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Despite its important existing challenges, quantum-dot cellular automata (QCA) is one of the promising replacement candidates of the traditional VLSI technology. Practical implementation issues such as fault tolerance and lack of customized CAD tools and algorithms for automatic synthesis of large complex systems are some important instances of QCA circuit design challenges. Currently, most of the research papers focus only on development of individually efficient QCA gates and circuits in terms of only their physical properties such as area and delay. However, throughout this paper, it is demonstrated that these compressed and fast individual QCA gates and circuits cause serious concerns when they are exploited as building blocks in modular design of higher level complex circuits. Some simple but effective design rules are then emphasized to solve this problem by preserving the “modular design efficiency” of the developed underlying QCA gates and circuits. As a case study, two new instances of fault-tolerant QCA XOR gates are introduced which are designed by simultaneously considering both area/delay and modular design efficiency rules. A wide range of numerical experiments are provided throughout the paper to prove the priority of the proposed gates with respect to eight other samples of the most efficient existing XOR structures, when exploiting them to build more complex circuits such as adders and error detection/correction circuits.

The system level hardware architecture of individual nodes in a distributed wireless sensor network has not received adequate attention. A novel hardware architecture based on the concept of task specific modular computing provides both the high flexibility and power efficiency required for effective distributed sensing solutions. This paper presents this newly developed architecture and provides an analysis of two possible methods for module interaction. Results from simulations based on this analysis are given. Finally, a brief description of the hardware and software design and prototype implementation of the modular architecture for sensor systems (MASS) is given to show the ease of use of the conceptual architecture.

Modular product architectures offer a solution for the trade-off between offering the market a wide variety of products and improving a company’s internal cost situation. However, individual cost effects that determine the extent to which modularity should be applied to product architecture are widely unknown in industry. In this paper, we develop a conceptual approach to provide suggestions for improving an examined modular product architecture from a cost perspective. Our work makes an important contribution: The conceptual approach accentuates which steps are necessary in order to recommend whether the product architecture’s current degree of modularity should be enhanced or diminished.

A modular learning design for classifying aircraft flight data in time-series prediction is proposed in this paper. This is part of the decision support system to assist landing signal officers in guiding aircraft to land on aircraft carriers. NeuroFuzzy systems are used to emulate the flight patterns for future real-time flight prediction. To improve the learning efficiency, a two stage modular learning design is proposed. The data to be learned is first decomposed into categories in accordance to their physical structure. Each module of data is presented to a different NeuroFuzzy system for learning purpose. Individually trained modules are modeled as genetic chromosomes. Genetic algorithm is used to produce a chromosome module that represents a generalization of all the trained modules. As compared with the non-modular approach, the modular approach offers comparable prediction performance with significantly lower overall computation time. We show that the reduction in computation time with the modular approach is exponential as the problem size increases. Navy aircraft data were used to validate the effectiveness of the modular design and the result is consistent and promising.

To solve the problem of the high cost and inconvenience of traditional automation teaching aids, this study focuses on the design of a set of portable, low-cost automation teaching aids, through the simple modular design, we can develop portable automation teaching equipment, which includes PLC (Programmable Logic Controller, PLC) program controller, human-machine interface design, intelligent set-top box, and so on. Component design can be different according to the drive mode of the two blocks of electric and pneumatic, can also be two blocks in combination with sensors to form a small real-world factory automation line simulation, simulation of the actual industry’s various control applications, you can also connect individual devices by importing IoT (Internet of Things, IoT) and then monitoring the movement of each device by your mobile phone. The development of portable teaching aids can be used to reverse traditional vocational education and to extend this teaching aids down to secondary and even primary education.

The volume of customized clothing order has increased, making the digital management of order flow the key to effectively control the production costs to improve the production efficiency and to increase the economic benefits. In this study, we aimed to formulate an effective and feasible digital management solution. First, we analyzed the production management status and the existing problems of customized clothing business. Then, using the enterprise resources planning (ERP) system, we optimized the traditional customized business process and redesigned the function module of the digital management system for customized clothing. This study introduced a component technology and a radio-frequency identification (RFID) middleware to enhance the adaptability and the efficiency of the digital management system. Finally, we proposed three digital management solutions: establishing the standard and reasonable product coding system, standardizing the production process using a grouping of similar procedures, and standardizing the production materials. The research results provided the theoretical basis and references for the digital management of the order flow for customized clothing enterprises as well as for the development of novel digital management systems.

Walking robots are designed to cope with difficult, challenging terrain. Therefore, developers have to take special care not to damage or break their robots legs in such environments. The shoulder joints are especially suffering from high stress values. This work presents a concept for a robust, modular shoulder design for bio-inspired hexapods. It was evaluated and is being used for the current version of the walking robot LAURON V.

According to the specific application environments and design demands in the marine environments, a novel comprehensive data acquisition system is developed. Modular design method is taken while hardware designing, so each module can work independently and be used in similar applications. Measurement algorithm and its time complexity are taken into account at one and the same time while software designing, so this system can work in real time. More importantly, performance contrast of different measurement algorithms can be used as the guidelines in other environment parameters acquisition system. Experimental results show that this system works well and completely meets the design demands. Furthermore, this system features high measurement precision, good real-time performance, strong robustness and low cost.