Electronics2014, 3(4), 689-711; doi:10.3390/electronics3040689 (registering DOI) - published 19 December 2014 Show/Hide Abstract
Abstract: In vehicular ad hoc networks (VANETs), besides the original applications typically related to traffic safety, we nowadays can observe an increasing trend toward infotainment applications, such as IPTV services. Quality of experience (QoE), as observed by the end users of IPTV, is highly important to guarantee adequate user acceptance for the service. In IPTV, QoE is mainly determined by the availability of TV channels for the users. This paper presents an efficient and rather generally applicable analytical model that allows one to predict the blocking probability of TV channels, both for channel-switching-induced, as well as for handover-induced blocking events. We present the successful validation of the model by means of simulation, and we introduce a new measure for QoE. Numerous case studies illustrate how the analytical model and our new QoE measure can be applied successfully for the dimensioning of IPTV systems, taking into account the QoE requirements of the IPTV service users in strongly diverse traffic scenarios.
Abstract: This paper considers a novel fusion rule for spectrum sensing scheme for a cognitive radio network with multi-antenna receivers. The proposed scheme exploits the fact that when any primary signal is present, measurements are spatially correlated due to presence of inter-antenna and inter-receiver spatial correlation. In order to exploit this spatial structure, the generalized likelihood ratio test (GLRT) operates with the determinant of the sample covariance matrix. Therefore, it depends on the sample size N and the dimensionality of the received data (i.e., the number of receivers K and antennas L). However, when the dimensionality fK; Lg is on the order, or larger than the sample size N, the GLRT degenerates due to the ill-conditioning of the sample covariance matrix. In order to circumvent this issue, we propose two techniques that exploit the inner spatial structure of the received observations by using single pair and multi-pairs Kronecker products. The performance of the proposed detectors is evaluated by means of numerical simulations, showing important advantages with respect to the traditional (i.e., unstructured) GLRT approach.
Abstract: Power consumption is the major constraint for modern microprocessor designs. In particular, static power consumption becomes a serious problem as the transistor size shrinks via semiconductor technology improvement. This paper proposes a technique that reduces the static power consumed by functional units. It exploits the activity rate of functional units and utilizes the power heterogeneous functional units. From detailed simulations, we investigate the conditions in which the proposed technique works effectively for simultaneous dynamic and static power reduction and find that we can reduce the total power by 11.2% if two out of four leaky functional units are replaced by leakless ones in the situation where the static power occupies half of the total power.
Abstract: In this paper, we propose a collision avoidance algorithm for multi-vehicle systems, which is a common problem in many areas, including navigation and robotics. In dynamic environments, vehicles may become involved in potential collisions with each other, particularly when the vehicle density is high and the direction of travel is unrestricted. Cooperatively planning vehicle movement can effectively reduce and fairly distribute the detour inconvenience before subsequently returning vehicles to their intended paths. We present a novel method of cooperative path planning for multi-vehicle systems based on reinforcement learning to address this problem as a decision process. A dynamic system is described as a multi-dimensional space formed by vectors as states to represent all participating vehicles’ position and orientation, whilst considering the kinematic constraints of the vehicles. Actions are defined for the system to transit from one state to another. In order to select appropriate actions whilst satisfying the constraints of path smoothness, constant speed and complying with a minimum distance between vehicles, an approximate value function is iteratively developed to indicate the desirability of every state-action pair from the continuous state space and action space. The proposed scheme comprises two phases. The convergence of the value function takes place in the former learning phase, and it is then used as a path planning guideline in the subsequent action phase. This paper summarizes the concept and methodologies used to implement this online cooperative collision avoidance algorithm and presents results and analysis regarding how this cooperative scheme improves upon two baseline schemes where vehicles make movement decisions independently.
Abstract: High-rate roll-to-roll (R2R) tracker systems are utilized for large volume flexible electronic device manufacturing, and the current alignment mechanism between layers is mainly achieved by relying on passive techniques. In this paper, we present a machine vision based alignment strategy that is used to achieve precise registration for stacking multilayers. Based on this strategy, we demonstrate two-layer printing with alignment accuracy better than 100 μm in web moving direction and 200 μm in lateral direction at a web rate of 5 m/min.
Abstract: Type 1 Diabetes Mellitus (T1DM) is an autoimmune disease in which the insulin-producing beta cells of the pancreas are destroyed and insulin must be injected daily to enable the body to metabolize glucose. Standard therapy for T1DM involves self-monitoring of blood glucose (SMBG) several times daily with a blood glucose meter and injecting insulin via a syringe, pen or insulin pump. An “Artificial Pancreas” (AP) is a closed-loop control system that uses a continuous glucose monitor (CGM), an insulin pump and an internal algorithm to automatically manage insulin infusion to keep the subject’s blood glucose within a desired range. Although no fully closed-loop AP systems are currently commercially available there are intense academic and commercial efforts to produce safe and effective AP systems. In this paper we present the Diabetes Assistant (DiAs), an ultraportable AP research platform designed to enable home studies of Closed Loop Control (CLC) of blood glucose in subjects with Type 1 Diabetes Mellitus. DiAs consists of an Android (Google Inc., Mountain View, CA, USA) smartphone equipped with communication, control and user interface software wirelessly connected to a continuous glucose monitor and insulin pump. The software consists of a network of mobile applications with well-defined Application Programming Interfaces (APIs) running atop an enhanced version of Android with non-essential elements removed. CLC and safety applications receive real-time data from the CGM and pump, estimate the patient’s metabolic state and risk of hypo- and hyperglycemia, adjust the insulin infusion rate, raise alarms as needed and transmit de-identified data to a secure remote server. Some applications may be replaced by researchers wishing to conduct outpatient ambulatory studies of novel Closed Loop Control, Safety or User Interface modules. Over the past three years the DiAs platform has been used in a series of AP clinical trials sponsored by the National Institutes of Health, the Juvenile Diabetes Research Foundation, the Helmsley Charitable Trust and the European Union AP@Home project. Results of clinical trials using DiAs indicate that a smartphone with targeted operating system modifications and appropriate system software can be successfully used in outpatient clinical trials of FDA Class III medical devices such as Artificial Pancreas.