User utility discovery for priority-based network resource pricing

While equilibrium analysis has been commonly used for network pricing under the assumption that user utility functions are precisely known, many researchers have criticized the validity of the assumption. In this paper, we propose a solution for bridging the gap between the existing theoretical work on optimal pricing and the unavailability of precise user utility information in real networks. In the proposed method, the service provider obtains increasingly more accurate estimates of user utility functions by iteratively changing the prices of service levels and observing the users’ service-level choices under various prices. Our study’s contribution is twofold. First, we have developed a general principle for estimating user utility functions. Especially, we present the utility estimation for dynamic user population. Second, we have developed a method for setting prices that can optimize the extraction of information about user utility functions. The extensive simulation results demonstrate the effectiveness of our method.     

A fuzzy-based interleaved multi-hop authentication scheme in wireless sensor networks

In sensor networks, a compromised node can either generate fabricated reports with false votes or inject false votes into real reports, which causes severe damage such as false alarms, energy drain and information loss. An interleaved hop-by-hop authentication (IHA) scheme addresses the former attack by detecting and filtering false reports in a deterministic and hop-by-hop fashion. Unfortunately, in IHA, all en-route nodes must join to verify reports while only a few are necessary to the authentication procedure. In this paper, we propose a fuzzy-based interleaved multi-hop authentication scheme based on IHA. In our scheme, the fuzzy logic system only selects some nodes for verification based on the network characteristics. Moreover, we apply a voting method and a hash-based key assignment mechanism to improve network security. Through performance evaluation, the proposed scheme is found to save up to 13% of the energy consumption and to provide more network protection compared to IHA.     

A local experts organization model with application to face emotion recognition

This paper presents a novel approach for recognizing human facial emotion in order to further detect human suspicious behaviors. Instead of relying on relative poor representation of facial features in a flat vector form, the approach utilizes a format of tree structures with Gabor feature representations to present a facial emotional state. The novel local experts organization (LEO) model is proposed for the processing of this tree structure representation. The motivation for the LEO model is to deal with the inconsistent length of features in case there are some features failed to be detected. The proposed LEO model is inspired by the natural hierarchical model presented in natural organization, where workers (local experts) reports to their supervisor (fusion classifier), whom in turn reports to upper management (global fusion classifier). Moreover, an Asian emotion database is created. The database contains high-resolution images of 153 Asian subjects in six basic pseudo-emotions (excluding neutral expression) in three different poses for evaluating our proposed system. Empirical studies were conducted to benchmark our approach with other well-known classifiers applying to the system, and the results showed that our approach is the most robust, and less affected by noise from feature locators for the face emotion recognition system.     

On-chip whole blood plasma separator based on microfiltration,sedimentation and wetting contrast

Miniaturized on-chip blood separators have a great value for point-of-care diagnosis. In our work, a combined design strategy—microfiltration, sedimentation in a retarded flow, and wetting contrast—was taken to overcome the known limitations of on-chip blood separators. Our microfluidic chip consists of a polydimethylsiloxane micropillar array and an etched glass with microchannel branches. The red blood cells are significantly slowed and gradually settled down due to micropillars and enlarged dimension of a chamber. An etched glass microchannel allows the extraction of blood plasma exclusively due to the capillary effect. The fabricated microfluidic device can separate blood plasma from a whole blood sample without any external driving force or dilution. The measured plasma separation efficiency was close to 100 % from human whole blood. Autonomous on-chip separation and collection of blood plasma was demonstrated.     

Design and implementation of a same-user identification system in invoked reality space

The objective of this study is to solve the problem of user data not being precisely received from sensors because of sensing region limitations in invoked reality (IR) space, distortion of colors or patterns by lighting, and blocking or overlapping of a user by other users. The sensing scope range is thus expanded using multiple sensors in the IR space. Moreover, user feature data are accurately identified by user sensing. Specifically, multiple sensors are employed when not all of user data are sensed because they overlap with data of other users. In the proposed approach, all clients share the user feature data from multiple sensors. Accordingly, each client recognizes that the user is the same individual on the basis of the shared data. Furthermore, the identification accuracy is improved by identifying the user features based on colors and patterns that are less affected by lighting. Therefore, accurate identification of the user feature data is enabled, even under lighting changes. The proposed system was implemented based on system performance analysis standards. The practicality and system performance in identifying the same person using the proposed method were verified through an experiment.     

Team THOR's Entry in the DARPA Robotics Challenge Finals 2015

This paper describes Team THOR's approach to human‐in‐the‐loop disaster response robotics for the 2015 DARPA Robotics Challenge (DRC) Finals. Under the duress of unpredictable networking and terrain, fluid operator interactions and dynamic disturbance rejection become major concerns for effective teleoperation. We present a humanoid robot designed to effectively traverse a disaster environment while allowing for a wide range of manipulation abilities. To complement the robot hardware, a hierarchical software foundation implements network strategies that provide real‐time feedback to an operator under restricted bandwidth using layered user interfaces. Our strategy for humanoid locomotion includes a backward‐facing knee configuration paired with specialized toe and heel lifting strategies that allow the robot to traverse difficult surfaces while rejecting external perturbations. With an upper body planner that encodes operator preferences, predictable motion plans are executed in unforeseen circumstances. These plans are critical for manipulation in unknown environments. Our approach was validated during the DRC Finals competition, where Team THOR scored three points in 18 min of operation time, and the results are presented along with an analysis of each task.     

B-plane targeting method for orbit maneuver using low thrust

International Journal of Control, Automation and Systems - In this research, a new control law for the trajectory correction maneuver (TCM) is proposed for a spacecraft assumed to be actuated by a...     

A new fair scheduling algorithm for periodic tasks on multiprocessors

We present a new scheduling algorithm, called PL that is work-conserving and in terms of schedulability, optimal on multiprocessors for a synchronous periodic task set. The PL algorithm is a laxity based algorithm and ensures execution of a task with approximate proportional fairness at each task's period. Existing optimal algorithms on multiprocessors may cause excessive scheduling decisions and preemptions or may not be applied in a discrete environment. The proposed algorithm can be applied in a discrete environment and reduce the number of scheduling decisions and preemptions compared with a Pfair algorithm.