Adaptive predistortion using threshold decomposition‐based piecewise linear modeling

A new adaptive predistortion approach for nonlinear power amplifiers based on the piecewise linear (PWL) approximation of nonlinear functions is presented. The PWL model is obtained using threshold decomposition (TD) of the input‐output characteristics. The TD based PWL model is used to develop a baseband predistorter using both the direct and the indirect learning architectures. The proposed predistorter is proved to provide a better performance in suppressing nonlinear distortion than conventional polynomial predistorters and a reduced hardware complexity as compared to lookup table (LUT) approach. © 2011 Wiley Periodicals, Inc. Int J RF and Microwave CAE, 2011.     

The Digital Learning Classroom: Improving English Language Learners’ academic success in mathematics and reading using interactive whiteboard technology

This study presents the findings from the first-year evaluation of the Round Rock Independent School District’s (ISD) Digital Learning Classroom project, an initiative focused on the improvement of English Language Learners’ (ELL) learning using interactive whiteboard (IWB) technology. An objective of the evaluation was to determine the extent IWB technology could foster performance parity in academic achievement between ELL and regular students, that is, reduce the student achievement gap between these two student groups in 3rd and 5th grade mathematics and reading. These grade levels and subjects were the primary focus of the project because students in grades 3 and 5 that do not pass the state’s standardized assessments in mathematics and reading cannot be promoted to the next grade level and therefore, these are “high stakes” tests for students. A second evaluation objective was to determine whether and the extent to which the Digital Learning Classroom could increase ELL students’ academic learning relative to that of ELL students in traditional classrooms (i.e., without IWBs). Using a quasi-experimental design, the results strongly indicate that IWBs can foster performance parity thereby closing the achievement gap between ELL and regular students while increasing ELL student achievement. Pedagogical implications for teachers of ELL students within the context of Digital Learning Classroom project implementation are presented, as well as recommendations for future study of the Digital Learning Classroom in ELL classroom settings.     

On visual servoing based on efficient second order minimization

This paper deals with the Efficient Second order Minimization (ESM) and the image-based visual servoing schemes. In other words, it deals with the minimization based on the pseudo-inverse of the mean of the Jacobians or on the mean of Jacobian Pseudo-inverses. Chronologically, it has been noticed in Tahri and Chaumette (2003) [22] that ESM generally improves the system behavior when compared with the system in which only the simple Jacobian Pseudo-inverses are used. Subsequently, a mathematical explanation has been given in Malis (2004) [12]. In this paper, the proofs given by Malis are discussed and it will be shown that there is a limitation to the validity of the ESM. We will also show that the use of ESM does not necessarily ensure a better system behavior, especially in the situations where large rotational motions are involved. Further, a new appropriate formula of the ESM is proposed and validated using several kinds of features.     

Enhanced AODV routing protocol for Bluetooth scatternet

Bluetooth is one of the most widespread technologies for personal area networks that allow portable devices to form multi-hop Bluetooth ad hoc networks, so called scatternets. Routing is one of the challenges in scatternets because of its impact on the performance of the network. It should focus on reducing the power consumption in the network because most of the nodes are battery-operated portable devices. In this paper, we propose a routing protocol for Bluetooth scatternets that customizes the Ad hoc On-Demand Distance Vector (AODV) routing protocol by making it power-aware and suitable for scatternets. It enhances the AODV flooding mechanism by excluding all non-bridge slaves from taking apart in the AODV route discovery process. In addition, it improves the AODV route discovery phase by considering the hop count, the predicated node’s power, and the average traffic intensity for each node as metrics for best route selection. By removing HELLO packets, our protocol reduces the control packets overhead and the power consumption in network devices. Simulation results show that the proposed protocol achieved considerable improvements over other enhanced AODV protocols by increasing the data delivery ratio by 10.78%, reducing the average end-to-end delay by 8.11%, and reducing the average energy consumption by 7.92%.     

A Fuzzy Collaborative Assessment Methodology for Partner Trust Evaluation

Trust level assessment within collaborative networks is an interesting issue in the partner evaluation and partner selection literature. This paper proposes a fuzzy collaborative assessment methodology for partner trust evaluation within horizontal collaborative networks. The proposed approach concerns a group evaluation context where a decision‐making comity associated with a manufacturer needs to evaluate its company's partners for their ranking purposes. Different expertise levels are attributed to the comity members. In this paper, trust level is evaluated based on information‐sharing attributes considered in the literature as critical influencing factors. Different weights are associated with these attributes with respect to their corresponding influence on trust. The semantic fuzzy partitioning method is considered for the collaborative trust assessment based on unbalanced linguistic term sets representing information‐sharing attributes. The developed approach is applied to a real case showing its effectiveness and its objectivity.     

A Declarative Approach to Network Device Configuration Correctness

Configuration Logic (CL) is a formal language that allows a network engineer to express constraints in terms of the actual parameters found in the configuration of network devices. We present an efficient algorithm that can automatically check a pool of devices for conformance to a set of CL constraints; moreover, this algorithm can point to the part of the configuration responsible for the error when a constraint is violated. Contrary to other validation approaches that require dumping the configuration of the whole network to a central location in order to be verified, we also present an algorithm that analyzes the correct formulas and greatly helps reduce the amount of data that need to be transferred to that central location, pushing as much of the evaluation of the formula locally on each device. The procedure is also backwards-compatible, in such a way that a device that does not (or only partially) supports a local evaluation may simply return a subset or all of its configuration. These capabilities have been integrated into a network management tool called ValidMaker.     

Modeling and simulation of structural components in recursive closed-loop multibody systems

Passenger cars, transit buses, railroad vehicles, off-highway trucks, earth moving equipment and construction machinery contain structural and light-fabrications (SALF) components that are prone to excessive vibration due to rough terrains and work-cycle loads’ excitations. SALF components are typically modeled as flexible components in the multibody system allowing the analysts to predict elastic deformation and hence the stress levels under different loading conditions. Including SALF component in the multibody system typically generates closed-kinematic loops. This paper presents an approach for integrating SALF modeling capabilities as a flexible body in a general-purpose multibody dynamics solver that is based on joint-coordinates formulation with the ability to handle closed-kinematic loops. The spatial algebra notation is employed in deriving the spatial multibody dynamics equations of motion. The system kinematic topology matrix is used to project the Cartesian quantities into the joint subspace, leading to a condensed set of nonlinear equations with minimum number of generalized coordinates. The proposed flexible body formulation utilizes the component mode synthesis approach to reduce the large number of finite element degrees of freedom to a small set of generalized modal coordinates. The resulting reduced flexible body model has two main characteristics: the stiffness matrix is constant while the mass matrix depends on the elastic modal coordinates. A consistent set of pre-computed inertia shape integrals are identified and used to update the modal mass matrix at each time step. The implementation of the component mode synthesis approach in a closed-loop recursive multibody formulation is presented. The kinematic equations are modified to include the effect of the flexible body modal elastic coordinates. Also, modified constraint equations that include the effect of flexibility at the joint connections and the necessary details of the Jacobian matrix are presented. Baumgarte stabilization approach is used to stabilize the constraint equations without using iterative schemes. A sample results for flexible body impeded in a closed system will be presented to demonstrate the above mentioned approach.     

An adaptive local binarization method for document images based on a novel thresholding method and dynamic windows

Binary image representation is essential format for document analysis. In general, different available binarization techniques are implemented for different types of binarization problems. The majority of binarization techniques are complex and are compounded from filters and existing operations. However, the few simple thresholding methods available cannot be applied to many binarization problems. In this paper, we propose a local binarization method based on a simple, novel thresholding method with dynamic and flexible windows. The proposed method is tested on selected samples called the DIBCO 2009 benchmark dataset using specialized evaluation techniques for binarization processes. To evaluate the performance of our proposed method, we compared it with the Niblack, Sauvola and NICK methods. The results of the experiments show that the proposed method adapts well to all types of binarization challenges, can deal with higher numbers of binarization problems and boosts the overall performance of the binarization.     

Power spectrum and Allan variance methods for calibrating single-molecule video-tracking instruments

Single-molecule manipulation instruments, such as optical traps and magnetic tweezers, frequently use video tracking to measure the position of a force-generating probe. The instruments are calibrated by comparing the measured probe motion to a model of Brownian motion in a harmonic potential well; the results of calibration are estimates of the probe drag, α, and spring constant, κ. Here, we present both time- and frequency-domain methods to accurately and precisely extract α and κ from the probe trajectory. In the frequency domain, we discuss methods to estimate the power spectral density (PSD) from data (including windowing and blocking), and we derive an analytical formula for the PSD which accounts both for aliasing and the filtering intrinsic to video tracking. In the time domain, we focus on the Allan variance (AV): we present a theoretical equation for the AV relevant to typical single-molecule setups and discuss the optimal manner for computing the AV from experimental data using octave-sampled overlapping bins. We show that, when using maximum-likelihood methods to fit to the data, both the PSD and AV approaches can extract α and κ in an unbiased and low-error manner, though the AV approach is simpler and more robust.