Finance and the technology-trade nexus

This paper sketches the contours of the evolving international/monetary system and examines the various roles of the intemediation mechanisms. Then it examines the extent to which the financial system is independent from the “real economy” and the various ways in which it impacts it. The paper discusses some views in good currency on the dynamics of the technology-trade-finance nexus and shows how the financial system influences organization, location and technology choices in meso-innovation systems. The final section of the paper looks at the policy implications that might be derived from the analysis and suggests some directions for the future research.     

Speech driven photo realistic facial animation based on an articulatory DBN model and AAM features

This paper presents a photo realistic facial animation synthesis approach based on an audio visual articulatory dynamic Bayesian network model (AF_AVDBN), in which the maximum asynchronies between the articulatory features, such as lips, tongue and glottis/velum, can be controlled. Perceptual Linear Prediction (PLP) features from audio speech, as well as active appearance model (AAM) features from face images of an audio visual continuous speech database, are adopted to train the AF_AVDBN model parameters. Based on the trained model, given an input audio speech, the optimal AAM visual features are estimated via a maximum likelihood estimation (MLE) criterion, which are then used to construct face images for the animation. In our experiments, facial animations are synthesized for 20 continuous audio speech sentences, using the proposed AF_AVDBN model, as well as the state-of-art methods, being the audio visual state synchronous DBN model (SS_DBN) implementing a multi-stream Hidden Markov Model, and the state asynchronous DBN model (SA_DBN). Objective evaluations on the learned AAM features show that much more accurate visual features can be learned from the AF_AVDBN model. Subjective evaluations show that the synthesized facial animations using AF_AVDBN are better than those using the state based SA_DBN and SS_DBN models, in the overall naturalness and matching accuracy of the mouth movements to the speech content.     

Fuzzy clustering with learnable cluster-dependent kernels

We propose a new relational clustering approach, called Fuzzy clustering with Learnable Cluster-dependent Kernels (FLeCK), that learns the underlying cluster-dependent dissimilarity measure while seeking compact clusters. The learned dissimilarity is based on a Gaussian kernel function with cluster-dependent parameters. Each cluster’s parameter learned by FLeCK reflects the relative intra-cluster and inter-cluster characteristics. These parameters are learned by optimizing both the intra-cluster and the inter-cluster distances. This optimization is achieved iteratively by dynamically updating the partition and the local kernel. This makes the kernel learning task takes advantages of the available unlabeled data and reciprocally, the categorization task takes advantages of the learned local kernels. Another key advantage of FLeCK is that it is formulated to work on relational data. This makes it applicable to data where objects cannot be represented by vectors or when clusters of similar objects cannot be represented efficiently by a single prototype. Using synthetic and real data sets, we show that FLeCK learns meaningful parameters and outperforms several other algorithms. In particular, we show that when data include clusters with various inter- and intra-cluster distances, learning cluster-dependent parameters is crucial in obtaining a good partition.     

Multi-mode of vortex-induced vibration of a flexible circular cylinder

The vortex-induced vibration of a flexible circular cylinder is investigated at a constant Reynolds number of 1 000.The finite-volume method on moving meshes is applied for the fluid flow, and the Euler-Bernoulli beam theory is used to model the dynamic response of a flexible cylinder.The relationship between the reduced velocity and the amplitude response agrees well with the experimental results.Moreover, five different vibrating modes appear in the simulation.From the comparisons of their vortex structures, the strength of the wake flow is related to the exciting vibrating mode and different vortex patterns arise for different vibrating modes.Only 2P pattern appears in the first vibrating mode while 2S-2P patterns occur in the other vibrating modes if monitoring at different sections along the length of the cylinder.The vibration of the flexible cylinder can also greatly alter the three-dimensionality in the wake, which needs further studies in our future work, especially in the transition region for the Reynolds number from 170 to 300.     

Local feature selection for multiple instance learning

Journal of Intelligent Information Systems - We propose a local feature selection method for the Multiple Instance Learning (MIL) framework. Unlike conventional feature selection algorithms that...     

A nonlinear geometric approach to power system excitation control and stabilization

In this paper, a unified approach to the design of a nonlinear excitation controller/power system stabilizer for a synchronous generator/infinite bus power system is presented. The approach is based on a form of state feedback linearization, known as input–output feedback linearization, which provides an exact semi-global state transformation that is valid for a large class of operating points of the power system. With this transformation, the terminal voltage becomes a linear function of the control input. The excitation controller/power system stabilizer is then synthesized by using linear controller design techniques. The controller is proven to provide small signal stability and to provide local asymptotic tracking of admissible constant reference signals for a large class of operating points. A procedure is given to tune the controller gains to provide significant damping of the power angle oscillations.     

Engineering TCP transmission and retransmission mechanisms for wireless networks

Transmission Control Protocol (TCP) provides mechanisms for reliable data communications. Although it works well in wired networks, it fails to offer satisfactory performance in lossy and wireless environments. And in the multi-hop wireless infrastructure, packet delivery suffers high cumulative loss rate if traveling over multiple wireless hops. The Selective acknowledgment (SACK) is one header option that might be used to combat segment corruptions in air channels. In this paper, an alternative set of flow control mechanisms is proposed to handle high packet loss rate in a wireless medium. Using a measurement-based mechanism, sustainable segment delivery is achievable through a novel size-reduction method. Multiple segment retransmission mechanisms are introduced to reduce successive timeout events. One single byte loss is sufficient to waste all other bytes in a file received at a destination. That is, a good TCP flow control mechanism should provide a high successful file transmission completion rate, and this is set as our design goal. Through thorough simulations, our proposed multi-segment retransmission designs perform with higher successful file transfer rate and fewer timeout events than NewReno and SACK under a wide range of packet loss probabilities.     

Why Teachers Must Learn: Student Innovation as a Driving Factor in the Future of the Web

User innovation is the key to the development and vitality of technology. As Huatong Sun wrote, “expanding the scope of localization practices and linking user localization efforts” to design cycles—including pedagogical design—will help bridge the gap between what teachers/designers create and what skills users/students need and want. This article theorizes the role of modern composition students and teachers as co-constructors of productive spaces for learning critical inquiry based on students’ statuses as digital natives. It focuses on a class of first-year composition students who reshaped an assignment to fit their own needs within the physical classroom and also enacted a shift to a virtual classroom. While doing so, they provided ways for each class member to individualize space within that digital environment, and they focused their project on examining the ways in which social networking forums colonize their daily lives. This article argues that by letting student innovation drive pedagogical practice—just as social media creators let user innovation drive the digital structures they produce—composition teachers can be assured of having a text for critique that blurs the lines between “private” student underlife and “public” classroom practice and legitimizes the creation of student-produced learning spaces. Using critical and cyberfeminist theories as lenses, this article draws conclusions about the future of computer usage in composition pedagogy based on students’ abilities to re-appropriate physical and digital classroom space.     

Distributed model predictive control of dynamically decoupled systems with coupled cost

This paper considers the distributed model predictive control (DMPC) of systems with interacting subsystems having decoupled dynamics and constraints but coupled costs. An easily-verifiable constraint is introduced to ensure asymptotic stability of the overall system in the absence of disturbance. The constraint introduced has a parameter which allows for the performance of the DMPC system to approach that controlled by a centralized model predictive controller. When the subsystems are linear and additive disturbance is present, the added constraint ensures the state of each subsystem converges to its respective minimal disturbance invariant set. The approach is demonstrated via several numerical examples.