Science topics: Automatism
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Automatism - Science topic

Automatic, mechanical, and apparently undirected behavior which is outside of conscious control.
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Publications related to Automatism (10,000)
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Chatter is an unstable and self-excited vibration that adversely affects part quality and tool life in various machining processes. To achieve high-performance machining, chatter identification has attracted considerable interest from many researchers in recent decades. Nevertheless, most existing chatter detection approaches fail to consider the p...
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In the field of agricultural information, the identification and prediction of rice leaf disease have always been the focus of research, and deep learning (DL) technology is currently a hot research topic in the field of pattern recognition. The research and development of high-efficiency, high-quality and low-cost automatic identification methods...
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The tumor in the brain is a serious disease that causes death in humans. Various imaging modalities are utilized for identifying tumors, but the huge data produced by magnetic resonance imaging (MRI) can affect the manual classification of brain tumors. Thus, an automatic technique to categorize tumors is highly desirable. A novel optimization-driv...
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Ptychography is a lens-free imaging method which can outstrip the resolution limitations of optical apparatuses, even so the algorithm automatically totes background noise during the imaging process. In order to rehabilitate a more exquisite image, an adaptive iterative guided filtering method is designed. The guided filter is incorporated into the...
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The hyperparameters in support vector regression (SVR) determine the effectiveness of the support vectors with fitting and predictions. However, the choice of these hyperparameters has always been challenging in both theory and practice. The ν-support vector regression eliminates the need to specify an value elegantly, but at the cost of specifying...
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Localized deformation bands are often observed in materials exhibiting the Portevin–Le Chatelier (PLC) effect. However, efficient quantitative analysis of PLC bands remains challenging. A novel method is thus proposed in this work, where a multi-strain-jump function is introduced to capture the experimentally obtained staircase-like strain profile...
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The experiments on Ni-Mn-Ga single crystal shape memory alloy under a heating-cooling cycle demonstrate that the automatically generated twin laminate structure of the compatible austenite-martensite interface in the forward martensitic phase transition is significantly different from that in the reverse phase transition, even though the temperatur...
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Optical-based near-real time deforestation alert systems in the Brazilian Amazon are ineffective in the rainy season. This study identify clear-cut deforested areas through Neural Network (NN) algorithm based on C-band, VV- and VH-polarized, Sentinel-1 images. Statistical parameters of backscatter coefficients (mean, standard deviation, and the dif...
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A locked chain is an immovable sub-chain within a kinematic chain. The detection of immovable sub-chains is a critical step in the structural synthesis of planetary gear trains (PGTs). This paper presents a simplified method for the identification of locked chains in PGTs based on the vertex-edge mobility criterion. The vertex-edge mobility criteri...
Preprint
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This article presents a multi-sensor calibration and fusion work for a dense reconstruction and colorization system. Unlike previous research, it explicitly addresses the edge effect in LiDAR measurements in both calibration and sensor fusion. The proposed calibration method can accomplish LiDAR-motor and LiDAR-camera calibration at a one-time expe...
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Heart sound signals, phonocardiography (PCG) signals, allow for the automatic diagnosis of potential cardiovascular pathology. Such classification task can be tackled using the bidirectional long short-term memory (biLSTM)network, trained on features extracted from labeled PCG signals. Regarding the non-stationarity of PCG signals, it is recommende...
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Autonomous surface vehicle (ASV) is a vehicle in the form of an unmanned on-water surface vessel that can move automatically. As such, an automatic control system is essentially required. The bow thruster system functions as a propulsion control device in its operations. In this research, the water momentum and propeller velocity were estimated bas...
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Key message The lack of efficient phenotyping capacities has been recognized as a bottleneck in forestry phenotyping and breeding. Modern phenotyping technologies use systems equipped with various imaging sensors to automatically collect high volume phenotypic data that can be used to assess trees' various attributes. Context Efficient phenotyping...
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Objective We aim to develop and validate a three-dimensional convolutional neural network (3D-CNN) model for automatic liver segment segmentation on MRI images. Methods This retrospective study evaluated an automated method using a deep neural network that was trained, validated, and tested with 367, 157, and 158 portal venous phase MR images, res...
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Image classification refers to the classification of the input image according to some algorithms. The general steps of image classification include image preprocessing, image feature extraction and image classification judgment. Convolutional neural network (CNN) imitates the visual perception mechanism of biology, solves the complicated engineeri...
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At present, dental implant surgery mainly relies on the clinical experience of the doctor and the assistance of preoperative medical imaging. However, there are some problems in dental implant surgery, such as narrow space, sight obstruction, inaccurate positioning, and high requirements of doctors' proficiency. Therefore, a dental implant robot sy...
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The Structural components in metallic structures subjected to mechanical and thermal loading in severe environmental conditions experience a different range of Temperatures. So, the Steel Structures are predominant thermal loading apart from automatic loading at the interfaces of the various metallic components under severe environmental conditions...
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Data provides a foundation for machine learning, which has accelerated data-driven materials design. The scientific literature contains a large amount of high-quality, reliable data, and automatically extracting data from the literature continues to be a challenge. We propose a natural language processing pipeline to capture both chemical compositi...
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Background To establish the digital diagnostic templates by cluster analysis based on a set of cephalometric films and evaluate the outcome of the different treatment methods in the patients affiliated to the same cephalometric morphology template (CMT). These templates could be used for the automatic diagnosis of dentofacial deformities and predic...
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Decision makers (DMs) are often hesitant about the evaluations for subjective or objective reasons, and established preference relations always have various limitations on the way that DMs express themselves. Aiming at investigating the consensus reaching process where DMs needs more decision freedom, this study proposes a novel decision support mo...
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Background Mechanical power is a promising new metric to assess energy transfer from a mechanical ventilator to a patient, which combines the contributions of multiple parameters into a single comprehensive value. However, at present, most ventilators are not capable of calculating mechanical power automatically, so there is a need for a simple equ...
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The purpose of this paper is to present a high-performance pH-ISFET readout circuit, which carries out a temperature insensitivity, linearity and temporal drift compensation, by using a new architecture that automates the control of an isothermal point. Unlike many existing readout circuits in the literature, this circuit can be optimized for sever...
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Leaf chlorophyll content (LCC) is an important indicator of foliar nitrogen status and photosynthetic capacity. Compared to physical models, the generality of empirical models based on vegetation indices is often questioned when they are used to estimate LCC due to the influence from canopy structure, such as leaf area index (LAI). A recent study d...
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This paper analyzes the impact of the COVID-19 crisis on household income in Austria, using detailed administrative labor market data, in combination with micro-simulation techniques that enable specific labor market transitions to be modeled. We find that discretionary fiscal policy measures in Austria are key to counteracting the inequality- and...
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Performance of Footing-Soil Interaction (FSI) system with thin layer interface is still an active field of research because the behavior of FSI mainly depends on behavior of interface and its influencing thickness. Many researchers performed FSI study with commercially available software with available zero thickness interface element. It has been...
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Music is the language of emotions. In recent years, music emotion recognition has attracted widespread attention in the academic and industrial community since it can be widely used in fields like recommendation systems, automatic music composing, psychotherapy, music visualization, and so on. Especially with the rapid development of artificial int...
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Frequency control of an interconnected power system in the presence of wind integration is complex since wind speed/power variations also affect system frequency in addition to load perturbations. Therefore, improving existing control schemes is necessary to maintain a stable frequency in such complex power system scenarios. In this paper, a new 2-...
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People miss a high proportion of targets that only appear rarely. This low prevalence (LP) effect has implications for applied search tasks such as the clinical reading of mammograms. Computer aided detection (CAD) has been used to help radiologists search mammograms by highlighting areas likely to contain a cancer. Previous research has found a be...
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In additive manufacturing of metal parts, the ability to accurately predict the extremely variable temperature field in detail, and relate it quantitatively to structure and properties, is a key step in predicting part performance and optimizing process design. In this work, a finite element simulation of the directed energy deposition (DED) proces...
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Corrosion costs an estimated 3–4% of GDP for most nations each year, leading to significant loss of assets. Research regarding automatic corrosion detection is ongoing, with recent progress leveraging advances in deep learning. Studies are hindered however, by the lack of a publicly available dataset. Thus, corrosion detection models use locally pr...
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In the field of model order reduction for frequency response problems, the minimal rational interpolation (MRI) method has been shown to be quite effective. However, in some cases, numerical instabilities may arise when applying MRI to build a surrogate model over a large frequency range, spanning several orders of magnitude. We propose a strategy...
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Online social networking platforms allow people to freely express their ideas, opinions, and emotions negatively or positively. Previous studies have examined sentiments on these platforms to study their behavior in different contexts and purposes. The mechanism of collecting public opinion information has attracted researchers to automatically cla...
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Forming of various customized bending parts, small batches, as well as numerous types of materials is a new challenges for Industry 4.0, the current control strategies can not meet the precision and flexibility requirement, expected control strategy of bending processes need to not only resist unknown interferences of process condition and models,...
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Background The diagnostic yield of whole-exome sequencing (WES) varies from 30%–50% among patients with mild to severe neurodevelopmental delay (NDD)/intellectual disability (ID). Routine retrospective reanalysis of undiagnosed patients has increased the total diagnostic yield by 10–15%. Here, we performed proband-only WES of 1065 patients with NDD...
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Background Graph theoretical network analysis with structural magnetic resonance imaging (MRI) of multiple sclerosis (MS) patients can be used to assess subtle changes in brain networks. However, the presence of multiple focal brain lesions might impair the accuracy of automatic tissue segmentation methods, and hamper the performance of graph theor...
Conference Paper
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Online testing of web APIs—testing APIs in production—is gaining traction in industry. Platforms such as RapidAPI and Sauce Labs provide online testing and monitoring services of web APIs 24/7, typically by re-executing manually designed test cases on the target APIs on a regular basis. In parallel, research on the automated generation of test case...
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Program synthesis is the task of automatically generating programs from user intent, which is one of the central problems in automated software engineering. Recently many researchers use a neural network to learn the distribution over programs based on user intent (such as API and type name), known as neural program synthesis (NPS). The generated p...
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App responsiveness is the most intuitive interpretation of App performance from the users’ perspective. Traditional performance profilers only focus on one type of program activity (e.g., CPU profiling). In contrast, the cause of slow responsiveness can be diverse or even due to the joint effect of multiple kinds. Also, various test configurations,...
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It is undeniable that software development is a team-based activity. The quality of the delivered product highly depends on the team configuration. However, selecting an appropriate team to complete a software task is non-trivial, as it needs to consider team compatibility in multiple aspects. While extensive literature introduced multiple team rec...
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Neural networks are getting increasingly popular thanks to their exceptional performance in solving many real-world problems. At the same time, they are shown to be vulnerable to attacks, difficult to debug and subject to fairness issues. To improve people’s trust in the technology, it is often necessary to provide some human-understandable explana...
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Identifying security concerns is a security activity that can be integrated into the requirements development phase. However, it has been shown that manually identifying concerns is a time-consuming and challenging task. The software engineering community has utilized natural language processing and query systems to automatically find part of the r...
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The process by which infants move from liquid feeding to caregiver-assisted spoon feeding of semi-solid food is quite a dramatic transition. In previous studies, we observed that in the weeks after the introduction to solid food, mother-infant dyads showed increased co-regulation and synchronization of their respective feeding behaviors (e.g. offer...
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Techniques have been studied to extend the measurement capability of stereo deflectometry from continuous specular surfaces only to complex structured specular surfaces. Segmentation is a key process in these techniques, which separates a measured structured surface into several continues segments with gradient and coordinate data to achieve high f...
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WARP is an energy-efficient lightweight block cipher that is currently the smallest 128-bit block cipher in terms of hardware. It was proposed by Banik et al. in SAC 2020 as a lightweight replacement for AES-128 without changing the mode of operation. This paper proposes key-recovery attacks on WARP based on differential cryptanalysis in single and...
Conference Paper
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This paper deals with the control of a laser spot in the context of minimally invasive surgery of the middle ear, e.g., cholesteatoma removal. More precisely, our work is concerned with the exhaustive burring of residual infected cells after primary mechanical resection of the pathological tissues since the latter cannot guarantee the treatment of...
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The rapid development of information and communication technologies has facilitated machining condition monitoring toward a data-driven paradigm, of which industrial Internet-of-Things (IIoT) serves as the fundamental basis to acquire data from physical equipment with sensing technologies as well as to learn the relationship between the system cond...
Conference Paper
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Recently, DGA has been becoming a popular technique used by many malwares in general and botnets in particular. DGA allows hacking groups to automatically generate and register domain names for C&C servers of their botnets in order to avoid being blacklisted and disabled if using static domain names and IP addresses. Many types of sophisticated DGA...
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Traffic identification has become a challenging task in recent years. Recently, deep learning methods have been extensively studied for network traffic classification recently. Unfortunately, these models require a large amount of training data. Another challenge with most traffic classification methods is that the features must be extracted by an...
Conference Paper
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Workflow languages play a key role in the discipline of Business Process Management (BPM): they allow business processes to be modelled in order to simplify their automatic management by means of BPM systems. Numerous workflow languages addressing various issues (expressiveness, formal analysis, etc.) have been proposed. In the last decade, some wo...
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An image caption generator produces syntactically and semantically correct sentences to narrate the scene of a natural image. A neural image caption (NIC) generator is a popular deep learning model for automatically generating image captions in plain English. The NIC generator combines a convolutional neural network (CNN) encoder and a long short-t...
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The Measures of Academic Progress (MAP) test is a unique benchmark exam with the differentiation features and the various individualized reports generated from test data. The aim of this study was to determine how teachers' opinions of the MAP exam influence their attitude towards the MAP policy. To achieve this aim, a mixed-methods approach was ut...
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Stopping violent incidents in real life is more dangerous for ordinary people. It may harm people's lives. Calling the police is the best choice to stop the violence. We should have an automatic system to recognize violence and warn the police on time. This paper proposes a method to classify violent incidents from video. However, classification of...
Article
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Automatic monitoring tools can be useful for assessing the health and welfare status of animals. Specifically, a computer-vision-based tracking tool could be helpful to remotely and automatically monitoring the behaviour of individual animals. However, animals housed in partly covered pens present a particular challenge for animal tracking due to t...
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The process of automatic building detection has become a concern for city governments in many developing nations as it is the foundation for urban planning and other purposes, particularly in high-density cities. Deep learning has attracted significant interest in recent years as the most appealing technique for problem resolution in the field of r...