General Motors (Poland)

Wireless indoor positioning systems have become very popular in recent years. These systems have been successfully used in many applications such as asset tracking and inventory management. This paper provides an overview of the existing wireless indoor positioning solutions and attempts to classify different techniques and systems. Three typical location estimation schemes of triangulation, scene analysis, and proximity are analyzed. We also discuss location fingerprinting in detail since it is used in most current system or solutions. We then examine a set of properties by which location systems are evaluated, and apply this evaluation method to survey a number of existing systems. Comprehensive performance comparisons including accuracy, precision, complexity, scalability, robustness, and cost are presented.

Catalysts based on single atoms of scarce precious metals can lead to more efficient use through enhanced reactivity and selectivity. However, single atoms on catalyst supports can be mobile and aggregate into nanoparticles when heated at elevated temperatures. High temperatures are detrimental to catalyst performance unless these mobile atoms can be trapped. We used ceria powders having similar surface areas but different exposed surface facets. When mixed with a platinum/aluminum oxide catalyst and aged in air at 800°C, the platinum transferred to the ceria and was trapped. Polyhedral ceria and nanorods were more effective than ceria cubes at anchoring the platinum. Performing synthesis at high temperatures ensures that only the most stable binding sites are occupied, yielding a sinter-resistant, atomically dispersed catalyst.

The present work provides a novel one-step synthesis for nitrogen-doped activated carbon. The excellent performance of the N-doped AC allows its further application in a hybrid-type supercapacitor, which utilizes a combination of the capacitor electrode and a Li-ion battery anode.

Recent advances in domain adaptation show that deep self-training presents a powerful means for unsupervised domain adaptation. These methods often involve an iterative process of predicting on target domain and then taking the confident predictions as pseudo-labels for retraining. However, since pseudo-labels can be noisy, self-training can put overconfident label belief on wrong classes, leading to deviated solutions with propagated errors. To address the problem, we propose a confidence regularized self-training (CRST) framework, formulated as regularized self-training. Our method treats pseudo-labels as continuous latent variables jointly optimized via alternating optimization. We propose two types of confidence regularization: label regularization (LR) and model regularization (MR). CRST-LR generates soft pseudo-labels while CRST-MR encourages the smoothness on network output. Extensive experiments on image classification and semantic segmentation show that CRSTs outperform their non-regularized counterpart with state-of-the-art performance. The code and models of this work are available at https://github.com/yzou2/CRST.

Several multihop applications developed for vehicular ad hoc networks use broadcast as a means to either discover nearby neighbors or propagate useful traffic information to other vehicles located within a certain geographical area. However, the conventional broadcast mechanism may lead to the so-called <i xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">broadcast</i> <i xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">storm</i> problem, a scenario in which there is a high level of contention and collisions at the link layer due to an excessive number of broadcast packets. While this is a well-known problem in mobile ad hoc wireless networks, only a few studies have addressed this issue in the VANET context, where mobile hosts move along the roads in a certain limited set of directions as opposed to randomly moving in arbitrary directions within a bounded area. Unlike other existing works, we quantify the impact of broadcast storms in VANETs in terms of message delay and packet loss rate in addition to conventional metrics such as message reachability and overhead. Given that VANET applications are currently confined to using the DSRC protocol at the data link layer, we propose three probabilistic and timer-based broadcast suppression techniques: <i xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">weighted</i> <i xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">p-persistence,</i> <i xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">slotted</i> <i xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">1-persistence,</i> <i xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">and</i> <i xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">slotted</i> <i xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">p-persistence</i> <i xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">schemes</i> , to be used at the network layer. Our simulation results show that the proposed schemes can significantly reduce contention at the MAC layer by achieving up to 70 percent reduction in packet loss rate while keeping end-to-end delay at acceptable levels for most VANET applications.

Background: Polynomial Systems Homotopy Continuation Projective Spaces Probability One Polynomials of One Variable Other Methods Isolated Solutions: Coefficient-Parameter Homotopy Polynomial Structures Case Studies Endpoint Estimation Checking Positive Dimensional Solution Sets: Some Concepts from Algebraic Geometry Basic Numerical Algebraic Geometry Cascading Through Embedded Systems The Numerical Irreducible Decomposition Intersection of Algebraic Sets.

article Free Access Share on Data mining and knowledge discovery in databases Authors: Usama Fayyad Jet Propulsion Laboratory, California Institute of Technology Jet Propulsion Laboratory, California Institute of TechnologyView Profile , Ramasamy Uthurusamy General Motors Corp. General Motors Corp.View Profile Authors Info & Claims Communications of the ACMVolume 39Issue 11Nov. 1996 pp 24–26https://doi.org/10.1145/240455.240463Online:01 November 1996Publication History 409citation3,548DownloadsMetricsTotal Citations409Total Downloads3,548Last 12 Months76Last 6 weeks9 Get Citation AlertsNew Citation Alert added!This alert has been successfully added and will be sent to:You will be notified whenever a record that you have chosen has been cited.To manage your alert preferences, click on the button below.Manage my Alerts New Citation Alert!Please log in to your account Save to BinderSave to BinderCreate a New BinderNameCancelCreateExport CitationPublisher SiteeReaderPDF

&lt;div class="htmlview paragraph"&gt;The objective of this work was to understand the physics of combustion-generated pressure waves from Homogeneous Charge Compression Ignition combustion and the resulting audible noise that is produced. Experiments were performed with a single-cylinder engine operating in both SI and HCCI combustion modes, and comparisons were made between the pressure waves generation from the two types of combustion. Cylinder pressure oscillation amplitudes at the first circumferential mode frequency (5 to 6 kHz) generated in HCCI combustion are 5 to 10 times higher than those generated in SI knocking combustion without an undue increase in audible engine noise. Frequency analysis of the data showed that in knocking combustion a larger portion of the wave energy is contained within the higher order resonance modes. Cylinder block vibration measurements indicate that the cylinder liner significantly dissipates the wave energy below 8 kHz.&lt;/div&gt; &lt;div class="htmlview paragraph"&gt;A correlation for the pressure wave intensity was developed and used to successfully correlate all of the experimental data. The correlation was applied to data obtained from the literature from a HCCI engine operated under supercharged conditions, and was able to successfully explain the experimental observation that with higher boost levels the engine could withstand higher rates of pressure rise without an increase in audible engine noise.&lt;/div&gt;

Machine-learning (ML) hardware and software system demand is burgeoning. Driven by ML applications, the number of different ML inference systems has exploded. Over 100 organizations are building ML inference chips, and the systems that incorporate existing models span at least three orders of magnitude in power consumption and five orders of magnitude in performance; they range from embedded devices to data-center solutions. Fueling the hardware are a dozen or more software frameworks and libraries. The myriad combinations of ML hardware and ML software make assessing ML-system performance in an architecture-neutral, representative, and reproducible manner challenging. There is a clear need for industry-wide standard ML benchmarking and evaluation criteria. MLPerf Inference answers that call. In this paper, we present our benchmarking method for evaluating ML inference systems. Driven by more than 30 organizations as well as more than 200 ML engineers and practitioners, MLPerf prescribes a set of rules and best practices to ensure comparability across systems with wildly differing architectures. The first call for submissions garnered more than 600 reproducible inference-performance measurements from 14 organizations, representing over 30 systems that showcase a wide range of capabilities. The submissions attest to the benchmark’s flexibility and adaptability.

Engineering systems are now frequently optimized via computer models.The inputoutput relationships in these models are often highly nonlinear deterministic functions that are expensive to compute.Thus, when searching for the global optimum, it is desirable to minimize the number of function evaluations.Bayesian global optimization methods are well-suited to this task because they make use of all previous evaluations in selecting the next search point.A statistical model is fit to the sampled points which allows predictions to be made elsewhere, along with a measure of possible prediction error (uncertainty).The next point is chosen to maximize a criterion that balances searching where the predicted value of the function is good (local search) with searching where the uncertainty of prediction is large (global search).We extend this methodology in several ways.First, we introduce a parameter that controls the local-global balance.Secondly, we propose a method for dealing with nonlinear inequality constraints from additional response variables.Lastly, we adapt the sequential algorithm to proceed in stages rather than one point at a time.The extensions are illustrated using a shape optimization problem from the automotive industry. Introduction.Global optimization via a computer model (sometimes called a computer code) is a problem encountered frequently in engineering.In this article, for example, we will discuss the optimization of the shape of an automobile piston.The inputs to the piston model are parameters describing the piston shape.The outputs are quality characteristics: undesirable piston motion (which causes noise) and the maximum pressure between the piston and the bore (which affects wear).The objective is to find the combination of shape parameters that minimizes maximum pressure subject to a constraint on motion.When function evaluations are fairly expensive, as here, there is a need to use optimization methods that require few evaluations.We shall see that the objective, maximum pressure, is highly nonlinear in the shape parameters; hence, some care is also necessary to find the global optimum.

A highly lithium ionic conductive solid-state electrolyte coating layer significantly increases cathode performance in lithium ion batteries.

In 1928, U.S. presidential candidate Herbert Hoover promised growing prosperity represented by “a chicken in every pot and two cars in every garage.” We now find ourselves at a point in history wondering if and when the power for those cars will come from fuel cells instead of internal combustion engines.

We report on the effects of partial substitution of nickel by palladium on the thermoelectric properties of ZrNiSn-based half-Heusler compounds. It is shown that the substitution of palladium for nickel results in a significant, beneficial reduction of the thermal conductivity. The Seebeck coefficient also decreases, but only by a small amount. In the Hf0.5Zr0.5Ni0.8Pd0.2Sn0.99Sb0.01 compound, a power factor of 22.1 μW K−2 cm−1 and a thermal conductivity as low as 4.5 W/m K are measured at room temperature. The dimensionless figure of merit ZT increases with increasing temperature and reaches a maximum value of 0.7 at about 800 K.

Since the first report of using micromechanical cleavage method to produce graphene sheets in 2004, graphene/graphene‐based nanocomposites have attracted wide attention both for fundamental aspects as well as applications in advanced energy storage and conversion systems. In comparison to other materials, graphene‐based nanostructured materials have unique 2D structure, high electronic mobility, exceptional electronic and thermal conductivities, excellent optical transmittance, good mechanical strength, and ultrahigh surface area. Therefore, they are considered as attractive materials for hydrogen (H 2 ) storage and high‐performance electrochemical energy storage devices, such as supercapacitors, rechargeable lithium (Li)‐ion batteries, Li–sulfur batteries, Li–air batteries, sodium (Na)‐ion batteries, Na–air batteries, zinc (Zn)–air batteries, and vanadium redox flow batteries (VRFB), etc., as they can improve the efficiency, capacity, gravimetric energy/power densities, and cycle life of these energy storage devices. In this article, recent progress reported on the synthesis and fabrication of graphene nanocomposite materials for applications in these aforementioned various energy storage systems is reviewed. Importantly, the prospects and future challenges in both scalable manufacturing and more energy storage‐related applications are discussed.

Abstract Despite the maximized metal dispersion offered by single-atom catalysts, further improvement of intrinsic activity can be hindered by the lack of neighboring metal atoms in these systems. Here we report the use of isolated Pt 1 atoms on ceria as “seeds” to develop a Pt-O-Pt ensemble, which is well-represented by a Pt 8 O 14 model cluster that retains 100% metal dispersion. The Pt atom in the ensemble is 100–1000 times more active than their single-atom Pt 1 /CeO 2 parent in catalyzing the low-temperature CO oxidation under oxygen-rich conditions. Rather than the Pt-O-Ce interfacial catalysis, the stable catalytic unit is the Pt-O-Pt site itself without participation of oxygen from the 10–30 nm-size ceria support. Similar Pt-O-Pt sites can be built on various ceria and even alumina, distinguishable by facile activation of oxygen through the paired Pt-O-Pt atoms. Extending this design to other reaction systems is a likely outcome of the findings reported here.

The potential of infrastructureless vehicular ad hoc networks for providing safety and nonsafety applications is quite significant. The topology of VANETs in urban, suburban, and rural areas can exhibit fully connected, fully disconnected, or sparsely connected behavior, depending on the time of day or the market penetration rate of wireless communication devices. In this article we focus on highway scenarios, and present the design and implementation of a new distributed vehicular multihop broadcast protocol, that can operate in all traffic regimes, including extreme scenarios such as dense and sparse traffic regimes. DV-CAST is a distributed broadcast protocol that relies only on local topology information for handling broadcast messages in VANETs. It is shown that the performance of the proposed DV-CAST protocol in terms of reliability, efficiency, and scalability is excellent.

Single crystals of the skutterudite ${\mathrm{CoSb}}_{3}$ exhibit large hole mobilities (up to 3000 ${\mathrm{cm}}^{2}$ ${\mathrm{V}}^{\mathrm{\ensuremath{-}}1}$ ${\mathrm{s}}^{\mathrm{\ensuremath{-}}1}$ at room temperature), intrinsic lattice thermal conductivity down to 10 K, and pronounced phonon drag effects in the thermoelectric power. The dependence of the mobility and diffusion thermopower on hole density is consistent with recent band-structure calculations, which indicate that ${\mathrm{CoSb}}_{3}$ possesses a highly nonparabolic valence-band structure.

&lt;div class="htmlview paragraph"&gt;A key element of General Motors' Advanced Propulsion Technology Strategy is the electrification of the automobile. The objectives of this strategy are reduced fuel consumption, reduced emissions and increased energy security/diversification. The introduction of hybrid vehicles was one of the first steps as a result of this strategy. To determine future opportunities and direction, an extensive study was completed to better understand the ability of Plug-in Hybrid Electric Vehicles (PHEV) and Extended-Range Electric Vehicles (E-REV) to address societal challenges. The study evaluated real world representative driving datasets to understand actual vehicle usage. Vehicle simulations were conducted to evaluate the merits of PHEV and E-REV configurations.&lt;/div&gt; &lt;div class="htmlview paragraph"&gt;As derivatives of conventional full hybrids, PHEVs have the potential to deliver a significant reduction in petroleum usage. However, the fuel consumption benefits are limited by the underlying constraints of the base hybrid systems and vehicles. Even with incremental electric power and speed improvements, the PHEV's lack of full-performance, all-electric capability requires engine operation under everyday speed and/or load conditions, regardless of available battery energy. This creates emissions concerns and can severely limit the actual all-electric driving range in the real world.&lt;/div&gt; &lt;div class="htmlview paragraph"&gt;The E-REV is principally an Electric Vehicle (EV) with full vehicle performance available as an EV. Significantly, it overcomes the historical EV re-charge time limitations by adding a fuel-powered electric generator to extend driving range. Actual all-electric driving can regularly be experienced throughout the working energy range of the vehicle's battery without fear of being stranded. The E-REV offers the opportunity for petroleum independence, and a dramatic reduction in emissions for many drivers.&lt;/div&gt; &lt;div class="htmlview paragraph"&gt;An E-REV traction drive and battery system needs to be specifically designed for the task. The systems are significantly more capable and larger than those designed for PHEVs. An E-REV is typically also architected to accommodate packaging of these systems while retaining performance and utility. The compelling benefits of the E-REV drive GM to address these challenges.&lt;/div&gt; &lt;div class="htmlview paragraph"&gt;The study results indicate that both the PHEVs and the E-REVs can play a role in addressing future needs. The study shows that in the real world the PHEV is quite likely to run with blended operation, but the E-REV is very likely to remain in EV mode for most drivers.&lt;/div&gt; &lt;div class="htmlview paragraph"&gt;GM is currently developing both PHEV and E-REV vehicles. The Saturn VUE Green Line PHEV is being developed as a derivative of the conventional 2-Mode Hybrid. The Chevrolet Volt E-REV is also under development with full performance, all-electric capability, but without practical range limitations.&lt;/div&gt;

Vehicular ad hoc networks play a critical role in enabling important active safety applications such as cooperative collision warning. These active safety applications rely on continuous broadcast of self-information by all vehicles, which allows each vehicle to track all its neighboring cars in real time. The most pressing challenge in such safety-driven communication is to maintain acceptable tracking accuracy while avoiding congestion in the shared channel. In this article we propose a transmission control protocol that adapts communication rate and power based on the dynamics of a vehicular network and safety-driven tracking process. The proposed solution uses a closed-loop control concept and accounts for wireless channel unreliability. Simulation results confirm that if packet generation rate and associated transmission power for safety messages are adjusted in an on-demand and adaptive fashion, robust tracking is possible under various traffic conditions.

In December 2013, 16 teams from around the world gathered at Homestead Speedway near Miami, FL to participate in the DARPA Robotics Challenge (DRC) Trials, an aggressive robotics competition partly inspired by the aftermath of the Fukushima Daiichi reactor incident. While the focus of the DRC Trials is to advance robotics for use in austere and inhospitable environments, the objectives of the DRC are to progress the areas of supervised autonomy and mobile manipulation for everyday robotics. NASA's Johnson Space Center led a team comprised of numerous partners to develop Valkyrie, NASA's first bipedal humanoid robot. Valkyrie is a 44 degree‐of‐freedom, series elastic actuator‐based robot that draws upon over 18 years of humanoid robotics design heritage. Valkyrie's application intent is aimed at not only responding to events like Fukushima, but also advancing human spaceflight endeavors in extraterrestrial planetary settings. This paper presents a brief system overview, detailing Valkyrie's mechatronic subsystems, followed by a summarization of the inverse kinematics‐based walking algorithm employed at the Trials. Next, the software and control architectures are highlighted along with a description of the operator interface tools. Finally, some closing remarks are given about the competition, and a vision of future work is provided.