A Routing-Based Repair Method for Digital Microfluidic Biochips Based on an Improved Dijkstra and Improved Particle Swarm Optimization Algorithm.
28 Nov 2020-Micromachines (Multidisciplinary Digital Publishing Institute)-Vol. 11, Iss: 12, pp 1052
TL;DR: The routing problem is identified as a dynamic path-planning problem and mixed path design problem under certain constraints, and an improved Dijkstra and improved particle swarm optimization (ID-IPSO) algorithm is proposed, which can accommodate more faulty electrodes for the same fault repair rate.
Abstract: Digital microfluidic biochips (DMFBs) are attractive instruments for obtaining modern molecular biology and chemical measurements. Due to the increasingly complex measurements carried out on a DMFB, such chips are more prone to failure. To compensate for the shortcomings of the module-based DMFB, this paper proposes a routing-based fault repair method. The routing-based synthesis methodology ensures a much higher chip utilization factor by removing the virtual modules on the chip, as well as removing the extra electrodes needed as guard cells. In this paper, the routing problem is identified as a dynamic path-planning problem and mixed path design problem under certain constraints, and an improved Dijkstra and improved particle swarm optimization (ID-IPSO) algorithm is proposed. By introducing a cost function into the Dijkstra algorithm, the path-planning problem under dynamic obstacles is solved, and the problem of mixed path design is solved by redefining the position and velocity vectors of the particle swarm optimization. The ID-IPSO routing-based fault repair method is applied to a multibody fluid detection experiment. The proposed design method has a stronger optimization ability than the greedy algorithm. The algorithm is applied to , , and fault-free chips. The proposed ID-IPSO routing-based chip design method saves 13.9%, 14.3%, and 14.5% of the experiment completion time compared with the greedy algorithm. Compared with a modular fault repair method based on the genetic algorithm, the ID-IPSO routing-based fault repair method has greater advantages and can save 39.3% of the completion time on average in the completion of complex experiments. When the ratio of faulty electrodes is less than 12% and 23%, the modular and ID-IPSO routing-based fault repair methods, respectively, can guarantee a 100% failure repair rate. The utilization rate of the electrodes is 18% higher than that of the modular method, and the average electrode usage time is 17%. Therefore, the ID-IPSO routing-based fault repair method can accommodate more faulty electrodes for the same fault repair rate; the experiment completion time is shorter, the average number of electrodes is lower, and the security performance is better.
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TL;DR: In this article , a multi-sensing four-wheel-drive Mecanum vehicle was built, which was equipped with UWB positioning, communication based on ESP8266 modules, ultrasonic ranging and a magnetic structure.
Abstract: The reconfigurable modular vehicle group can transform into different configurations according to different requirements to be competent for various tasks and scenarios and to facilitate the utilization of robots in unstructured scenarios. Efficient and effective reconfiguration strategies and path planning are essential for improving the performance of modular vehicle groups. First, a multi-sensing four-wheel-drive Mecanum vehicle was built, which was equipped with UWB positioning (based on wireless carrier communication technology), communication based on ESP8266 modules, ultrasonic ranging and a magnetic structure. Second, concerning the indoor storage environment, a UWB two-way bilateral ranging and positioning system was designed, and the experimental accuracy for positioning could reach ±0.1 m. Third, a path planning strategy based on the improved artificial potential field method was adopted. According to the target configuration as well as the obstacle avoidance requirements, the motion space was converted into a gravitational field and a repulsive force field, and the vector superposition of the gradients was used for the path planning of each vehicle in turn. Depending on the reconfiguration command and the connection matrix, the magnetic structure would strengthen or disconnect the vehicle group configuration. Finally, the vehicle reconfiguration from the stochastic dispersion state to the target configuration and the transition between different configurations were accomplished using the proposed strategy in both simulations and experiments.
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TL;DR: In this article, the authors proposed an improved whale optimization algorithm (IWOA), which can reduce the excessive use of an electrode and reuse electrodes in an average manner to optimize the longest lifetime of digital microfluidic biochips.
1 citations
TL;DR: In this paper , a routing-based synthesis method based on a digital microfluidic biochip (DMFB) platform is presented, which can ensure a much higher chip utilization factor by removing the virtual modules on the chip and the extra electrodes needed as guard cells.
Abstract: With the continuous application and development of the digital microfluidic technology in various fields, many researchers have studied the design of digital microfluidic chips. Module-based chip design methods greatly simplify the design process but waste resources, including through the inadequate use of electrodes within the module and guard cells. To address this problem, a routing-based synthesis method based on a digital microfluidic biochip (DMFB) platform is presented. Routing-based DMFBs ensure a much higher chip utilization factor by removing the virtual modules on the chip and the extra electrodes needed as guard cells. Many previous works focused only on the problems of synthesis completion times, bioassay completion times, and electrode utilization rates. However, the reliability of chips has not been fully studied, and this factor is extremely important because faulty chips affect the test results. Thus, the influence of chip reliability should be fully considered. This paper proposes a design method based on Bayesian decision-making (BBD) for routing-based DMFBs that can fully consider the reliability of chips during the DMFB design process. Simulated experimental results showed that the method can address the reliability problems of chips. The efficiency and convergence performance of the algorithm were very good. The proposed method can achieve an average assay completion time that is shorter than those of the moduleless synthesis (MLS) and modified-MLS (MMLS) methods. The electrode usage rate of the proposed method is better than that of the module-based and improved Dijkstra and improved particle swarm optimization (ID-IPSO) methods.
1 citations
17 May 2021
TL;DR: In this paper, an improved particle swarm optimization (PSO) method was used to optimize the testing path of a digital microfluidic biochips (DMFB) to ensure robust DMFB operation and high confidence in the outcome of experiments.
Abstract: Digital microfluidic biochips (DMFBs) is an attractive platform for immunoassays, point-of-care clinical diagnostics due to its flexible application and low fabrication cost and further for the development of instruments. Due to the DMFBs have been applied for these safe-critical field, those procedures require high output precision, so the reliability of the chips are extremely important. On-line testing methods are required to ensure robust DMFB operation and high confidence in the outcome of experiments, so a robust testing method is necessary. Many testing methods have been proposed, but most of them are simple functional testing or off-line testing. These testing methods are increasingly unable to meet the requirements of current chip testing. The online test means that there are testing droplet and bioassays running on the DMFB simultaneously. This paper introduces a heuristic method to optimize the testing path. The study utilizes the improved particle swarm optimization to solve the problem. The simulation results showed the proposed method is convergent and could be applied in various operations to reduce about 20% searching time, compared with the improved ant colony algorithm.
1 citations
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126 citations
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