Daimler (United States)

This paper uses a sample of more than 2,500 firms from 27 countries to investigate the relation among ownership structure, analyst following, investor protection, and valuation. We find that analysts are less likely to follow firms with potential incentives to withhold or manipulate information, such as when the family/management group is the largest control rights blockholder. Furthermore, this relation is stronger for firms from low‐shareholder‐protection countries. Using valuation regressions that take into account potential endogeneity between analyst following and firm value, we find a positive valuation effect when analysts cover firms that have both potentially poor internal governance and weak country‐level external governance. Overall, our findings suggest that corporate governance plays an important role in analysts' willingness to follow firms and that increased analyst following is associated with higher valuations, particularly for firms likely to face governance problems.

The automotive industry is moving aggressively in the direction of advanced active safety. Dedicated short-range communication (DSRC) is a key enabling technology for the next generation of communication-based safety applications. One aspect of vehicular safety communication is the routine broadcast of messages among all equipped vehicles. Therefore, channel congestion control and broadcast performance improvement are of particular concern and need to be addressed in the overall protocol design. Furthermore, the explicit multichannel nature of DSRC necessitates a concurrent multichannel operational scheme for safety and non-safety applications. This article provides an overview of DSRC based vehicular safety communications and proposes a coherent set of protocols to address these requirements

The present study examines changes in a variety of oculomotoric variables as a function of increasing sleepiness in 129 participants, who have been passed through a broad range of subjective alertness. Up to now, spontaneous eye blinks are the most promising biosignal for in-car sleepiness warnings. Reviewing the current literature on eye movements and fatigue, experimental data are provided including additional indicative oculomotoric parameters; inter-individual differences in the experiments were also assessed. Here, self-rated alertness decreased over six steps on average and proved itself a reliable measurement. Regarding oculomotoric parameters, blink duration, delay of lid reopening, blink interval and standardised lid closure speed were identified as the best indicators of subjective as well as objective sleepiness. Saccadic parameters and fixation durations also showed specific changes with increasing sleepiness. Substantial inter-individual differences in all of these variables were illustrated. Oculomotoric parameters were linked to three different components of sleepiness while driving: a) deactivation; b) decreasing attention, resulting in disinhibition of spontaneous blinks and reflexive saccades; c) increasing attempts of self-activation. Finally, implications for the development of drowsiness detection devices were discussed.

NS-2, with its IEEE 802.11 support, is a widely utilized simulation tool for wireless communications researchers. However, the current NS-2 distribution code has some significant shortcomings both in the overall architecture and the modeling details of the IEEE 802.11 MAC and PHY modules. This paper presents a completely revised architecture and design for these two modules. The resulting PHY is a full featured generic module able to support any single channel frame-based communications (i.e. it is also able to support non-IEEE 802.11 based MAC). The key features include cumulative SINR computation, preamble and PLCP header processing and capture, and frame body capture. The MAC accurately models the basic IEEE 802.11 CSMA/CA mechanism, as required for credible simulation studies. The newly designed MAC models transmission and reception coordination, backoff management and channel state monitoring in a structured and modular manner. In turn, the contributions of this paper make extending the MAC for protocol researches much easier and provide for a significantly higher level of simulation accuracy.

One key usage of VANET is to support vehicle safety applications. This use case is characterized by the prominence of broadcasts in scaled settings. In this context, we try to answer the following questions: i) what is the probability of reception of a broadcast message by another car depending on its distance to the sender, ii) how to give priority access and an improved reception rate for important warnings, e.g., sent out in an emergency situation, and iii) how are the above two results affected by signal strength fluctuations caused by radio channel fading? We quantify via simulation the probability of reception for the two-ray-ground propagation model as well as for the Nakagami distribution in saturated environments. By making use of some IEEE 802.11e EDCA mechanisms for priority access, we do not only quantify how channel access times can be reduced but also demonstrate how improved reception rates can be achieved. Our results show that the mechanisms for priority access are successful under the two-way-ground model. However, with a non-deterministic radio propagation model like Nakagami's distribution the benefit is still obvious but the general level of probability of reception is much smaller compared to two-ray-ground model. The results indicate that -- particularly for safety-critical and sensor network type of applications -- the proper design of repetition or multi-hop retransmission strategies represents an important aspect of future work for robustness and network stability of vehicular ad hoc networks.

OBJECTIVE: Despite advances in diagnostic techniques, unnecessary laparotomies (no repairs/no drains) are still performed in trauma centers. The true risks of such procedures are unclear. Our hypothesis was that the overall incidences of complications after an unnecessary laparotomy for trauma that have been reported in the literature were significant underestimates because of flaws in study design. To test our hypothesis, a prospective study to record all perioperative complications in patients undergoing an unnecessary laparotomy for trauma was performed. DESIGN: Prospective case series. MEASUREMENTS AND MAIN RESULTS: The main outcome measures were perioperative complications. An unnecessary laparotomy was performed in 254 patients who sustained trauma. The mechanism of injury was a penetrating wound in 98% of the patients. Complications occurred in 41.3% of the patients (n = 105) and included atelectasis (15.7%), postoperative hypertension that required medical treatment (11.0%), pleural effusion (9.8%), pneumothorax (5.1%), prolonged ileus (4.3%), pneumonia (3.9%), surgical wound infection (3.2%), small bowel obstruction (2.4%), urinary infection (1.9%), and others. Complication rates for patients who did (n = 111) and did not (n = 143) have an associated injury were 61.3% and 25.9%, respectively (p = 0.0001). Complications occurred in 19.7% of 81 patients who did not have an associated injury and who did not have intraperitoneal or retroperitoneal penetration. The mortality rate for the entire series was 0.8% and was unrelated to the unnecessary laparotomies. CONCLUSIONS: Unnecessary laparotomies for trauma result in a significant morbidity when complications are recorded prospectively. Current efforts to reduce the incidence of these unnecessary procedures without increasing that of missed injuries are obviously worthwhile.

A method is proposed for designing stable controllers with arbitrarily small tracking error for uncertain, mismatched nonlinear systems. This method is another "synthetic input technique", similar to backstepping and multiple surface control methods, but with an important addition, r-1 low pass filters are included in the design, where r is the relative degree of the output to be controlled. It is shown that these low pass filters allow a design where the model is not differentiated, thus ending the complexity arising due to the "explosion of terms" that has made other methods difficult to implement in practice. This paper presents the method and proves stability via a composite Lyapunov method.

The main purpose of this exploratory study was to examine the relationship between certain learning organization characteristics and change adaptation, innovation, and bottom-line organizational performance. The following learning organization characteristics were found to be the strongest predictors of rapid change adaptation, quick product or service introduction, and bottomline organizational performance: open communications and information sharing; risk taking and new idea promotion; and information, facts, time, and resource availability to perform one's job in a professional manner.

Most document recognition work to date has been performed on English text. Because of the large overlap of the character sets found in English and major Western European languages such as French and German, some extensions of the basic English capability to those languages have taken place. However, automatic language identification prior to optical character recognition is not commonly available and adds utility to such systems. Languages and their scripts have attributes that make it possible to determine the language of a document automatically. Detection of the values of these attributes requires the recognition of particular features of the document image and, in the case of languages using Latin-based symbols, the character syntax of the underlying language. We have developed techniques for distinguishing which language is represented in an image of text. This work is restricted to a small but important subset of the world's languages. The method first classifies the script into two broad classes: Han-based and Latin-based. This classification is based on the spatial relationships of features related to the upward concavities in character structures. Language identification within the Han script class (Chinese, Japanese, Korean) is performed by analysis of the distribution of optical density in the text images. We handle 23 Latin-based languages using a technique based on character shape codes, a representation of Latin text that is inexpensive to compute.

As computers and other information technology move into cars and trucks, distraction-related crashes are likely to become an important problem. This paper begins to address this problem by examining how alert strategy (graded and single-stage) and alert modality (haptic and auditory) affect how well collision warning systems mitigate distraction and direct drivers attention to the car ahead when it unexpectedly brakes. We conducted two experiments in which drivers interacted with an in-vehicle email system and a collision warning system signaled a braking lead vehicle. The first experiment showed that graded alerts led to a greater safety margin and a lower rate of inappropriate responses to nuisance warnings. A second experiment focused on attitudes toward the collision warning system and found that graded alerts were more trusted than single stage alerts and that haptic alerts, a vibrating seat in these experiments, were perceived as less annoying and more appropriate. Graded haptic alerts offer a promising approach to developing context aware computing in a safety-critical application.

<div class="htmlview paragraph">The purpose of the 4-SPACE (<b>4-S</b>troke <b>P</b>owered gasoline <b>A</b>uto-ignition <b>C</b>ontrolled combustion <b>E</b>ngine) industrial research project is to research and develop an innovative controlled auto-ignition combustion process for lean burn automotive gasoline 4-stroke engines application. The engine concepts to be developed could have the potential to replace the existing stoichiometric / 3-way catalyst automotive spark ignition 4-stroke engines by offering the potential to meet the most stringent EURO 4 emissions limits in the year 2005 without requiring DeNOx catalyst technology. A reduction of fuel consumption and therefore of corresponding CO2 emissions of 15 to 20% in average urban conditions of use, is expected for the « 4-SPACE » lean burn 4-stroke engine with additional reduction of CO emissions.</div> <div class="htmlview paragraph">This paper describes the first set of results of different experimental and numerical studies aiming to get such new combustion process in 4-stroke engines within the framework of this European consortium.</div> <div class="htmlview paragraph">One of the target of this consortium driven by IFP, is to develop a 4-stroke gasoline engine running conventionally at high load (with a normal compression ratio and without any intake air heating) and able to achieve <b>C</b>ontrolled <b>A</b>uto-<b>I</b>gnition (CAI) process at part load by reproducing the 2-stroke internal conditions (internal EGR rate and fluid dynamic control, temperature level…) favorable to this particular combustion process. For this purpose and as a starting point of the work program, a production 2-stroke engine known for its part load auto-ignition behavior is fully studied. Such work is focused on the analysis of in-cylinder conditions prior to auto-ignition using combined experimental testing, 3D CFD computations and optical diagnostics.</div> <div class="htmlview paragraph">From this analysis, 1D CFD computations have been extensively performed to evaluate the possible 4-stroke concepts able to reproduce internal conditions favorable to CAI. Then, the most “promising” configurations have been experimentally investigated. Encouraging preliminary results have already shown that NOx emissions are reduced by 10 to 40 times and the fuel economy is improved by 8 to 10% when compared with stoichiometric reference conditions.</div> <div class="htmlview paragraph">Other ways of getting auto-ignition of the lean fresh mixture are also explored by the project partners. The effects of several parameters, such as the fuel composition, the engine compression ratio, the intake air temperature level, etc… are also included in the research program. Thus, to analyze better analyze intrinsic auto-ignition process, specific tools as for example Rapid Compression Machine have been developed. Different fuels at various initial conditions (e.g. temperature, excess air) have been tested and compared, for example in terms for example of combustion rate and auto-ignition delay. Results obtained contribute to the better understanding of the auto-ignition process.</div> <div class="htmlview paragraph">Preliminary visualization results from specially designed single cylinder engines (2-stroke and 4-stroke) have been obtained for controlled auto-ignition combustion. The effect of charge stratification is briefly discussed.</div>

A new approach to dynamic feedback linearization control of an induction motor is given, Previously, it has been shown that the dynamic model of an induction motor, consisting of speed, stator currents, and rotor flux, is dynamically feedback linearizable. However, the controller and transformation were valid only as long as the motor torque was nonzero and the methodology required switching between two computationally complex transformations. Here it is shown that by considering the direct-quadrature model of the induction motor, a single dynamic feedback linearizing transformation exists and is valid (essentially) as long as the (magnitude of the) rotor flux is nonzero. Furthermore, the resulting control computations are well within the capabilities of contemporary microprocessor technology.

Dedicated Short Range Communication (DSRC) wireless band, allocated by the FCC for vehicular communication, constitutes the basis for one of the first vehicular ad-hoc networks/systems that is likely to be deployed. Therefore, it is important to characterize the physical properties of the DSRC channel.In this work we propose that due to the complexity, unpredictability and wide variety of road environments a statistical parametric model should be used to describe the physical channel behavior, and its parameters should be inferred from empirical data.Based on this methodological approach we construct channel gain models for two different environments: an open space and a typical highway with moderate traffic. To model the distribution of channel gain amplitude we choose the well-known two-parameter Nakagami model and estimate the distance dependency of its parameters from empirical road data. Spatial correlation of the channel strength is also estimated for a few separation distances.The results obtained show that in both environments the Nakagami average power parameter O falls off as the inverse-square of the sender-receiver separation distance up to a crossover distance of about 160m and as the inverse-fourth of the distance thereafter. The Nakagami fading parameter m lies between 1 and 4 for the open area and between 0.5 and 1 for the highway. The spatial correlation coefficients lie between 0.4 and 0.75 for the open environment, but between 0.9 and 1 for the highway. These results provide valuable input to support the design of optimal modulation, coding, diversity and protocol schemes for vehicle-to-vehicle and vehicle-to-infrastructure communication.

Maneuver recognition and trajectory prediction of moving vehicles are two important and challenging tasks of advanced driver assistance systems (ADAS) at urban intersections. This paper presents a continuing work to handle these two problems in a consistent framework using non-parametric regression models. We provide a feature normalization scheme and present a strategy for constructing three-dimensional Gaussian process regression models from two-dimensional trajectory patterns These models can capture spatio-temporal characteristics of traffic situations. Given a new, partially observed and unlabeled trajectory, the maneuver can be recognized online by comparing the likelihoods of the observation data for each individual regression model. Furthermore, we take advantage of our representation for trajectory prediction. Because predicting possible trajectories at urban intersection involves obvious multimodalities and non-linearities, we employ the Monte Carlo method to handle these difficulties. This approach allows the incremental prediction of possible trajectories in situations where unimodal estimators such as Kalman Filters would not work well. The proposed framework is evaluated experimentally in urban intersection scenarios using real-world data.

Dissatisfied with our unnecessary laparotomy rate in patients with gunshot wounds (GSWs) to the right thoracoabdomen (RTA), a prospective study was designed to test the hypothesis that hemodynamically stable patients without peritonitis could be managed without a surgical procedure. From 1990 through 1993, 13 consecutive patients with a GSW between the right nipple, costal margin, right posterior axillary line, and anterior midline were studied. No patient had or developed more than local wound tenderness. All patients had a right hemothorax treated with a chest tube. Computed tomographic (CT) scanning of the RTA was performed within 8 hours of admission in 12 of the 13 patients, and the following injuries were noted: pulmonary contusion (12), hepatic laceration (seven), spinal cord transection (two), and a renal laceration (one). Follow-up CT scans, 3 to 14 days after injury, in six of the seven patients with hepatic wounds showed partial or complete resolution of the injury in all. In one patient, an associated renal injury was unchanged on the follow-up CT scan. Mean length of hospitalization for the 11 patients who did not have an injury to the spinal cord was 5.1 days (3–8 days). Complications included atelectasis (four), a small persistent pneumothorax (two), and pneumonia (one). No complications occurred after discharge. Conclusions from this prospective study were: (1) hemodynamically stable patients without peritonitis after sustaining a GSW to the RTA can be managed nonsurgically with a low incidence of minor intrathoracic complications; (2) thoracoabdominal CT scanning is a comprehensive means of diagnosis and follow-up when nonsurgical management is chosen; and (3) such patients will usually have injury to the right lung and the liver.

This article focuses on development baseline for a novel LIDAR for future autonomous cars, which require perception not only in clear weather, but also under harsh weather conditions such as fog and rain. Development of automotive laser scanners is bound to the following requirements: maximize sensor performance, assess the performance level and keep the scanner component costs reasonable (<;1000 €) even if more expensive optical and electronic components are needed. The objective of this article is to review the existing automotive laser scanners and their capabilities to pave the way for developing new scanner prototypes, which are more capable in harsh weather conditions. Testing of scanner capabilities has been conducted in the northern part of the Finland, at Sodankylä Airport, where fog creates a special problem. The scanner has been installed in the airport area for data gathering and analyzes if fog, snow or rain are visible in the scanner data. The results indicate that these conditions degrade sensor performance by 25%, and therefore, future work in software module development should take this into account with in-vehicle system performance estimations concerning the visual range of the scanner. This allows the vehicle to adapt speed, braking distance and stability control systems accordingly.

Risk estimation for the current traffic situation is crucial for safe autonomous driving systems. One part of the uncertainty in risk estimation is the behavior of the surrounding traffic participants. In this paper we focus on highway scenarios, where possible behaviors consist of a change in acceleration and lane change maneuvers. We present a novel approach for the recognition of lane change intentions of traffic participants. Our novel approach is an extension of the Naïve Bayesian approach and results in a generative model. It builds on the relations to the directly surrounding vehicles and to the static traffic environment. We obtain the conditional probabilities of all relevant features using Gaussian mixtures with a flexible number of components. We systematically reduce the number of features by selecting the most powerful ones. Furthermore we investigate the predictive power of each feature with respect to the time before a lane change event. In a large scale experiment on real world data with over 160.781 samples collected on a test drive of 1100km we trained and validated our intention prediction model and achieved a significant improvement in the recognition performance of lane change intentions compared to current state of the art methods.

Understanding traffic situations in dynamic traffic environments is an essential requirement for autonomous driving. The prediction of the current traffic scene into the future is one of the main problems in this context. In this publication we focus on highway scenarios, where the maneuver space for traffic participants is limited to a small number of possible behavior classes. Even though there are many publications in the field of maneuver prediction, most of them set the focus on the classification problem, whether a certain maneuver is executed or not. We extend approaches which solve the classification problem of lane-change behavior by introducing the novel aspect of estimating a continuous distribution of possible trajectories. Our novel approach uses the probabilities which are assigned by a Random Decision Forest to each of the maneuvers lane following, lane change left and lane change right. Using measured data of a vehicle and the knowledge of the typical lateral movement of vehicles over time taken from realworlddata, we derive a Gaussian Mixture Regression method. For the final result we combine the predicted probability density functions of the regression method and the computed maneuver probabilities using a Mixture of Experts approach. In a large scale experiment on real world data collected on multiple test drives we trained and validated our prediction model and show the gained high prediction accuracy of the proposed method.

Details a method for measuring three key vehicle states-wheel slip, body sideslip angle, and tire sideslip angle-using GPS velocity information in conjunction with other sensors. Based on initial noise data obtained from the system components, a prediction of the accuracy of these new measurements is obtained. Subsequent experiments validate both the methodology for obtaining the measurements as well as the error analysis. The experimental results for the GPS velocity-based sideslip angle measurement compare favorably to theoretical predictions, suggesting that this technique has merit for future implementation in vehicle safety systems.

Side on! Combined FTIR and NMR studies revealed the presence of a side-on nitrosyl species in the zeolite Cu-SSZ-13. This intermediate is very similar to those found in nitrite reductase enzyme systems. The identification of this intermediate led to the proposal of a reaction mechanism that is fully consistent with the results of both kinetic and spectroscopic studies. As a service to our authors and readers, this journal provides supporting information supplied by the authors. Such materials are peer reviewed and may be re-organized for online delivery, but are not copy-edited or typeset. Technical support issues arising from supporting information (other than missing files) should be addressed to the authors. Please note: The publisher is not responsible for the content or functionality of any supporting information supplied by the authors. Any queries (other than missing content) should be directed to the corresponding author for the article.