Context-sensitive dependency pairs

Termination is one of the most interesting problems when dealing with context-sensitive rewrite systems. Although a good number of techniques for proving termination of context-sensitive rewriting (CSR) have been proposed so far, the adaptation to CSR of the dependency pair approach, one of the most powerful techniques for proving termination of rewriting, took some time and was possible only after introducing some new notions like collapsing dependency pairs, which are specific for CSR. In this paper, we develop the notion of context-sensitive dependency pair (CSDP) and show how to use CSDPs in proofs of termination of CSR. The implementation and practical use of the developed techniques yield a novel and powerful framework which improves the current state-of-the-art of methods for automatically proving termination of CSR.     

Spoken emotion recognition through optimum-path forest classification using glottal features

A new method for the recognition of spoken emotions is presented based on features of the glottal airflow signal. Its effectiveness is tested on the new optimum path classifier (OPF) as well as on six other previously established classification methods that included the Gaussian mixture model (GMM), support vector machine (SVM), artificial neural networks – multi layer perceptron (ANN-MLP), k-nearest neighbor rule (k-NN), Bayesian classifier (BC) and the C4.5 decision tree. The speech database used in this work was collected in an anechoic environment with ten speakers (5 M and 5 F) each speaking ten sentences in four different emotions: Happy, Angry, Sad, and Neutral. The glottal waveform was extracted from fluent speech via inverse filtering. The investigated features included the glottal symmetry and MFCC vectors of various lengths both for the glottal and the corresponding speech signal. Experimental results indicate that best performance is obtained for the glottal-only features with SVM and OPF generally providing the highest recognition rates, while for GMM or the combination of glottal and speech features performance was relatively inferior. For this text dependent, multi speaker task the top performing classifiers achieved perfect recognition rates for the case of 6th order glottal MFCCs.     

Shrinking‐horizon dynamic programming

We describe a heuristic control policy for a general finite‐horizon stochastic control problem, which can be used when the current process disturbance is not conditionally independent of the previous disturbances, given the current state. At each time step, we approximate the distribution of future disturbances (conditioned on what has been observed) by a product distribution with the same marginals. We then carry out dynamic programming (DP), using this modified future disturbance distribution, to find an optimal policy, and in particular, the optimal current action. We then execute only the optimal current action. At the next step, we update the conditional distribution, and repeat the process, this time with a horizon reduced by one step. (This explains the name ‘shrinking‐horizon dynamic programming’). We explain how the method can be thought of as an extension of model predictive control, and illustrate our method on two variations on a revenue management problem. Copyright © 2010 John Wiley & Sons, Ltd.     

Active time scheduling for rechargeable sensor networks

Recent progress in energy harvesting technologies made it possible to build sensor networks with rechargeable nodes which target an indefinitely long operation. In these networks, the goal of energy management is to allocate the available energy such that the important performance metrics, such as the number of detected threats, are maximized. As the harvested energy is not sufficient for continuous operation, the scheduling of the active and inactive time is one of the main components of energy management. The active time scheduling protocols need to maintain the energy equilibrium of the nodes, while considering the uncertainties of the energy income, which is strongly influenced by the weather, and the energy expenditures, which are dependent on the behavior of the targets. In this paper, we describe and experimentally compare three active time scheduling protocols: (a) static active time, (b) dynamic active time based on a multi-parameter heuristic and (c) utility-based uniform sensing. We show that protocols which take into consideration the probabilistic models of the energy income and expenditure and can dynamically adapt to changes in the environment, can provide a significant performance advantage.     

Vehicle license plate tilt correction based on the straight line fitting method and minimizing variance of coordinates of projection points

Tilt correction is a very crucial and inevitable task in the automatic recognition of the vehicle license plate (VLP). In this paper, according to the least square fitting with perpendicular offsets (LSFPO), the VLP region is fitted to a straight line. After the line slope is obtained, rotation angle of the VLP is estimated. Then the whole image is rotated for tilt correction in horizontal direction by this angle. Tilt correction in vertical direction by minimizing the variance of coordinates of the projection points is proposed. Character segmentation is performed after horizontal correction and character points are projected along the vertical direction after shear transform. Despite the success of VLP detection approaches in the past decades, a few of them can effectively locate license plate (LP), even when vehicle bodies and LPs have similar color. A common drawback of color-based VLP detection is the failure to detect the boundaries or border of LPs. In this paper, we propose a modified recursive labeling algorithm for solving this problem and detecting candidate regions. According to different colored LP, these candidate regions may include LP regions. Geometrical properties of the LP such as area, bounding box and aspect-ratio are then used for classification. Various LP images were used with a variety of conditions to test the proposed method and results are presented to prove its effectiveness.     

An integrated case-based reasoning and MCDM system for Web based tourism destination planning

The accelerating interaction between technology and tourism has changed radically the efficiency and effectiveness of tourism organizations, as well as how consumers interact with organizations. In this study, a Web based intelligent framework for travel agencies is proposed that offers customers a fast and reliable response service in a less costly manner. The proposed framework integrates case-based reasoning (CBR) system with a well-known multi criteria decision making (MCDM) technique, namely Analytic Hierarchy Process, to enhance the accuracy and speed in case matching in tourism destination planning. The integration of two techniques enables taking advantages of their strengths and complements each other’s weaknesses. A case study is performed to demonstrate how this framework can facilitate intelligent decision support by retrieving best-fitted responses for customers.     

Designing a sustainable supply chain using an integrated analytic network process and goal programming approach in quality function deployment

Sustainable supply chain management (SSCM) provides economic, social end environmental requirements in material and service flows occurring between suppliers, manufacturers and customers. SSCM structure is considered as a prerequisite for a sustainable success. Thus designing an effective SCM structure provides competitive advantages for the companies. In order to achieve an effective design of this structure, it is possible to apply quality function deployment (QFD) approach which is successfully applied as an effective product and system development tool. This study presents a decision framework where analytic network process (ANP) integrated QFD and zero-one goal programming (ZOGP) models are used in order to determine the design requirements which are more effective in achieving a sustainable supply chain (SSC). The first phase of the QFD is the house of quality (HOQ) which transforms customer requirements into product design requirements. In this study, after determining the sustainability requirements named customer requirements (CRs) and design requirements (DRs) of a SSC, ANP is employed to determine the importance levels in the HOQ considering the interrelationships among the DRs and CRs. Furthermore ZOGP approach is used to take into account different objectives of the problem. The proposed method is applied through a case study and obtained results are discussed.     

An interactive whiteboard student survey: Development,validity and reliability

The interactive whiteboard (IWB) has become a popular technology for instructors over the last decade. Though research asserts that the IWBs facilitate learning in different ways, there is a lack of studies examining actual IWB use in classroom settings based on learners’ perspectives by means of valid instruments. The purpose of this study is to develop a valid and reliable interactive whiteboard student survey in order to evaluate the IWB use based on perceptions of students who have been taught with IWBs. In establishing the theoretical base of the survey, the Technology Acceptance Model (TAM) and constructivist learning theories were considered. In addition, with respect to IWB use in classrooms, a number of studies emanated from countries such as the UK, the USA, and Australia were examined, and similar research questionnaires and findings and also reflections of students about IWBs were utilized to create an item pool. A 39-item survey was conducted among middle school students (N = 263) from the city of Istanbul in Turkey. Collected data was exposed to exploratory factor analysis and resulted in a 26-item, three-factor survey, whose factors were named as the perceived efficiency of IWB, perceived learning contribution and motivation, and the perceived negative effects of IWB. The results of the analyses illustrated that this new IWB student scale, which explains 50% of the total variance with a good level of Cronbach’s Alpha coefficient (0.93) is a valid and reliable instrument designed specifically for measuring the use of IWBs in real classroom settings. Besides, theoretical foundations of interactive whiteboard use, the development process of the instrument, and results of validity and reliability analyses were discussed in detail.     

New Compliance-Mechanism Design for Small Companion Robots

The compliance mechanisms used on robotic arms can be classified into two major categories: mechanical and electronic. The ideal characteristics of a compliance mechanism include small volume, simple mechanical structure, low cost, large complaint range, and high precision and accuracy under displacement control. Most mechanical compliance mechanisms are able to meet the first three conditions but have a small compliant range and low precision and accuracy under displacement control. The electronic compliance mechanism is hardly limited in the degree of deformation and comes with a higher precision and accuracy under the displacement control, but its sensors are expensive and the system is difficult to control. To combine the advantages of both types, this research aims to develop a new design of compliance mechanism in which a small-scale torque-limiting mechanism with a self-locking feature is installed between the actuator and the arm structure to minimize the volume while providing an ample torque limit. When the robotic arm is overloaded under an external force, a slide will occur inside the compliance mechanism so that the robotic arm will move along the direction of the external force to avoid damage. The robotic arm will automatically return to its original position after the external force is removed. The new compliance mechanism not only exceeds most of the current mechanical designs in the range of compliance but also does not affect the precision and accuracy of the displacement control. Furthermore, the new compliance mechanism does not require any sensors, which will benefit small robotic arms.     

Autonomous motion planning of a hand-arm robotic system based on captured human-like hand postures

The paper deals with the problem of motion planning of anthropomorphic mechanical hands avoiding collisions and trying to mimic real human hand postures. The approach uses the concept of “principal motion directions” to reduce the dimension of the search space in order to obtain results with a compromise between motion optimality and planning complexity (time). Basically, the work includes the following phases: capturing the human hand workspace using a sensorized glove and mapping it to the mechanical hand workspace, reducing the space dimension by looking for the most relevant principal motion directions, and planning the hand movements using a probabilistic roadmap planner. The approach has been implemented for a four finger anthropomorphic mechanical hand (17 joints with 13 independent degrees of freedom) assembled on an industrial robot (6 independent degrees of freedom), and experimental examples are included to illustrate its validity.