Journal of Electronic Science and Technology最新文献

As big data becomes an apparent challenge to handle when building a business intelligence (BI) system, there is a motivation to handle this challenging issue in higher education institutions (HEIs). Monitoring quality in HEIs encompasses handling huge amounts of data coming from different sources. This paper reviews big data and analyses the cases from the literature regarding quality assurance (QA) in HEIs. It also outlines a framework that can address the big data challenge in HEIs to handle QA monitoring using BI dashboards and a prototype dashboard is presented in this paper. The dashboard was developed using a utilisation tool to monitor QA in HEIs to provide visual representations of big data. The prototype dashboard enables stakeholders to monitor compliance with QA standards while addressing the big data challenge associated with the substantial volume of data managed by HEIs’ QA systems. This paper also outlines how the developed system integrates big data from social media into the monitoring dashboard

A microwave-induced thermoacoustic imaging (MITAT) system is a non-destructive physical medical imaging method that combines the advantages of the high contrast of microwave imaging and the high resolution of ultrasound imaging. It uses the microwave as the excitation source and ultrasound as the information carrier. When different kinds of biological tissue absorb electromagnetic energy, it results in localized temperature rises. The thermal expansion will induce ultrasonic signals (i.e., thermoacoustic signals) known as the thermoacoustic effect. The microwave absorption image of the sample can be reconstructed by algorithm processing. The MITAT contrast depends on different dielectric parameters of different kinds of tissue. We introduce the developed system and its application. In addition, the challenges and prospects of the MITAT for further development are argued.

At present, a life-cycle assessment of energy storage systems (ESSs) is not widely available in the literature. Such an assessment is increasingly vital nowadays as ESS is recognized as one of the important equipment in power systems to reduce peak demands for deferring or avoiding augmentation in the network and power generation. As the battery cost is still very high at present, a comprehensive assessment is necessary to determine the optimal capacity of ESS so that the maximum financial gain is achievable at the end of the batteries’ lifespan. Therefore, an effective life-cycle assessment is proposed in this paper to show how the optimum capacity of ESS can be determined such that the maximum net financial gain is achievable at the end of the batteries’ lifespan when ESS is used to perform peak demand reductions for the customer or utility companies. The findings reveal the positive financial viability of ESS on the power grid, otherwise the projection of the financial viability is often seemingly poor due to the high battery cost with a short battery lifespan. An improved battery degradation model is used in this assessment, which can simulate the battery degradation accurately in a situation whereby the charging current, discharging current, and temperature of the batteries are intermittent on a site during peak demand reductions. This assessment is crucial to determine the maximum financial benefits brought by ESS.

Some electrical parameters of the SIS-type hysteretic underdamped Josephson junction (JJ) can be measured by its current-voltage characteristics (IVCs). Currents and voltages at JJ are commensurate with the intrinsic noise level of measuring instruments. This leads to the need for multiple measurements with subsequent statistical processing. In this paper, the digital algorithms are proposed for the automatic measurement of the JJ parameters by IVC. These algorithms make it possible to implement multiple measurements and check these JJ parameters in an automatic mode with the required accuracy. The complete sufficient statistics are used to minimize the root-mean-square error of parameter measurement. A sequence of current pulses with slow rising and falling edges is used to drive JJ, and synchronous current and voltage readings at JJ are used to realize measurement algorithms. The algorithm performance is estimated through computer simulations. The significant advantage of the proposed algorithms is the independence from current source noise and intrinsic noise of current and voltage meters, as well as the simple implementation in automatic digital measuring systems. The proposed algorithms can be used to control JJ parameters during mass production of superconducting integrated circuits, which will improve the production efficiency and product quality.

This paper deals with the supervisory control problem of discrete event systems modeled by labeled Petri nets. The system is originally unbounded. First, the solvability of the problem is confirmed. A necessary condition is given and proven for the existence of a feasible priority-based controller based on the notions of liveness and transition invariants. Next, a cyclic behavior graph is constructed, which shows the reachable markings that guarantee the maximum liveness of the system within a given bound vector. Finally, an on-line control strategy is proposed to enforce boundedness and liveness to the given system by appending priority relations to transitions. The dynamic priority relation changes flexibly according to the current state of the system and enforces the system evolving in a bounded and live manner. In addition, numerical examples are studied to verify the validity of the proposed approach that remains the structure of the plant net and is efficient for on-line control.

With the rapid development of wind power, wind turbines are accompanied by a large quantity of power electronic converters connected to the grid, causing changes in the characteristics of the power system and leading to increasingly serious sub-synchronous oscillation (SSO) problems, which urgently require the generalized classification and characterization of the emerging oscillation problems. This paper classifies and characterizes the emerging types of SSO caused by grid-connected wind turbines to address these issues. Finally, the impact of the typical system parameters changes on the oscillation pattern is analyzed in depth to provide effective support for the subsequent suppression and prevention of SSO.