Error Detection System Research Articles

Обнаружение неисправностей в комбинационных схемах на основе самодвойственного дополнения до равновесных кодов

A new method of combinational circuits concurrent checking is considered based on Boolean complement of the working functions of the diagnosis object to the constant-weight code words with parallel checkout of the bits functions belonging to the self-dual functions class of the Boolean logic. The described approach to the organization of concurrent error-detection (CED) systems allows to increase the detection ability in comparison with the traditional checkout by constant-weight code. In this case, the undetectable error can be a such error, which will lead to the preservation of the code word weight generated at the outputs of the Boolean complement block, if the distortions of all the functions bits on the opposite sets is coincide. This condition is more stringent than the checkout of the vector belonging a pre-selected code, it means that it gives a greater probability of detecting distortion arising from errors. The described method allows checkout of combinational circuit based on constant-weight codes with the same number of single and zero bits. In this case, the priority is in the widely used «2-out-of-4» code, which has a simple checker structure. A detailed description of the new CED system structure is given, and algorithms for the extension of definition of the values of the checkout functions that provide testability of technical diagnostic tools are given.

Feasibility of a dual detector system to perform transit dosimetry and MV imaging in-vivo

In this work, a dual detector system for simultaneous in-vivo dosimetry and MV imaging was investigated. The ability to measure real-time water equivalent dose post transit for a heterogeneous phantom was demonstrated, illustrating its advantage over non-water equivalent EPID dosimetry. Identification of incorrect MU delivery as well as patient misalignment can be identified in the dose profiles and confirmed through co-registration with EPID images. The dual detector comprising of a silicon array detector “Magic Plate” (MP) and an EPID was positioned beneath the patient couch at a source to detector distance of 150 cm. Two pseudo lung phantoms were utilised in this study; identical, except for the inclusion of a water equivalent hidden target mimicking a tumour. The dosimetric accuracy of the MP was evaluated with EBT3 film and TPS calculations. The presence and position of the hidden target was detected and accurately co-registered between the dose profiles measured with MP and the EPID image. The system measured a difference in post transit doses through the two phantoms of (5.0 ±1.6) cGy due to the presence of the target, in agreement with the TPS calculation of 5.16 cGy. The capability of the system for error detection was confirmed when a deliberate 7 mm lateral shift of the phantom was observed in both the dose profiles measured with MP and the EPID images. The MP as a dosimetric real time detector is lucent in MV photon fields and does not obstruct the EPID field of view.

Logic Error Detection System based on Structure Pattern and Error Degree

Logic Error Detection System based on Structure Pattern and Error Degree

Indonesian Words Error Detection System using Nazief Adriani Stemmer Algorithm

Stemming in each language has a different process and is determined according to the structure of the language. Stemming is mostly used as a complete step in the processing of words and phrases. There are many stemming algorithms available, and some used as a process for word processing. One function of stemming is to detect word errors in Indonesian. In this study, researchers created the Indonesian words error detection system using Nazief and Adriani algorithm. In the trials conducted, the system will accept text input obtained from the user. Then the system will preprocess the text. In this study, there are three stages of preprocessing, namely tokenization, case folding, and filtering. After the stages in preprocessing are finished, the system will call each word for the process of stemming. The results of the stemming will be compared with the base words available in the database. If it does not match, then the word is highlighted and is considered an error word. The first finding is the Nazief Adriani's algorithm can be able to detect words error until 100%. The second finding is the Nazief Adriani's algorithm also detect non-words error, the accuracy of detecting is 97.464%.

Особенности организации систем функционального контроля комбинационных схем на основе полиномиальных кодов

Objective: To study the specificities of polynomial codes application during the organization of concurrent error detection systems for combinational logic circuits of automation and computer engineering. Methods: The methods of information theory and coding, the theory of discrete devices and diagnostic engineering of discrete systems were applied. Results: The possibilities of using polynomial codes in the process of combinational logic circuits control organization were analyzed. Some essential properties, inherent in generator polynomials, which make it possible to synthesize self-checking circuits of concurrent error detection systems, were pointed out. Particularly, one of such essential properties is the presence of a constant term in a generator polynomial (otherwise, all the required test patterns are not generated for a complete check of a coding device). An example of concurrent error detection sys- tem implementation for a combinational circuit was given. Some experimental data on error detection in LGSynth’89 combinational benchmarks were described. Practical importance: The use of polynomial codes for combinational circuit control makes it possible to synthesize self-checking discrete devices of automation and computer engineering.

An error-aware gaze-based keyboard by means of a hybrid BCI system

Gaze-based keyboards offer a flexible way for human-computer interaction in both disabled and able-bodied people. Besides their convenience, they still lead to error-prone human-computer interaction. Eye tracking devices may misinterpret user’s gaze resulting in typesetting errors, especially when operated in fast mode. As a potential remedy, we present a novel error detection system that aggregates the decision from two distinct subsystems, each one dealing with disparate data streams. The first subsystem operates on gaze-related measurements and exploits the eye-transition pattern to flag a typo. The second, is a brain-computer interface that utilizes a neural response, known as Error-Related Potentials (ErrPs), which is inherently generated whenever the subject observes an erroneous action. Based on the experimental data gathered from 10 participants under a spontaneous typesetting scenario, we first demonstrate that ErrP-based Brain Computer Interfaces can be indeed useful in the context of gaze-based typesetting, despite the putative contamination of EEG activity from the eye-movement artefact. Then, we show that the performance of this subsystem can be further improved by considering also the error detection from the gaze-related subsystem. Finally, the proposed bimodal error detection system is shown to significantly reduce the typesetting time in a gaze-based keyboard.

A Framework for Grammatical Error Detection and Correction System for Punjabi Language Using Stochastic Approach

A Framework for Grammatical Error Detection and Correction System for Punjabi Language Using Stochastic Approach

User action and facial expression recognition for error detection system in an ambient assisted environment

Emotion recognition through facial expressions represents a relevant way to understand and even predict the human behavior. Thus, it has been used in various fields such as human-robot interaction and ambient assistance. Nevertheless, it remains a challenging task since expressed emotions might be affected by different parameters such as ethnic origins, age and so on. In this paper, we introduce an efficient facial expression recognition approach based on a Convolutional Neural Network architecture. Carried experimentation on five benchmark facial expression datasets confirms the efficiency of the proposed approach with recognition rates higher than 95%. In the context of ambient assistance, we introduced an error detection module using a user action recognition from Radio Frequency IDentification tags placed on various objects of daily living. The experiments performed in a smart environment show a consistent improvement of the error detection module when including facial expression recognition. Indeed, the false positive detection rate is significantly reduced by over 20%.

Экспериментальные исследования кодов с суммированием единичных и одного взвешенного разрядов в системах функционального контроля

Экспериментальные исследования кодов с суммированием единичных и одного взвешенного разрядов в системах функционального контроля

Focusing error detection based on astigmatic method with a double cylindrical lens group

Autofocusing and autotracking are widely used in maskless laser lithography, optical imaging, and recording and readout of optical information storage. With the development of optoelectronic techniques, the accuracy of autofocusing and autotracking thus needs to be improved to the nanoscale, and the autotracking range also needs to be extended to tens of micrometers. In this work, an astigmatic method with two cylindrical lenses is proposed, where the focusing error signal is extracted to detect the focusing error. A theoretical analysis and simulation are carried out, accordingly. A focusing error detection system is established to demonstrate the theoretical analysis. The experimental results indicate that the focusing error signal curves present good “S” characteristics. The linear tracking range is up to 18 μm, and the tracking accuracy is approximately 50 nm. The theoretical and experimental results indicate that the astigmatic method with two cylindrical lenses is a good method for autofocusing and autotracking with both high accuracy and large dynamic range. This work is useful in the fields of high-resolution maskless laser lithography and optical imaging.

Sum Codes with Efficient Detection of Twofold Errors for Organization of Concurrent Error-Detection Systems of Logical Devices

Developed were new sum codes detecting efficiently twofold errors in the data vectors. A method of constructing concurrent error-detection systems of the logical combination devices with detection of all single malfunctions based on decomposing the outputs into individual groups and checking them with the use of new sum codes was proposed.

Commissioning and Evaluation of an Electronic Portal Imaging Device-Based In-Vivo Dosimetry Software.

This study reports on our experience with the in-vivo dose verification software, EPIgray® (DOSIsoft, Cachan, France). After the initial commissioning process, clinical experiments on phantom treatments were evaluated to assess the level of accuracy of the electronic portal imaging device (EPID) based in-vivo dose verification.EPIgray was commissioned based on the company’s instructions. This involved ion chamber measurements and portal imaging of solid water blocks of various thicknesses between 5 and 35 cm. Field sizes varied between 2 x 2 cm2 and 20 x 20 cm2. The determined conversion factors were adjusted through an additional iterative process using treatment planning system calculations. Subsequently, evaluation was performed using treatment plans of single and opposed beams, as well as intensity modulated radiotherapy (IMRT) plans, based on recommendations from the task group report TG-119 to test for dose reconstruction accuracy. All tests were performed using blocks of solid water slabs as a phantom.For single square fields, the dose at isocenter was reconstructed within 3% accuracy in EPIgray compared to the treatment planning system dose. Similarly, the relative deviation of the total dose was accurately reconstructed within 3% for all IMRT plans with points placed inside a high-dose region near the isocenter. Predictions became less accurate than < 5% when the evaluation point was outside the treatment target. Dose at points 5 cm or more away from the isocenter or within an avoidance structure was reconstructed less reliably.EPIgray formalism accuracy is adequate for an efficient error detection system with verifications performed in high-dose volumes. It provides immediate intra-fractional feedback on the delivery of treatment plans without affecting the treatment beam. Besides the EPID, no additional hardware is required. The software evaluates local point dose measurements to verify treatment plan delivery and patient positioning within 5% accuracy, depending on the placement of evaluation points.

Analytical Review of Error Control in Data Link Layer

Error control portrays how the system handles and identifies blunders particularly in the information interface layer. In this paper, we exhibit a review of blunder control with respect to mistake discovery and mistake redress. Error control occurs in data link layer. We chiefly examine the kind of error detection systems that is utilized to recognize the mistakes and how the mistakes will be redressed so the collector can remove the genuine information. For most applications, a framework must ensure that the information got are indistinguishable to the information transmitted. Transmission media are prone to error. In a network, the capacity of nodes is different and the rate at which the sender is sending data might not be the same rate at which the receiver accepts it. In this paper, we discuss on designing issues of data link layer. The primary focus is on various error detecting and controlling mechanisms.

Two-Modulus Codes with Summation of On-Data Bits for Technical Diagnostics of Discrete Systems

A fundamentally new approach to building a code with summation of on-data bits based on the selection and separate check of subsets of bits of the data vector is presented. The properties of the proposed code are analyzed in comparison with the classic and modified Berger codes. The advantages and disadvantages of new codes with summation of on-data bits are noted. The basic properties of the proposed codes with summation that should be taken into account in solving problems of technical diagnostics are established. The results of experimental applications of the developed codes to the organization of concurrent error detection systems of combinational benchmarks from LGSynth`89 are given.

System of error detection in the manufacture of garments using artificial vision

A computer vision system is implemented to detect errors in the cutting stage within the manufacturing process of garments in the textile industry. It provides solution to errors within the process that cannot be easily detected by any employee, in addition to significantly increase the speed of quality review. In the textile industry as in many others, quality control is required in manufactured products and this has been carried out manually by means of visual inspection by employees over the years. For this reason, the objective of this project is to design a quality control system using computer vision to identify errors in the cutting stage within the garment manufacturing process to increase the productivity of textile processes by reducing costs.

Синтез систем функционального контроля многовыходных комбинационных схем на основе метода логического дополнения

Синтез систем функционального контроля многовыходных комбинационных схем на основе метода логического дополнения

Classification of Error Related Brain Activity in an Auditory Identification Task with Conditions of Varying Complexity

The detection of an error is the cognitive evaluation of an action outcome that is considered undesired or mismatches an expected response. Brain activity during monitoring of correct and incorrect responses elicits Event Related Potentials (ERPs) revealing complex cerebral responses to deviant sensory stimuli. Development of accurate error detection systems is of great importance both concerning practical applications and in investigating the complex neural mechanisms of decision making. In this study, data are used from an audio identification experiment that was implemented with two levels of complexity in order to investigate neurophysiological error processing mechanisms in actors and observers. To examine and analyse the variations of the processing of erroneous sensory information for each level of complexity we employ Support Vector Machines (SVM) classifiers with various learning methods and kernels using characteristic ERP time-windowed features. For dimensionality reduction and to remove redundant features we implement a feature selection framework based on Sequential Forward Selection (SFS). The proposed method provided high accuracy in identifying correct and incorrect responses both for actors and for observers with mean accuracy of 93% and 91% respectively. Additionally, computational time was reduced and the effects of the nesting problem usually occurring in SFS of large feature sets were alleviated.

Коды с суммированием с последовательностью весовых коэффициентов, образующей натуральный ряд чисел, в системах функционального контроля

Коды с суммированием с последовательностью весовых коэффициентов, образующей натуральный ряд чисел, в системах функционального контроля

Binocular-vision-based error detection system and identification method for PIGEs of rotary axis in five-axis machine tool

Errors of the rotary axes are the main sources of geometric errors in a five-axis machine tool. Thus, accurate periodic checks and calibrations of the rotary axes are important for improving the machining precision. In this paper, to achieve error detection with three-dimensional (3D) measurement capability and to simplify the complex error identification formulations of position-independent geometric errors (PIGEs) in the rotary axis (C-axis), both a binocular-vision-based error detection system and an identification algorithm are proposed. First, the 3D error detection system is investigated, in which a novel self-luminous cooperative target is designed to characterize the movement information of a rotary table; thus, high-precision installation and high-signal-to-noise image acquisition are realized. In addition, to further guarantee the 3D vision measurement accuracy, a center location method based on reconciled conjugate constraints is adopted to improve the position accuracy of the rotary table. Then, in the error identification process, an error identification model that is independent of the machine structure is established to separate the error parameters, which simplifies the complex mathematical formulations. By best-fitting a set of 3D measurement positions to the identification algorithms, each error parameter of the PIGEs can be separately identified by simply mounting the cooperative target on the rotary table in one setup. Experiments for the measurement and identification of PIGEs in C-axis of a five-axis machine tool were performed in a laboratory; in comparison with the identification results obtained by double-ball bar (DBB) test, the experimental results verified the vision-based error identification accuracy and feasibility.

Error Detection and Reporting in the Intensive Care Unit: Progress, Barriers, and Future Direction

In this article, we aim to assess the current progress the healthcare system has made creating a robust model of error detection and event reporting. In addition, we analyze the impediments to quality improvement on a unit-specific basis such as the impact of reporting on ICU workflow. There are major barriers to a fully realized inclusive, multimodal error detection system, which has led to uncertainty in the true rate of adverse events and near misses. Patient safety is the responsibility of every healthcare provider. Healthcare providers must work together to implement a resilient system capable of identifying, collecting, and responding to the preventable harm that frequently occurs in the context of patient care. There has been appreciable progress made thus far, with initiatives such as the Global Trigger Tool, TeamSTEPPS, and CUSP, but more work needs to be done if we are to achieve the desired goal of zero preventable patient harm.