Biblio

With the rapid development of blockchain technology, it provides a new technical solution for secure storage of data and trusted computing. However, in the actual application of data traceability, blockchain technology has an obvious disadvantage: the large amount of data stored in the blockchain system will lead to a long response time for users to query data. Higher query delay severely restricts the development of block chain technology in the traceability system. In order to solve this problem, we propose an efficient, secure and low storage overhead blockchain query scheme. Specifically, we design an index structure independent of Merkle tree to support efficient intra-block query, and create new fields in the block header to optimize inter-block query. Compared with several existing schemes, our scheme ensures the security of data. Finally, we simulate and evaluate our proposed scheme. The results show that the proposed scheme has better execution efficiency while reducing additional overhead.

An increasing number of industries around the world are adopting advance manufacturing technologies for product design, among which additive manufacturing (AM) is gaining attention among aerospace, defense, automotive and health care domains. Products with complicated designs demanding lesser weight, improved performance and conformance are manufactured by companies using AM technologies. Some noticeable examples of ducting, airflow system and vent products in the aerospace domain can be seen being made out of AM techniques. One of the benefits being mentioned is the significant reduction in the number of components going into a finished product, thereby impacting the supply chain as well. However, one of the challenges in AM process is to reduce the process variation which affects the reliability of the product. To realize the true benefits of additively manufactured products, it is imperative to ensure that the reliability of AM products is similar or better than traditionally manufactured products. Current state of art for assessing reliability of traditionally manufactured products is mature. However, the reliability assessment framework for products manufactured by advanced technologies are being studied upon. In this direction, this paper highlights a structured reliability assessment framework for additive manufactured products, which will help in identifying, analyzing and mitigating reliability risks as part of product development life cycle.

Cloud computing has included an essential part of its industry and statistics garage is the main service provided, where a huge amount of data can be stored in a virtual server. Storing data in public platforms may be vulnerable to threats. Consequently, the obligation of secure usage and holistic backup of statistics falls upon the corporation providers. Subsequently, an affordable and compliant mechanism of records auditing that permits groups to audit the facts stored in shared clouds whilst acting quick and trouble- unfastened healing might be a fairly sought-after cloud computing task concept. There is a lot of advantage in growing this domain and there is considerable precedence to follow from the examples of dropbox, google power among others.

Digital-Twins simulate physical world objects by creating 'as-is' virtual images in a cyberspace. In order to create a well synchronized digital-twin simulator in manufacturing, information and activities of a physical machine need to be virtualized. Many existing digital-twins stream read-only data of machine sensors and do not incorporate operations of manufacturing machines through Internet. In this paper, a new method of virtualization is proposed to integrate machining data and operations into the digital-twins using Internet scale machine tool communication method. A fully functional digital-twin is implemented in CPMC testbed using MTComm and several manufacturing application scenarios are developed to evaluate the proposed method and system. Performance analysis shows that it is capable of providing data-driven visual monitoring of a manufacturing process and performing manufacturing operations through digital twins over the Internet. Results of the experiments also shows that the MTComm based digital twins have an excellent efficiency.

NoC (Network-on-Chip) is widely considered and researched by academic communities as a new inter-core interconnection method that replaces the bus. Nowadays, the complexity of on-chip systems is increasing, requiring better communication performance and scalability. Therefore, the optimization of communication performance has become one of the research hotspots. While the NoC is rapidly developing, it is threatened by hardware Trojans inserted during the design or manufacturing processes. This leads to that the attackers can exploit NoC's vulnerability to attack the on-chip systems. To solve the problem, we design and implement a replay-type hardware Trojan inserted into the NoC, aiming to provide a benchmark test set to promote the defense strategies for NoC hardware security. The experiment proves that the power consumption of the designed Trojan accounts for less than one thousandth of the entire NoC power consumption and area. Besides, simulation experiments reveal that this replaytype hardware Trojan can reduce the network throughput.

The manufacturing process of electrical machines influences the geometric dimensions and material properties, e.g. the yoke thickness. These influences occur by statistical variation as manufacturing tolerances. The effect of these tolerances and their potential impact on the mechanical torque output is not fully studied up to now. This paper conducts a sensitivity analysis for geometric and material parameters. For the general approach these parameters are varied uniformly in a range of 10 %. Two dimensional finite element analysis is used to simulate the influences at three characteristic operating points. The studied object is an internal permanent magnet machine in the 100 kW range used for hybrid drive applications. The results show a significant dependency on the rotational speed. The general validity is studied by using boundary condition variations and two further machine designs. This procedure offers the comparison of matching qualitative results for small quantitative deviations. For detecting the impact of the manufacturing process realistic tolerance ranges are used. This investigation identifies the airgap and magnet remanence induction as the main parameters for potential torque fluctuation.