A Behavior-Based Autonomous Agent Possessing System Detectable Error

2000 ◽  
Author(s):  
Keith L. Bearden ◽  
Mark L. Nowack ◽  
Wade O. Troxell
Keyword(s):  
Error Detection ◽  
System Level ◽  
Autonomous Agent ◽  
Main Function ◽  
External Observer ◽  
Processor Time ◽  
Detection Approach ◽  
Error Space ◽  
Behavior Based ◽  
Sensor Errors

Abstract A great deal of recent research is devoted to increasing the robustness and capability of behavior-based robotic systems. Behavior-based systems are extremely susceptible to sensor errors. To overcome this, most researchers have added processors to the basic system to compare multiple redundant sensors. This is an effective error detection approach, but it costs processor time, increases complexity, and can actually reduce reliability. Most importantly such systems lack the ability to self-detect error. All other forms of representation are unable to determine system level functional failures without the use of an external observer. This paper proposes a divergence from detecting sensor error to detecting functional error. By looking at the functional error space, the system can determine an error and move away from the error. This method will not determine a sensory failure as the cause of the functional failure; rather, this method determines that the system is not performing its main function and then tries something else. This leads to a system that can function with the loss of forty percent of its sensory capability for either the case of a disconnected sensor or a stuck sensor.

scholarly journals A Tip–Tilt and Piston Detection Approach for Segmented Telescopes

Photonics ◽  
2020 ◽  
Vol 8 (1) ◽  
pp. 3
Author(s):  
Shun Qin ◽  
Wai Kin Chan
Keyword(s):  
Error Detection ◽  
Phase Retrieval ◽  
Dynamic Range ◽  
Detection Accuracy ◽  
Wavefront Sensing ◽  
Next Generation ◽  
Large Aperture ◽  
Detection Approach ◽  
Segmented Mirror ◽  
And Control

Accurate segmented mirror wavefront sensing and control is essential for next-generation large aperture telescope system design. In this paper, a direct tip–tilt and piston error detection technique based on model-based phase retrieval with multiple defocused images is proposed for segmented mirror wavefront sensing. In our technique, the tip–tilt and piston error are represented by a basis consisting of three basic plane functions with respect to the x, y, and z axis so that they can be parameterized by the coefficients of these bases; the coefficients then are solved by a non-linear optimization method with the defocus multi-images. Simulation results show that the proposed technique is capable of measuring high dynamic range wavefront error reaching 7λ, while resulting in high detection accuracy. The algorithm is demonstrated as robust to noise by introducing phase parameterization. In comparison, the proposed tip–tilt and piston error detection approach is much easier to implement than many existing methods, which usually introduce extra sensors and devices, as it is a technique based on multiple images. These characteristics make it promising for the application of wavefront sensing and control in next-generation large aperture telescopes.

Achieving cost-efficient fail-operational behavior based on inherent redundancy at the system level

2021 ◽  
pp. 104380
Author(s):  
Tobias Dörr ◽  
Timo Sandmann ◽  
Patrick Friederich ◽  
Arnd Leitner ◽  
Jürgen Becker
Keyword(s):  
System Level ◽  
Behavior Based ◽  
Cost Efficient

scholarly journals From foodwebs to gene regulatory networks (GRNs) - weak repressions by microRNAs confer system stability

2017 ◽  
Author(s):  
Yuxin Chen ◽  
Yang Shen ◽  
Stefano Allesina ◽  
Chung-I Wu
Keyword(s):  
Regulatory Networks ◽  
Stability Control ◽  
System Stability ◽  
Yeast Cells ◽  
System Level ◽  
Main Function ◽  
Highly Expressed Genes ◽  
Gene Regulatory ◽  
Mechanistic Basis ◽  
The Stability

AbstractMore than 30% of mRNAs are repressed by microRNAs (miRNAs) but most repressions are too weak to have a phenotypic consequence. The diffuse actions have been a central conundrum in understanding the functions of miRNAs. By applying the May-Wigner theory used in foodweb studies, we show that i) weak repressions cumulatively enhance the stability of gene regulatory network (GRN), and ii) broad and weak repressions confer greater stability than a few strong ones. Transcriptome data show that yeast cells, which do not have miRNAs, use strong and non-specific mRNA degradation to stabilize their GRN; in contrast, human cells use miRNAs to increase degradation more modestly and selectively. Simulations indicate that miRNA repressions should be distributed broadly to >25% of mRNAs, in agreement with observations. As predicted, extremely highly expressed genes are avoided and transcription factors are preferred by miRNAs. In conclusion, the diffuse repression by miRNAs is likely a system-level strategy for enhancing GRN stability. This stability control may be the mechanistic basis of “canalization” (i.e., developmental homeostasis within each species), sometimes hypothesized to be a main function of miRNAs.

scholarly journals Consistency Index-Based Sensor Fault Detection System for Nuclear Power Plant Emergency Situations Using an LSTM Network

Sensors ◽  
2020 ◽  
Vol 20 (6) ◽  
pp. 1651 ◽  
Author(s):  
Jeonghun Choi ◽  
Seung Jun Lee
Keyword(s):  
Power Plant ◽  
Nuclear Power Plant ◽  
Error Detection ◽  
Nuclear Power ◽  
Detection System ◽  
Emergency Situation ◽  
Consistency Index ◽  
Sensor Error ◽  
Emergency Situations ◽  
Sensor Errors

A nuclear power plant (NPP) consists of an enormous number of components with complex interconnections. Various techniques to detect sensor errors have been developed to monitor the state of the sensors during normal NPP operation, but not for emergency situations. In an emergency situation with a reactor trip, all the plant parameters undergo drastic changes following the sudden decrease in core reactivity. In this paper, a machine learning model adopting a consistency index is suggested for sensor error detection during NPP emergency situations. The proposed consistency index refers to the soundness of the sensors based on their measurement accuracy. The application of consistency index labeling makes it possible to detect sensor error immediately and specify the particular sensor where the error occurred. From a compact nuclear simulator, selected plant parameters were extracted during typical emergency situations, and artificial sensor errors were injected into the raw data. The trained system successfully generated output that gave both sensor error states and error-free states.

scholarly journals An Investigation into Soft Error Detection Efficiency at Operating System Level

2014 ◽  
Vol 2014 ◽  
pp. 1-8 ◽  
Author(s):  
Seyyed Amir Asghari ◽  
Okyay Kaynak ◽  
Hassan Taheri
Keyword(s):  
Operating System ◽  
Error Detection ◽  
Detection Efficiency ◽  
Soft Errors ◽  
Control Flow ◽  
Soft Error ◽  
System Level ◽  
Occurrence Rate ◽  
Transient Errors ◽  
System Components

Electronic equipment operating in harsh environments such as space is subjected to a range of threats. The most important of these is radiation that gives rise to permanent and transient errors on microelectronic components. The occurrence rate of transient errors is significantly more than permanent errors. The transient errors, or soft errors, emerge in two formats: control flow errors (CFEs) and data errors. Valuable research results have already appeared in literature at hardware and software levels for their alleviation. However, there is the basic assumption behind these works that the operating system is reliable and the focus is on other system levels. In this paper, we investigate the effects of soft errors on the operating system components and compare their vulnerability with that of application level components. Results show that soft errors in operating system components affect both operating system and application level components. Therefore, by providing endurance to operating system level components against soft errors, both operating system and application level components gain tolerance.

Rule selection versus rule execution in preschoolers: An error-detection approach.

1999 ◽  
Vol 35 (3) ◽  
pp. 770-780 ◽  
Author(s):  
Sophie Jacques ◽  
Philip David Zelazo ◽  
Natasha Z. Kirkham ◽  
Tanya K. Semcesen
Keyword(s):  
Error Detection ◽  
Rule Selection ◽  
Detection Approach

MoG: Behavior-Obfuscation Resistance Malware Detection

2019 ◽  
Vol 62 (12) ◽  
pp. 1734-1747
Author(s):  
Binlin Cheng ◽  
Jinjun Liu ◽  
Jiejie Chen ◽  
Shudong Shi ◽  
Xufu Peng ◽  
...  
Keyword(s):  
Malware Detection ◽  
Dependency Graph ◽  
The Internet ◽  
Security Threat ◽  
Detection Approach ◽  
The Family ◽  
Complete Resistance ◽  
Effectiveness And Efficiency ◽  
Behavior Based

Abstract Malware brings a big security threat on the Internet today. With the great increasing malware attacks. Behavior-based detection approaches are one of the major method to detect zero-day malware. Such approaches often use API calls to represent the behavior of malware. Unfortunately, behavior-based approaches suffer from behavior obfuscation attacks. In this paper, we propose a novel malware detection approach that is both effective and efficient. First, we abstract the API call to object operation. And then we generate the object operation dependency graph based on these object operations. Finally, we construct the family dependency graph for a malware family. Our approach use family dependency graph to represent the behavior of malware family. The evaluation results show that our approach can provide a complete resistance to all types of behavior obfuscation attacks, and outperforms existing behavior-based approaches in terms of better effectiveness and efficiency.

Sign in / Sign up

Export Citation Format

Share Document