An energy-saving nonlinear position control strategy for electro-hydraulic servo systems

The electro-hydraulic servo system (EHSS) demonstrates numerous advantages in size and performance compared to other actuation methods. Oftentimes, its utilization in industrial and machinery settings is limited by its inferior efficiency. In this paper, a nonlinear backstepping control algorithm with an energy-saving approach is proposed for position control in the EHSS. To achieve improved efficiency, two control valves including a proportional directional valve (PDV) and a proportional relief valve (PRV) are used to achieve the control objectives. To design the control algorithm, the state space model equations of the system are transformed to their normal form and the control law through the PDV is designed using a backstepping approach for position tracking. Then, another nonlinear set of laws is derived to achieve energy-saving through the PRV input. This control design method, based on the normal form representation, imposes internal dynamics on the closed-loop system. The stability of the internal dynamics is analyzed in special cases of operation. Experimental results verify that both tracking and energy-saving objectives are satisfied for the closed-loop system.     

M. Carey Lea, the first mechanochemist

The experiments of M. Carey Lea (1823-1897) are usually considered the first systematic investigations on the chemical effects of mechanical action. This paper collects the most important facts about Lea's life and discusses his research from the point of view of mechanochemistry. Lea was born into a family of considerable privilege and exceptional achievements. He suffered from weak health throughout his life. Consequently, he was educated at home by a tutor and later worked in the private laboratory of his home in Philadelphia. Lea was primarily a photochemist, his first mechanochemical observation in 1866 concerned the pressure sensitivity of photographic plates. Later in his life, he investigated the effect of various kinds of energy—heat, light, mechanical action—on allotropic (colloidal) silver and silver halides. The “parallelism” of the results motivated Lea to study the mechanochemical decomposition of dozens of stable compounds between 1892 and 1894. He observed the decomposition of silver and mercuric chlorides by trituration in a mortar, although the same compounds are known to melt or sublime undecomposed when heated. Lea was elected member of the National Academy of Sciences in 1892.     

Beyond Boundary Objects: Collaborative Reuse in Aircraft Technical Support

Boundary objects are a critical, but understudied, theoretical construct in CSCW. Through a field study of aircraft technical support, we examined the role of boundary objects in the practical achievement of safety by service engineers. Their resolution of repair requests was preserved in the organization’s memory via three compound boundary objects. These crystallizations did not manifest a static interpretation, but instead were continually reinterpreted in light of meta-negotiations. This suggests design implications for organizational memory systems which can more fluidly represent the meta-negotiations surrounding boundary objects.     

Discourse cues to deception in the case of multiple receivers

Behavioral cues to deception are instrumental in detecting deception. As one of the primary sources of deception behavior, text has been analyzed at the level of sub-sentence or message but not the discourse of interaction. Additionally, empirical studies on cues to deception in the case of multiple receivers remain nonexistent. To fill these voids, we propose a discourse framework and six hypotheses about deception behaviors in a multi-receiver environment. The deception behaviors are operationalized by discourse features based on an analysis of real-world data. The results of statistical analysis validate the efficacy of discourse features in discriminating deceivers from truth-tellers.     

Experimental study and model validation of selective spinal cord and brain hypothermia induced by a simple torso-cooling pad

In vivo experiments have been performed to test the effectiveness of a torso-cooling pad to reduce the temperature in the spinal cord and brain in rats. Coolant was circulated through the cooling pad to provide either mild or moderate cooling. Temperatures in the brain tissue, on the head surface, and on the spine and back surfaces were measured. During mild cooling, the temperature on the back surface was 22.82 +/- 2.43 degrees C compared to 29.34 +/- 1.94 degrees C on the spine surface. The temperature on the back surface during moderate cooling was 13.66 +/- 1.28 degrees C compared to 24.12 +/- 5.7 degrees C on the spine surface. Although the temperature in the brain tissue did not drastically deviate from its baseline value during cooling, there was a difference between the rectal and brain temperatures during cooling, which suggests mild hypothermia in the brain tissue. Using experimental data, theoretical models of the rat head and torso were developed to predict the regional temperatures and to validate the rat models. There was good agreement between the theoretical and experimental temperatures in the torso region. Differences between the predicted and measured temperatures in the brain are likely to be the result of imperfect mixing between the cold spinal fluid and the warm cerebrospinal fluid that surrounds the brain.     

A privacy preserving technique for distance-based classification with worst case privacy guarantees

There has been relatively little work on privacy preserving techniques for distance based mining. The most widely used ones are additive perturbation methods and orthogonal transform based methods. These methods concentrate on privacy protection in the average case and provide no worst case privacy guarantee. However, the lack of privacy guarantee makes it difficult to use these techniques in practice, and causes possible privacy breach under certain attacking methods. This paper proposes a novel privacy protection method for distance based mining algorithms that gives worst case privacy guarantees and protects the data against correlation-based and transform-based attacks. This method has the following three novel aspects. First, this method uses a framework to provide theoretical bound of privacy breach in the worst case. This framework provides easy to check conditions that one can determine whether a method provides worst case guarantee. A quick examination shows that special types of noise such as Laplace noise provide worst case guarantee, while most existing methods such as adding normal or uniform noise, as well as random projection method do not provide worst case guarantee. Second, the proposed method combines the favorable features of additive perturbation and orthogonal transform methods. It uses principal component analysis to decorrelate the data and thus guards against attacks based on data correlations. It then adds Laplace noise to guard against attacks that can recover the PCA transform. Third, the proposed method improves accuracy of one of the popular distance-based classification algorithms: K-nearest neighbor classification, by taking into account the degree of distance distortion introduced by sanitization. Extensive experiments demonstrate the effectiveness of the proposed method.     

Applications of wavelet data reduction in a recommender system

Memory-based collaborative filtering (CF) recommender systems have emerged as an effective technique for information filtering. CF recommenders are being widely adopted for e-commerce applications to assist users in finding and selecting items of interest. As a result, the scalability of CF recommenders presents a significant challenge; one that is particularly resilient because the volume of data these systems utilize will continue to increase over time. This paper examines the impact of discrete wavelet transformation (DWT) as an approach to enhance the scalability of memory-based collaborative filtering recommender systems. In particular, a wavelet transformation methodology is proposed and applied to both synthetic and real-world recommender ratings. For experimental purposes, the DWT methodology’s effect on predictive accuracy and calculation speed is evaluated to compare recommendation quality and performance.     

Remote sensing of photosynthetic light-use efficiency across two forested biomes: Spatial scaling

Eddy covariance (EC) measurements have greatly advanced our knowledge of carbon exchange in terrestrial ecosystems. However, appropriate techniques are required to upscale these spatially discrete findings globally. Satellite remote sensing provides unique opportunities in this respect, but remote sensing of the photosynthetic light-use efficiency (ε), one of the key components of Gross Primary Production, is challenging. Some progress has been made in recent years using the photochemical reflectance index, a narrow waveband index centered at 531 and 570 nm. The high sensitivity of this index to various extraneous effects such as canopy structure, and the view observer geometry has so far prevented its use at landscape and global scales. One critical aspect of upscaling PRI is the development of generic algorithms to account for structural differences in vegetation. Building on previous work, this study compares the differences in the PRI: ? relationship between a coastal Douglas-fir forest located on Vancouver Island, British Columbia, and a mature Aspen stand located in central Saskatchewan, Canada. Using continuous, tower-based observations acquired from an automated multi-angular spectro-radiometer (AMSPEC II) installed at each site, we demonstrate that PRI can be used to measure ? throughout the vegetation season at the DF-49 stand (r² = 0.91, p < 0.00) as well as the deciduous site (r² = 0.88, p < 0.00). It is further shown that this PRI signal can be also observed from space at both sites using daily observations from the Moderate Resolution Imaging Spectro-radiometer (MODIS) and a multi-angular implementation of atmospheric correction (MAIAC) (r² = 0.54 DF-49; r² = 0.63 SOA; p < 0.00). By implementing a simple hillshade model derived from airborne light detection and ranging (LiDAR) to approximate canopy shadow fractions (α_s), it is further demonstrated that the differences observed in the relationship between PRI and ε at DF-49 and SOA can be attributed largely to differences in α_s. The findings of this study suggest that algorithms used to separate physiological from extraneous effects in PRI reflectance may be more broadly applicable and portable across these two climatically and structurally different biome types, when the differences in canopy structure are known.