ADMM-based Adaptive Sampling Strategy for Nonholonomic Mobile Robotic Sensor Networks

This paper discusses the adaptive sampling problem in a nonholonomic mobile robotic sensor network for efficiently monitoring a spatial field. It is proposed to employ Gaussian process to model a spatial phenomenon and predict it at unmeasured positions, which enables the sampling optimization problem to be formulated by the use of the log determinant of a predicted covariance matrix at next sampling locations. The control, movement and nonholonomic dynamics constraints of the mobile sensors are also considered in the adaptive sampling optimization problem. In order to tackle the nonlinearity and nonconvexity of the objective function in the optimization problem we first exploit the linearized alternating direction method of multipliers (L-ADMM) method that can effectively simplify the objective function, though it is computationally expensive since a nonconvex problem needs to be solved exactly in each iteration. We then propose a novel approach called the successive convexified ADMM (SC-ADMM) that sequentially convexify the nonlinear dynamic constraints so that the original optimization problem can be split into convex subproblems. It is noted that both the L-ADMM algorithm and our SC-ADMM approach can solve the sampling optimization problem in either a centralized or a distributed manner. We validated the proposed approaches in 1000 experiments in a synthetic environment with a real-world dataset, where the obtained results suggest that both the L-ADMM and SC- ADMM techniques can provide good accuracy for the monitoring purpose. However, our proposed SC-ADMM approach computationally outperforms the L-ADMM counterpart, demonstrating its better practicality.Comment: submitted to IEEE Sensors Journal, revised versio

Platform-Specific Timing Verification Framework in Model-Based Implementation

In the model-based implementation methodology, the timed behavior of the software is typically modeled independently of the platform-specific timing semantics such as the delay due to scheduling or I/O handling. Although this approach helps to reduce the complexity of the model, it leads to timing gaps between the model and its implementation. This paper proposes a platform-specific timing verification framework that can be used to formally verify the timed behavior of an implementation that has been developed from a platform-independent model. We first describe a way to categorize the interactions among the software, a platform, and the environment in the form of implementation schemes. We then present an algorithm that systematically transforms a platform-independent model into a platform-specific model under a given implementation scheme. This transformation algorithm ensures that the timed behavior of the platform-specific model is close to that of the corresponding implementation. Our case study of an infusion pump system shows that the measured timing delay of the system is bounded by the formally verified bound of its platform-specific model

Business process improvement for sustainable technologies investments in construction: A configurational approach

Given the importance of investments in business process improvements for sustainable technologies, many industry sectors are forced to examine and balance new investments with long-term economic viability. There are disputes with regard to the value of investments, particularly within the construction sector, which is characterized by poor capitalization, over-leveraged firms, and high risks, often coupled with business cycles or boom and bust periods. Understanding when construction firms should engage in business process improvements with sustainable technologies is not clear due to the risks and investment costs. To address this problem, the study takes a configurational approach to examine the factors of leverage and use of capital to examine their impact on firm performance with qualitative comparative analysis (QCA). We show distinct configurational outcomes that are associated with superior success, giving construction firms viable pathways to evaluate potential investments in sustainable technologies. Specifically, one configuration, focusing on incremental innovations, consistently produces positive firm performance. Two configurations that lead to the absence of performance are associated with radical innovations in firms that struggle to manage their working capital

Transport On-Demand in a Service Supply Chain Experiencing Seasonal Demand: Managing Persistent Backlogs

Successful transport-on-demand (TOD) requires having sufficient capacity in the right location to meet demand when it occurs. Consumer and recovery vehicle locations are variable, and the vehicle recovery service is contracted out in the service supply chain. This research aims to identify how different variables/factors influence backlogs during busy periods and service performance. A case study of a vehicle recovery company was undertaken using observation and analysis of historical data to map the process. Discrete event simulation (DES) was used to model several processes to evaluate the operational impact of changes. We find that ensuring complete and accurate information transmission over the chain supports the TOD service by enhancing the ‘allocation’ activity of the dispatch center staff; i.e., pairing vehicles to consumer requirements. Simple changes to how information is collected, shared, and used in the service supply chain can significantly reduce the percentage of jobs taking more than a given time

Chiral nematic self-assembly of minimally surface damaged chitin nanofibrils and its load bearing functions

Chitin is one of the most abundant biomaterials in nature, with 1010 tons produced annually as hierarchically organized nanofibril fillers to reinforce the exoskeletons of arthropods. This green and cheap biomaterial has attracted great attention due to its potential application to reinforce biomedical materials. Despite that, its practical use is limited since the extraction of chitin nanofibrils requires surface modification involving harsh chemical treatments, leading to difficulties in reproducing their natural prototypal hierarchical structure, i.e. chiral nematic phase. Here, we develop a chemical etching-free approach using calcium ions, called "natural way", to disintegrate the chitin nanofibrils while keeping the essential moiety for the self-assembly, ultimately resulting in the reproduction of chitin's natural chiral structure in a polymeric matrix. This chiral chitin nanostructure exceptionally toughens the composite. Our resultant chiral nematic phase of chitin materials can contribute to the understanding and use of the reinforcing strategy in nature.open119sciescopu

A Compact Dual Bandpass Filter Using Dual Composite Right-/Left-Handed and Open-Loop Ring Resonators for 4G and 5G Applications

In this paper a very compact design of a dual-band band pass filter (D-BPF) using dual composite right-/left-handed (D-CRLH) and open-loop ring (OLR) resonators is presented. To overcome the frequency ratio limitations of D-CLRH resonators technique, the D-BPF design combines D-CRLH and OLR resonators to finally perform a D-BPF. The filter covers the 2.6 and 3.5 GHz spectrums for 4G and 5G applications, respectively. The reported D-BPF is designed and optimized using ADS software, and is implemented on a Rogers RO5880 substrate with a relative dielectric constant of 2.2 and thickness of 0.787 mm. The overall compact size is 8×8×0.787 mm^3. To our knowledge, this design is considered as the most compact and smallest size dual-bandpass filters