic Actions

2021 ◽  
Author(s):  
Andrei de Souza Inácio ◽  
Raphael Marinho Teixeira ◽  
Heitor Silvério Lopes
Keyword(s):  
Anomaly Detection ◽  
Natural Language ◽  
Experimental Results ◽  
False Alarms ◽  
Human Behaviors ◽  
Atomic Actions ◽  
Atomic Action ◽  
Human Attributes ◽  
Over Time ◽  
Detection And Recognition

Anomaly detection in surveillance videos is an exhaustive and tedious task to be performed manually by humans. Many methods have been proposed to detect anomalous events by learning normal patterns and differentiate them from abnormal ones. However, these methods often suffer from false alarms, as human behaviors and environments can change over time. In addition, these methods fail to discriminate the types of anomalies that can occur, especially in anomalies performed by humans. This work presents an approach to detect anomalous events based on atomic action descriptions. It combines a tracking people method with atomic action detection and recognition network to understand video events and generate atomic descriptions. Besides detecting the anomalies, the proposed approach can also describe the anomalous action with human attributes in natural language. Anomalies are detected based on the generated descriptions of the scene. Experimental results show the effectiveness of our approach, presenting an average F1-Score of 87%.

Social transmission bias and the cultural evolution of folk-economic beliefs

2018 ◽  
Vol 41 ◽  
Author(s):  
David Hirshleifer ◽  
Siew Hong Teoh
Keyword(s):  
Cultural Evolution ◽  
Social Transmission ◽  
Cognitive Approach ◽  
Economic Problems ◽  
Economic Attitudes ◽  
The Social ◽  
Economic Beliefs ◽  
Over Time

AbstractEvolved dispositions influence, but do not determine, how people think about economic problems. The evolutionary cognitive approach offers important insights but underweights the social transmission of ideas as a level of explanation. The need for asocialexplanation for the evolution of economic attitudes is evidenced, for example, by immense variations in folk-economic beliefs over time and across individuals.

Articulatory Generalization in Two Word-Medial, Ambisyllabic Contexts

1988 ◽  
Vol 19 (3) ◽  
pp. 251-258 ◽  
Author(s):  
Virginia I. Wolfe ◽  
Suzanne D. Blocker ◽  
Norma J. Prater
Keyword(s):  
Common View ◽  
Perceptual Salience ◽  
The Common ◽  
Unitary Concept ◽  
Over Time

Articulatory generalization of velar cognates /k/, /g/ in two phonologically disordered children was studied over time as a function of sequential word-morpheme position training. Although patterns of contextual acquisition differed, correct responses to the word-medial, inflected context (e.g., "picking," "hugging") occurred earlier and exceeded those to the word-medial, noninflected context (e.g., "bacon," "wagon"). This finding indicates that the common view of the word-medial position as a unitary concept is an oversimplification. Possible explanations for superior generalization to the word-medial, inflected position are discussed in terms of coarticulation, perceptual salience, and the representational integrity of the word.

Treatment Fidelity Procedures for an Aphasia Intervention Within a Randomized Controlled Trial: Design, Feasibility, and Results

2020 ◽  
Vol 29 (1S) ◽  
pp. 412-424
Author(s):  
Elissa L. Conlon ◽  
Emily J. Braun ◽  
Edna M. Babbitt ◽  
Leora R. Cherney
Keyword(s):  
Randomized Controlled Trial ◽  
Controlled Trial ◽  
Treatment Protocol ◽  
Treatment Fidelity ◽  
Protocol Adherence ◽  
Study Condition ◽  
Randomized Controlled ◽  
Aphasia Therapy ◽  
Percent Accuracy ◽  
Over Time

Purpose This study reports on the treatment fidelity procedures implemented during a 5-year randomized controlled trial comparing intensive and distributed comprehensive aphasia therapy. Specifically, the results of 1 treatment, verb network strengthening treatment (VNeST), are examined. Method Eight participants were recruited for each of 7 consecutive cohorts for a total of 56 participants. Participants completed 60 hr of aphasia therapy, including 15 hr of VNeST. Two experienced speech-language pathologists delivered the treatment. To promote treatment fidelity, the study team developed a detailed manual of procedures and fidelity checklists, completed role plays to standardize treatment administration, and video-recorded all treatment sessions for review. To assess protocol adherence during treatment delivery, trained research assistants not involved in the treatment reviewed video recordings of a subset of randomly selected VNeST treatment sessions and completed the fidelity checklists. This process was completed for 32 participants representing 2 early cohorts and 2 later cohorts, which allowed for measurement of protocol adherence over time. Percent accuracy of protocol adherence was calculated across clinicians, cohorts, and study condition (intensive vs. distributed therapy). Results The fidelity procedures were sufficient to promote and verify a high level of adherence to the treatment protocol across clinicians, cohorts, and study condition. Conclusion Treatment fidelity strategies and monitoring are feasible when incorporated into the study design. Treatment fidelity monitoring should be completed at regular intervals during the course of a study to ensure that high levels of protocol adherence are maintained over time and across conditions.

Percutaneous Tracheostomy: A Multidisciplinary Approach

2008 ◽  
Vol 18 (2) ◽  
pp. 87-98 ◽  
Author(s):  
Vinciya Pandian ◽  
Thai Tran Nguyen ◽  
Marek Mirski ◽  
Nasir Islam Bhatti
Keyword(s):  
Health Care ◽  
Quality Assurance ◽  
Data Collection ◽  
Health Care Professionals ◽  
Multidisciplinary Approach ◽  
Percutaneous Tracheostomy ◽  
Johns Hopkins Hospital ◽  
Prospective Data ◽  
Comprehensive Service ◽  
Over Time

Abstract The techniques of performing a tracheostomy has transformed over time. Percutaneous tracheostomy is gaining popularity over open tracheostomy given its advantages and as a result the number of bedside tracheostomies has increased necessitating the need for a Percutaneous Tracheostomy Program. The Percutaneous Tracheostomy Program at the Johns Hopkins Hospital is a comprehensive service that provides care to patients before, during, and after a tracheostomy with a multidisciplinary approach aimed at decreasing complications. Education is provided to patients, families, and health-care professionals who are involved in the management of a tracheostomy. Ongoing prospective data collection serves as a tool for Quality Assurance.

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