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Fully Declarative Specification of Static Code Checkers

Static code checkers are tools that help software engineers by automatically finding defects without executing the programs. These tools contain a set of detectors that rely on static program analyses to find common programming defects or to enforce coding guidelines.While existing code checker frameworks package a rich collection of detectors, aimed at common bug defects, the effort to adapt thes

Unified framework for entropy search and expected improvement in Bayesian optimization

Bayesian optimization is a widely used method for optimizing expensive black-box functions, with Expected Improvement being one of the most commonly used acquisition functions. In contrast, information-theoretic acquisition functions aim to reduce uncertainty about the function's optimum and are often considered fundamentally distinct from EI. In this work, we challenge this prevailing perspective

Understanding high-dimensional Bayesian optimization

Recent work reported that simple Bayesian optimization methods perform well for high-dimensional real-world tasks, seemingly contradicting prior work and tribal knowledge. This paper investigates the 'why'. We identify fundamental challenges that arise in high-dimensional Bayesian optimization and explain why recent methods succeed. Our analysis shows that vanishing gradients caused by Gaussian pr

Threshold Saturation for Quantitative Group Testing with Low-Density Parity-Check Codes

We recently proposed a quantitative group testing (GT) scheme with low-complexity peeling decoding based on low-density parity-check (LDPC) codes. Based on finite length simulations and a density evolution analysis we were able to demonstrate that simple (dv,dc)-regular LDPC codes can be more efficient for GT than existing generalized LDPC (GLDPC) code constructions based on BCH component codes. E

Radio Channel Characterization for Distributed MIMO

Future wireless systems are envisioned to be able to deliver ultra-reliable and low-latency communication.The third generation partner project (3GPP) has identified three different usage scenarios such as enhanced mobile broadband, massive machine-type communication, and ultra-reliable low latency communication.In each of those scenarios, several services and applications can be implemented, e.g.

Towards understanding inter-organizational data sharing practices and technical tools needs

Background: Data quickly emerges as a core driver of businesses across the worlddue to rapidly expanding use in different areas, such as Machine Learning. In orderfor the data-related organizational operations to be efficient, the topic of data shar-ing has to be explored. This thesis focuses on understanding inter-organizationaldata sharing by exploring practices and challenges that are present w

Graph-Based Multi-Bounce Modeling and Channel Parameter Estimation for Indoor Sensing

Indoor sensing is challenging because of the multi-bounce effect, spherical wavefront, and spatial nonstationarity (SNS) of the near-field effect. This paper addresses radio-based environment sensing considering these issues. Specifically, graph theory (GT) is used to model the multi-bounce propagation of the near field. In this manner, indoor reflectors/scatterers are modeled as vertices in a pro

LDPC Codes for Quantitative Group Testing With a Non-Binary Alphabet

We propose and analyze a novel scheme based on LDPC codes for quantitative group testing. The key underlying idea is to augment the bipartite graph by introducing hidden non-binary variables to strengthen the message-passing decoder. This is achieved by grouping items into bundles of size q within the test matrix, while keeping the testing procedure unaffected. The decoder, inspired by some works

Clog: A Declarative Language for C Static Code Checkers (Artifact)

Clog is a declarative language for describing static code checkers for C. Clog is a dialect of Datalog and adds syntactic pattern matching over the C language. We have built Clog using the MetaDL framework and the Clang C compiler frontend. The MetaDL framework supports Datalog evaluation and syntactic patterns, while the Clang frontend provides AST facts and an AST matching mechanism.We provide t

Coherent Bandwidth and Distance in an Ultra-Large-Scale Antenna Array at 15 GHz

This study presents a measurement campaign with an ultra-large-scale antenna array in both Line-of-Sight (LoS) and Non-Line-of-Sight (NLoS) outdoor scenarios. Measurements were conducted at a center frequency of 15 GHz with a bandwidth of 4 GHz. A virtual 40×40 planar antenna array, formed by moving a vertically-polarized bi-conical omni-directional antenna (ODA) along regularly spaced grids, was

Optimizing the Temperature Sensitivity of the Isoprene Emission Model MEGAN in Different Ecosystems Using a Metropolis-Hastings Markov Chain Monte Carlo Method

Isoprene is a reactive hydrocarbon emitted to the atmosphere in large quantities by terrestrial vegetation. Annual total isoprene emissions exceed 300 Tg a−1, but emission rates vary widely among plant species and are sensitive to meteorological and environmental conditions including temperature, sunlight, and soil moisture. Due to its high reactivity, isoprene has a large impact on air quality an

Scaling massive MIMO with imperfect transceivers

The number of users and the information transmitted over wireless networks have been growing constantly during the last decades. Nowadays, the pace of this growth is extremely sharp because of the new applications which heavily rely on wireless networks to meet users' demands. Wireless networks infrastructures are constantly developing to meet these demands. Massive multiple-input multiple-output

Learning Skill-based Industrial Robot Tasks with User Priors

Robot skills systems are meant to reduce robot setup time for new manufacturing tasks. Yet, for dexterous, contact-rich tasks, it is often difficult to find the right skill parameters. One strategy is to learn these parameters by allowing the robot system to learn directly on the task. For a learning problem, a robot operator can typically specify the type and range of values of the parameters. Ne

Generalizing Behavior Trees and Motion-Generator (BTMG) Policy Representation for Robotic Tasks Over Scenario Parameters

We propose a generalisation of a behaviour tree and motiongenerator based robot arm policy representation for learning and solving tasks such as contact-rich tasks like peg insertion or pushing an object. We use planning to generate skill sequences needed to execute these tasks and rely on reinforcement learning to obtain parameters of the policy. We assume gaussian processes as a suitable method

Pose estimation from RGB images of highly symmetric objects using a novel multi-pose loss and differential rendering

We propose a novel multi-pose loss function to train a neural network for 6D pose estimation, using synthetic data and evaluating it on real images. Our loss is inspired by the VSD (Visible Surface Discrepancy) metric and relies on a differentiable renderer and CAD models. This novel multi-pose approach produces multiple weighted pose estimates to avoid getting stuck in local minima. Our method re

Deployment Strategies for Large Intelligent Surfaces

Beyond 5G communication systems must be able to meet the requirements imposed by the ever-increasing demand in capacity, while guaranteeing robustness, reliability, low latency, security, as well as spectral and power efficiencies. Large intelligent surfaces (LIS) as an evolution of massive MIMO have drawn considerable attention among researchers, being already considered as one of the key technol

Industrial Robotics

Much of the technology that makes robots reliable, human friendly, and industrialroboticsadaptable for numerous applications has emerged from manufacturers of industrial robots. With an estimated installation base in 2014 of about 1.5 million units, some 171000 new installations in that year and an annual turnover of the robotics industry estimated to be US$ 32 billion, industrial robots are by fa