scholarly journals A new measurement of the 122Sb half-life

2021 ◽  
Author(s):  
G. D’Agostino ◽  
M. Di Luzio ◽  
N. E. Sharp ◽  
M. Oddone
Keyword(s):  
Half Life ◽  
State Of The Art ◽  
Uncertainty Budget ◽  
Standard Uncertainty ◽  
Reference Time ◽  
Detection Systems ◽  
Pile Up ◽  
Random Pulse ◽  
Uncertainty Level ◽  
Peak Count

AbstractFollowing significant discrepancies observed when decay-correcting 122Sb γ-peak count rates to a reference time, we looked at the literature supporting the presently recommended 2.7238(2) d (1σ) 122Sb half-life value as the source of these discrepancies. Investigation revealed that the value was derived from an inconsistent dataset and was published without reporting details of the experiment nor the uncertainty budget. In this work we performed a new measurement of the 122Sb half-life by measuring the 122Sb decay of neutron-activated antimony samples using state-of-the-art γ-detection systems characterized in terms of efficiency drift and random pulse pile-up. The measurement was carried out in two different laboratories with the same method. The resulting 2.69454(39) d  and 2.69388(30) d (1σ) 122Sb half-life values are in agreement at the evaluated 10–4 relative combined standard uncertainty level but are significantly lower (1.07% and 1.10% lower, respectively) than the preexisting recommended value.

scholarly journals Giant refractometric sensitivity by combining extreme optical Vernier effect and modal interference

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
André D. Gomes ◽  
Jens Kobelke ◽  
Jörg Bierlich ◽  
Jan Dellith ◽  
Manfred Rothhardt ◽  
...  
Keyword(s):  
State Of The Art ◽  
Single Mode ◽  
High Magnification ◽  
Magnification Factor ◽  
Detection Systems ◽  
Current State ◽  
Modal Interference ◽  
Vernier Effect ◽  
Index Unit ◽  
Conventional Detection

Abstract The optical Vernier effect consists of overlapping responses of a sensing and a reference interferometer with slightly shifted interferometric frequencies. The beating modulation thus generated presents high magnified sensitivity and resolution compared to the sensing interferometer, if the two interferometers are slightly out of tune with each other. However, the outcome of such a condition is a large beating modulation, immeasurable by conventional detection systems due to practical limitations of the usable spectral range. We propose a method to surpass this limitation by using a few-mode sensing interferometer instead of a single-mode one. The overlap response of the different modes produces a measurable envelope, whilst preserving an extremely high magnification factor, an order of magnification higher than current state-of-the-art performances. Furthermore, we demonstrate the application of that method in the development of a giant sensitivity fibre refractometer with a sensitivity of around 500 µm/RIU (refractive index unit) and with a magnification factor over 850.

scholarly journals Automatic Identification of Harmful, Aggressive, Abusive, and Offensive Language on the Web: A Survey of Technical Biases Informed by Psychology Literature

2021 ◽  
Vol 4 (3) ◽  
pp. 1-56
Author(s):  
Agathe Balayn ◽  
Jie Yang ◽  
Zoltan Szlavik ◽  
Alessandro Bozzon
Keyword(s):  
Computer Science ◽  
State Of The Art ◽  
Automatic Detection ◽  
Automatic Identification ◽  
Machine Learning Classification ◽  
Detection Systems ◽  
Science Community ◽  
Psychology Literature ◽  
Offensive Language ◽  
The Web

The automatic detection of conflictual languages (harmful, aggressive, abusive, and offensive languages) is essential to provide a healthy conversation environment on the Web. To design and develop detection systems that are capable of achieving satisfactory performance, a thorough understanding of the nature and properties of the targeted type of conflictual language is of great importance. The scientific communities investigating human psychology and social behavior have studied these languages in details, but their insights have only partially reached the computer science community. In this survey, we aim both at systematically characterizing the conceptual properties of online conflictual languages, and at investigating the extent to which they are reflected in state-of-the-art automatic detection systems. Through an analysis of psychology literature, we provide a reconciled taxonomy that denotes the ensemble of conflictual languages typically studied in computer science. We then characterize the conceptual mismatches that can be observed in the main semantic and contextual properties of these languages and their treatment in computer science works; and systematically uncover resulting technical biases in the design of machine learning classification models and the dataset created for their training. Finally, we discuss diverse research opportunities for the computer science community and reflect on broader technical and structural issues.

Host–Based Intrusion Detection Systems

2014 ◽  
pp. 184-213
Author(s):  
Vít Bukač ◽  
Vashek Matyáš
Keyword(s):  
Intrusion Detection ◽  
Detection Method ◽  
State Of The Art ◽  
Research Trends ◽  
The State ◽  
Intrusion Detection Systems ◽  
Future Directions ◽  
Detection Systems ◽  
Research Findings ◽  
Art Research

In this chapter, the reader explores both the founding ideas and the state-of-the-art research on host-based intrusion detection systems. HIDSs are categorized by their intrusion detection method. Each category is thoroughly investigated, and its limitations and benefits are discussed. Seminal research findings and ideas are presented and supplied with comments. Separate sections are devoted to the protection against tampering and to the HIDS evasion techniques that are employed by attackers. Existing research trends are highlighted, and possible future directions are suggested.

scholarly journals Proposed standardized definitions for vertical resolution and uncertainty in the NDACC lidar ozone and temperature algorithms – Part 2: Ozone DIAL uncertainty budget

2016 ◽  
Vol 9 (8) ◽  
pp. 4051-4078 ◽  
Author(s):  
Thierry Leblanc ◽  
Robert J. Sica ◽  
Joanna A. E. van Gijsel ◽  
Sophie Godin-Beekmann ◽  
Alexander Haefele ◽  
...  
Keyword(s):  
Cross Sections ◽  
Stratospheric Ozone ◽  
Random Noise ◽  
Uncertainty Budget ◽  
Standard Uncertainty ◽  
Atmospheric Composition ◽  
Differential Absorption ◽  
Differential Absorption Lidar ◽  
Processing Chain ◽  
The Individual

Abstract. A standardized approach for the definition, propagation, and reporting of uncertainty in the ozone differential absorption lidar data products contributing to the Network for the Detection for Atmospheric Composition Change (NDACC) database is proposed. One essential aspect of the proposed approach is the propagation in parallel of all independent uncertainty components through the data processing chain before they are combined together to form the ozone combined standard uncertainty. The independent uncertainty components contributing to the overall budget include random noise associated with signal detection, uncertainty due to saturation correction, background noise extraction, the absorption cross sections of O3, NO2, SO2, and O2, the molecular extinction cross sections, and the number densities of the air, NO2, and SO2. The expression of the individual uncertainty components and their step-by-step propagation through the ozone differential absorption lidar (DIAL) processing chain are thoroughly estimated. All sources of uncertainty except detection noise imply correlated terms in the vertical dimension, which requires knowledge of the covariance matrix when the lidar signal is vertically filtered. In addition, the covariance terms must be taken into account if the same detection hardware is shared by the lidar receiver channels at the absorbed and non-absorbed wavelengths. The ozone uncertainty budget is presented as much as possible in a generic form (i.e., as a function of instrument performance and wavelength) so that all NDACC ozone DIAL investigators across the network can estimate, for their own instrument and in a straightforward manner, the expected impact of each reviewed uncertainty component. In addition, two actual examples of full uncertainty budget are provided, using nighttime measurements from the tropospheric ozone DIAL located at the Jet Propulsion Laboratory (JPL) Table Mountain Facility, California, and nighttime measurements from the JPL stratospheric ozone DIAL located at Mauna Loa Observatory, Hawai'i.

scholarly journals Non-EEG seizure-detection systems and potential SUDEP prevention: State of the art

Seizure ◽  
2013 ◽  
Vol 22 (5) ◽  
pp. 345-355 ◽  
Author(s):  
Anouk Van de Vel ◽  
Kris Cuppens ◽  
Bert Bonroy ◽  
Milica Milosevic ◽  
Katrien Jansen ◽  
...  
Keyword(s):  
State Of The Art ◽  
Seizure Detection ◽  
Detection Systems

Seismic RTDT: Real-Time Digital Twin for Boosting Performance of Seismic Operations

2019 ◽  
Author(s):  
Severin Sadjina ◽  
Stian Skjong ◽  
Armin Pobitzer ◽  
Lars T. Kyllingstad ◽  
Roy-Jostein Fiskerstrand ◽  
...  
Keyword(s):  
Machine Learning ◽  
Real Time ◽  
State Of The Art ◽  
Seismic Survey ◽  
Digital Twin ◽  
Detection Systems ◽  
Early Results ◽  
Actual Equipment ◽  
Automation Systems ◽  
And Control

Abstract Here, we present the R&D project Real-Time Digital Twin for Boosting Performance of Seismic Operations, which aims at increasing the overall operational efficiency of seismic vessels through digitisation and automation. The cornerstone in this project is the development of a real-time digital twin (RTDT) — a sophisticated mathematical model and state estimator of all the in-sea seismic equipment, augmented with real-time measurements from the actual equipment. This provides users and systems on-board the vessel with a live digital representation of the state of the equipment during operations. By combining the RTDT with state-of-the-art methods in machine learning and control theory, the project will develop new advisory and automation systems that improve the efficiency of seismic survey operations, reduce the risk of equipment damage, improve health monitoring and fault detection systems, and improve the quality of the seismic data. This will lead to less unproductive time, reduced costs, reduced fuel consumption and reduced emissions for a given operational scope. The main focus in this paper is the presentation of today’s challenges in offshore seismic surveys, and how state-of-the-art technology can be adopted to improve various operations. We discuss how simulation technology, machine learning and live sensor measurements can be integrated in on-board decision support and automation systems, and highlight the importance of such systems for designing the complex, autonomous offshore vessels of the future. Finally, we present some early results from the project in the form of two brief case studies.

scholarly journals Adaptive Real-Time Method for Anomaly Detection Using Machine Learning

Proceedings ◽  
2020 ◽  
Vol 54 (1) ◽  
pp. 38
Author(s):  
David Novoa-Paradela ◽  
Óscar Fontenla-Romero ◽  
Bertha Guijarro-Berdiñas
Keyword(s):  
Machine Learning ◽  
Anomaly Detection ◽  
Real Time ◽  
State Of The Art ◽  
Learning Ability ◽  
Convex Hulls ◽  
Detection Systems ◽  
Anomalous Data ◽  
Frequent Use ◽  
Normal Class

Anomaly detection is a sub-area of machine learning that deals with the development of methods to distinguish among normal and anomalous data. Due to the frequent use of anomaly-detection systems in monitoring and the lack of methods capable of learning in real time, this research presents a new method that provides such online adaptability. The method bases its operation on the properties of scaled convex hulls. It begins building a convex hull, using a minimum set of data, that is adapted and subdivided along time to accurately fit the boundary of the normal class data. The model has online learning ability and its execution can be carried out in a distributed and parallel way, all of them interesting advantages when dealing with big datasets. The method has been compared to other state-of-the-art algorithms demonstrating its effectiveness.

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