Memory applications of a thiophene-based conjugated polymer by photoluminescence measurements

Data-storage and memory applications of conjugated polymers and organic semiconductors are generally probed by device current or dielectric properties to determine the storage and switching properties. In this article, we use photoluminescence as an alternate method of probing the states of the devices. We have fabricated such devices based on a polythiophene derivative, and recorded photoluminescence (PL) spectra during and after applying bias. The presence of localized charges on the backbone of the polymer has been found to modulate the PL intensity. Since the relaxation of the space charges is slow, we have shown that PL intensity can be used as a probe for memory applications to read the state of the device. PL as a probe for memory applications of polymeric materials offers an intrinsic advantage that the state can be read without affecting the device properties.     

Subspace filtering approach based on orthogonal projection for better analysis of stressed speech under clean and noisy environments

This study explores a novel subspace projection-based approach for analysis of stressed speech. Studies have shown that stress influences the speech production system and it results in a large acoustic variation between the neutral and the stressed speech. This degrades the discrimination capability of an automatic speech recognition system trained on neutral speech when tested on stressed speech. An effort is made to reduce the acoustic mismatch by explicitly normalizing the stress-specific attributes. The stress-specific divergences are normalized by exploiting the subspace filtering technique. To accomplish this, an orthogonal projection based linear relationship between the speech and the stress information has been explored to filter an effective speech subspace, which consists of speech information. Speech subspace is constructed using K-means clustering followed by singular value decomposition method using neutral speech data. The speech and the stress information are separated by projecting the stressed speech orthogonally onto an effective speech subspace. Experimental results indicate that, the bases of an effective subspace comprises the first few eigenvectors corresponding to the highest eigenvalues. To further improve the system performance, both the neutral and the stressed speech are projected onto the lower dimensional subspace. The projections derived using the neutral speech employs heteroscedastic linear discriminant analysis in maximum likelihood linear transformations-based semi-tied adaptation framework. Consistent improvements are noted for the proposed technique in all the discussed cases.     

Proposal of a statistical test rule induction method by use of the decision table

Rough sets theory is widely used as a method for estimating and/or inducing the knowledge structure of if-then rules from various decision tables. This paper presents the results of a retest of rough set rule induction ability by the use of simulation data sets. The conventional method has two main problems: firstly the diversification of the estimated rules, and secondly the strong dependence of the estimated rules on the data set sampling from the population. We here propose a new rule induction method based on the view that the rules existing in their population cause partiality of the distribution of the decision attribute values. This partiality can be utilized to detect the rules by use of a statistical test. The proposed new method is applied to the simulation data sets. The results show the method is valid and has clear advantages, as it overcomes the above problems inherent in the conventional method.     

A new robust observer-based adaptive type-2 fuzzy control for a class of nonlinear systems

In this paper, a novel robust observer-based adaptive controller is presented using a proposed simplified type-2 fuzzy neural network (ST2FNN) and a new three dimensional type-2 membership function is presented. Proposed controller can be applied to the control of high-order nonlinear systems and adaptation of the consequent parameters and stability analysis are carried out using Lyapunov theorem. Moreover, a new adaptive compensator is presented to eliminate the effect of the external disturbance, unknown nonlinear functions approximation errors and sate estimation errors. In the proposed scheme, using the Lyapunov and Barbalat's theorem it is shown that the system is stable and the tracking error of the system converges to zero asymptotically. The proposed method is simulated on a flexible joint robot, two-link robot manipulator and inverted double pendulums system. Simulation results confirm that in contrast to other robust techniques, our proposed method is simple, give better performance in the presence of noise, external disturbance and uncertainties, and has less computational cost.     

A study of optimal viewing distance in a parallax barrier 3D display

The optimal viewing distance was proposed as a parameter for designing a parallax barrier 3D display. It can be designed based on simple geometric method and by considering the pitches of image display pixels and parallax barrier, or even including the aperture ratios of the image display pixels and parallax barrier. It can be analyzed by using ray tracing method. By considering the optical refraction index of the cover glass, the angular behavior of the system becomes more realistic; however, the geometric method is difficult to be used. We propose a revised method for estimating the view distance and angular behavior. In this paper, we have demonstrated a designated eye position (DEP) for each view and shown that multiple DEPs make a circular curve around the center of the display. We prove the new concept by comparing the optical ray tracing calculations and optical measurement.     

Generalizing the CHOKe flow protection

This paper proposes a simple and stateless active queue management (AQM) scheme, called geometric CHOKe (gCHOKe), to protect responsive flows from unresponsive ones. gCHOKe has its root in and is a generalization of the original CHOKe. It provides an additional power of protection, achieved by introducing an extra flow matching trial following each successful flow comparison of packets. The maximum number of comparisons permitted for an arrival can be controlled by a parameter called maxcomp. The quality of flow protection improves with maxcomp. Compared to the plain CHOKe (which is just the simplest case of gCHOKe), our analysis and simulations show that the scheme can achieve over 20% improvement in the bounds of both bandwidth and buffer space used by an aggressive flow. In addition, up to 14% of the total link capacity can be saved from the unresponsive flow, allowing responsive or rate-adaptive flows to obtain a better share of resources in the router.     

MC-MLAS: Multi-channel Minimum Latency Aggregation Scheduling in Wireless Sensor Networks

Data aggregation is a key, yet time-consuming functionality in wireless sensor networks (WSNs). Multi-channel design is a promising technique to alleviate interference as a primary reason for long latency of TDMA aggregation scheduling. Indeed, it provides more potential of parallel transmissions over different frequency channels, thus minimizing time latency. In this paper, we focus on designing a multi-channel minimum latency aggregation scheduling protocol, named MC-MLAS, using a new joint approach for tree construction, channel assignment, and transmission scheduling. To our best knowledge, this is the first work in the literature which combines orthogonal channels and partially overlapping channels to consider the total latency involved in data aggregation. Extensive simulations verify the superiority of MC-MLAS in WSNs.