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Reference Implementation of the PID Controller

The PID controller is the by far most frequently employed type of controller. As you read, billions of digitally implemented PID controllers are running, shaping the dynamic behavior of anything from the fan speed in your laptop to safety-critical components in nuclear power plants. Given the abundance of commissioned PID controllers, it is surprisingly hard to find a single source that provides a

Performance of the European Kidney Function Consortium (EKFC) creatinine-based equation in United States cohorts

Estimating glomerular filtration rate (GFR) is important in daily practice to assess kidney function and adapting the best clinical care of patients with and without chronic kidney disease. The new creatinine-based European Kidney Function Consortium (EKFC) equation is used to estimate GFR. This equation was developed and validated mainly in European individuals and based on a rescaled creatinine,

Real-time Bayesian control of reactive brain computer interfaces

This paper introduces an improved method for real-time brain computer interface control. We demonstrate how Bayesian optimization and feedback can be used to achieve faster statistical convergence by controlling the sequence of stimuli shown in a brain computer interface based on a visual oddball paradigm.

Collision Avoidance for ASVs in Archipelagos—A COLREGs-Aware Optimization-Based Method

With increased autonomy in marine vessels, autonomous surface vessels (ASVs) and conventionally manned vessels need to coexist at sea. Any relocation needs to include collision avoidance according to the traffic rules at sea, COLREGs. Here, a local collision-avoidance planner for an archipelago environment is presented. The optimization-based local planner presented considers a predefined nominal

On Modeling and Detecting Trojans in Instruction Sets

Amid growing concerns about hardware security, comprehensive security testing has become essential for chip certification. This paper proposes a deep-testing method for identifying Trojans of particular concern to middle-to-high-end users, with a focus on illegal instructions. A hidden instruction Trojan can employ a low-probability sequence of normal instructions as a boot sequence, which is foll

Homotopic Optimization for Autonomous Vehicle Maneuvering

Optimization of vehicle maneuvers using dynamic models in constrained spaces is challenging. Homotopic optimization, which has shown success for vehicle maneuvers with kinematic models, is studied in the case where the vehicle model is governed by dynamic equations considering road-tire interactions. This method involves a sequence of optimization problems that start with a large free space. By it

Investigating Characteristics and Opportunities for Rear-Wheel Steering

The potential of additional steering possibilities (like rear-wheel or all-wheel steering) is analyzed for critical situations to investigate possible safety improvements. For this purpose, a dynamic optimization problem is formulated to find the best possible maneuver. The optimization criterion is to maximize the entry speed into a constant radius 90°-curve. The optimization problem is solved fo

Improving EEG-based decoding of the locus of auditory attention through domain adaptation

This paper presents a novel domain adaptation framework to enhance the accuracy of EEG-based auditory attention classification, specifically for classifying the direction (left or right) of attended speech. The framework aims to improve the performances for subjects with initially low classification accuracy, overcoming challenges posed by instrumental and human factors. Limited dataset size, vari

Null-Space Compliance Variation for Safe Human-Robot Collaboration in Redundant Manipulators using Safety Control Barrier Functions

In this paper, Safety Control Barrier Functions (SCBFs) were used to adjust the null-space compliant behavior of a redundant robot to improve safety in Human–Robot Collaboration (HRC) without modifying the robot behavior with respect to its main Cartesian task. A Lyapunov function was included in an energy storage formulation compatible with strict passivity to provide global asymptotic stability

A 1095 pJ/b 219 Mb/s Application-specific Instruction-set Processor for Distributed Massive MIMO in 22FDX

Distributed massive multiple-input multiple-output (D-MIMO) has been identified as a promising technology to meet the service requirements of 6 G wireless networks and beyond. The coordination between a massive number of distributed antennas introduces stiff challenges and requires a substantial amount of computing resources that must be put together with careful algorithm-architecture codesign. T

A Scalable Process for the Production of Calcium Formate from Lime Mud

The utilization of industrial side streams for generating value has always been of interest, but in today's society, with a high focus on the circular economy, it is becoming increasingly important. Lime mud (whose major component is calcium carbonate, CaCO3) is a low-value by-product of the pulp and paper industry that is generated in considerable amounts during the causticizing process. Designin

Model-Based Predictive Impedance Variation for Obstacle Avoidance in Safe Human–Robot Collaboration

Human–robot collaboration (HRC) in manufacturing environments requires that physical safety can be guaranteed. Control methods that implicitly regulate the interaction forces between a controlled robot and its environment, such as impedance control, are often used for safety in HRC. However, these methods could be complemented by restricting the robot operational space for additional safety guaran

Iterative Reference Learning for Cartesian Impedance Control of Robot Manipulators

In this paper, an iterative learning strategy was developed to improve trajectory tracking for an impedance-controlled robot manipulator. In this learning strategy, an update law was proposed to modify the Cartesian reference of an impedance controller. Also, the conditions that ensure its convergence considering the dynamics of the robot were derived. Finally, an experimental evaluation was perfo

Exploring ML testing in practice - Lessons learned from an interactive rapid review with Axis Communications

There is a growing interest in industry and academia in machine learning (ML) testing. We believe that industry and academia need to learn together to produce rigorous and relevant knowledge. In this study, we initiate a collaboration between stakeholders from one case company, one research institute, and one university. To establish a common view of the problem domain, we applied an interactive r

Estimation of the glomerular filtration rate in children and young adults by means of the CKD-EPI equation with age-adjusted creatinine values

The CKD-EPI creatinine-based estimation equation for glomerular filtration rate (GFR) cannot be used in children, overestimates GFR in young adults, and its combination with the KDIGO recommended pediatric CKiD (Schwartz bedside) equation causes implausible increases in estimated GFR when switching from pediatric to adult care. By establishing sex-specific creatinine growth curves for children and

Faint objects in motion : the new frontier of high precision astrometry

Sky survey telescopes and powerful targeted telescopes play complementary roles in astronomy. In order to investigate the nature and characteristics of the motions of very faint objects, a flexibly-pointed instrument capable of high astrometric accuracy is an ideal complement to current astrometric surveys and a unique tool for precision astrophysics. Such a space-based mission will push the front

Hovering flight in hummingbird hawkmoths : Kinematics, wake dynamics and aerodynamic power

Hovering insects are divided into two categories: ‘normal’ hoverers that move the wing symmetrically in a horizontal stroke plane, and those with an inclined stroke plane. Normal hoverers have been suggested to support their weight during both downstroke and upstroke, shedding vortex rings each half-stroke. Insects with an inclined stroke plane should, according to theory, produce flight forces on

M2D2 : Maximum-Mean-Discrepancy Decoder for Temporal Localization of Epileptic Brain Activities

Recent years have seen growing interest in leveraging deep learning models for monitoring epilepsy patients based on electroencephalographic (EEG) signals. However, these approaches often exhibit poor generalization when applied outside of the setting in which training data was collected. Furthermore, manual labeling of EEG signals is a time-consuming process requiring expert analysis,