An inexact hybrid projection-proximal point algorithm for solving generalized mixed variational inequalities

In this paper, we investigate an inexact hybrid projection-proximal method for solving a class of generalized mixed variational inequalities in Hilbert spaces. We construct a general inexact hybrid projection-proximal point algorithm, in which an inexact relaxed proximal point step is followed by a suitable orthogonal projection onto a hyperplane. Under some suitable conditions concerned with the pseudomonotone set-valued mapping T, the nonsmooth convex function f and the step size λ_k, we prove the convergence of the inexact hybrid projection-proximal point algorithm for solving generalized mixed variational inequalities in Hilbert spaces.     

Decision support system based on hierarchical co-evolutionary fuzzy approach: A case study in detecting gamma ray signals

Decision support systems are powerful technologies for complex decision making and problem solving. However, constructing an accurate and interpretable decision support system (DSS) for any domain is a challenge. In this paper, a novel hierarchical co-evolutionary fuzzy system called HiCEFS is presented that can autonomously derive a fuzzy rule-based DSS from exemplar data. Most of the important components in HiCEFS, including irregular shaped membership functions (ISMFs) and fuzzy rules, are generated using a hierarchical co-evolutionary genetic algorithm that simultaneously co-evolves these components in separate genetic populations. Owing to its generic learning capability, the HiCEFS approach can be easily applied to produce DSSs for classification and regression tasks in various domains. As a case study, HiCEFS is employed to construct a DSS for detecting gamma ray signals. Experimental results show that the system is able to successfully discern the gamma rays from background hadrons, and performs superior to other established techniques.     

A computer-enabled solution procedure for food wholesalers’ distribution decision in cities with a circular transportation infrastructure

This paper addresses the food distribution decision from a wholesaler's perspective, as the wholesalers are often faced with thorny issues such as when, where, how to deliver products at the lowest costs to best satisfy the retailers’ changing needs. This research relies on a distribution problem encountered at Northern Grocery Company in Beijing as an example to develop a two-stage solution procedure and subsequent computer-enabled programs for identifying efficient vehicle routing alternatives. The solution process, which integrates heuristic search algorithms and an integer programming model, can be applied to a wide range of distribution problems with specified route durations and a circular transportation network structure as exemplified by City of Beijing.     

Multi-sensor calibration through iterative registration and fusion

In this paper, a new multi-sensor calibration approach, called iterative registration and fusion (IRF), is presented. The key idea of this approach is to use surfaces reconstructed from multiple point clouds to enhance the registration accuracy and robustness. It calibrates the relative position and orientation of the spatial coordinate systems among multiple sensors by iteratively registering the discrete 3D sensor data against an evolving reconstructed B-spline surface, which results from the Kalman filter-based multi-sensor data fusion. Upon each registration, the sensor data gets closer to the surface. Upon fusing the newly registered sensor data with the surface, the updated surface represents the sensor data more accurately. We prove that such an iterative registration and fusion process is guaranteed to converge. We further demonstrate in experiments that the IRF can result in more accurate and more stable calibration than many classical point cloud registration methods.     

A controllable and accountable state-oriented Card-Aided Firewall

This paper proposes a new approach, named Card-Aided Firewall (CAF) that combines the simplified firewall and the state-oriented smart card technologies to construct a controllable and accountable Internet access framework. The idea suggests that a client computer, protected by a light-weight firewall, could establish diversified authenticated communication channels, controlled and accounted by “legal” states of the smart card.The program of a smart card is state-oriented or a state machine, which defines a chain of events involving various state transitions. The “legal” states of a smart card program are defined to be legal to communicate with surfing targets. A predefined Access Control List (ACL), stored in the same card, is necessary. An ACL is a sequential list of permit or deny statements that apply to addresses or upper-layer protocols. The proposed firewall decides acceptance or rejection messages by matching the current state of the card program and the ACL. In addition, a complete surfing account for tracing back is recorded. It is a by-product of the smart card authentication.The proposed Card-Aided Firewall framework is implemented to demonstrate its effectiveness. The implementation is done at the driver level. It keeps up with the high line speed. The driver takes 39K bytes and works well with other firewalls. The average packet processing time of the CAF driver is 31.74 μs. On the premise of secure authentication within the smart card, the Card-Aided Firewall would facilitate various rapidly growing applications in campus cards, family cards, and employee cards, etc. that require accurate controllability and accountability in the surfing boundary.     

A system-level model for a silicon thermal flow sensor

A system-level model with lumped parameters for a thermal flow sensor is presented. The model is built with 13 circuit cells consisting of thermal resistors and thermal capacitors in SPICE. The circuit cell originates from the heat conduction equation using the Finite Differential Method, including the 2-D thermal conduction cell, the convection cell, and the thermal capacity in the chip. Based on the thermal model of the flow sensor, the 2-D temperature distribution of the chip can be calculated with SPICE in both the constant power mode (CP) and constant temperature difference mode (CTD). As an example, the system level model of the thermal anemometer in the CTD mode was established in PSPICE. Wind tunnel test was carried out to verify the system model, and show a reasonable agreement with the simulation results, with an error less than 8%.     

Agent long-term coalition credit

Agent trust researches become more and more important because they will ensure good interactions among the software agents in large-scale open systems. Moreover, individual agents often interact with long-term coalitions such as some E-commerce web sites. So the agents should choose a coalition based on utility and trust. Unfortunately, few studies have been done on agent coalition credit and there is a need to do it in detail. To this end, a long-term coalition credit model (LCCM) is presented. Furthermore, the relationship between coalition credit and coalition payoff is also attended. LCCM consists of internal trust based on agent direct interactions and external reputation based on agent direct observation. Generalization of LCCM can be demonstrated through experiments applied in both cooperative and competitive domain environment. Experimental results show that LCCM is capable of coalition credit computation efficiently and can properly reflect various factors effect on coalition credit. Another important advantage that is a useful and basic property of credit is that LCCM can effectively filter inaccurate or lying information among interactions.     

Designing an exergaming system for exercise bikes using kinect sensors and Google Earth

This paper proposes an Exergaming system for exercise bikes. With the assistance of a Kinect device and the proposed body-movement-detection algorithm, exercise bike users are required to perform correct neck and shoulder movements to control the airplane trajectory in Google Earth. They can take a flying tour in the virtual reality provided by Google Earth while riding an exercise bike. According to the experimental results, 95 % of the users in the experiment considered the proposed Exergaming system to be very entertaining; more than 85 % of the users affirmed that the assigned neck and shoulder movements effectively help stretch the muscles in these body parts; the detection rate of the proposed body-movement algorithm was over 90 %. Therefore, the proposed Exergaming system is a good assisting system for exercise bikes.