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Due to the presence of actuator disturbances and sensor noise, increased false alarm rate and decreased fault detection rate in fault diagnosis systems have become major concerns. Various performance indexes are proposed to deal with such problems with certain limitations. This paper proposes a robust performance-index based fault diagnosis methodology using input–output data. That data is used to construct robust parity space using the subspace identification method and proposed performance index. Generated residual shows enhanced sensitivity towards faults and robustness against unknown disturbances simultaneously. The threshold for residual is designed using the Gaussian likelihood ratio, and the wavelet transformation is used for post-processing. The proposed performance index is further used to develop a fault isolation procedure. To specify the location of the fault, a modified fault isolation scheme based on perfect unknown input decoupling is proposed that makes actuator and sensor residuals robust against disturbances and noise. The proposed detection and isolation scheme is implemented on the induction motor in the experimental setup. The results have shown the percentage fault detection of 98.88%, which is superior among recent research.

The approach to applications integration for World Data Center (WDC) interdisciplinary scientific investigations is developed in the article. The integration is based on mathematical logic and artificial intelligence. Key elements of the approach-a multilevel system architecture, formal logical system, implementation-are based on intelligent agents interaction. The formal logical system is proposed. The inference method and mechanism of solution tree recovery are elaborated. The implementation of application integration for interdisciplinary scientific research is based on a stack of modern protocols, enabling communication of business processes over the transport layer of the OSI model. Application integration is also based on coordinated models of business processes, for which an integrated set of business applications are designed and realized.

In this article, a rectangular dielectric resonator antenna (RDRA) with circularly polarized (CP) response is presented for 5G NR (New Radio) Sub-6 GHz band applications. A uniquely shaped conformal metal feeding strip is proposed to excite the RDRA in higher-order mode for high gain utilization. By using the proposed feeding mechanism, the degenerate mode pair of the first higher-order, i.e., TEδ13x at 4.13 GHz and TE1δ3y,  at 4.52 GHz is excited to achieve a circularly polarized response. A circular polarization over a bandwidth of ~10%, in conjunction with a wide impedance matching over a bandwidth of ~17%, were attained by the antenna. The CP antenna proposed offers a useful gain of ~6.2 dBic. The achieved CP bandwidth of the RDRA is good enough to cover the targeted 5G NR bands around 4.4–4.8 GHz, such as n79. The proposed antenna configuration is modelled and optimized using computer simulation technology (CST). A prototype was built to confirm (validate) the performance estimated through simulation. A good agreement was observed between simulated and measured results.

The amazing fusion of the internet of things (IoT) into traditional health monitoring systems has produced remarkable advances in the field of e-health. Different wireless body area network devices and sensors are providing real-time health monitoring services. As the number of IoT devices is rapidly booming, technological and security challenges are also rising day by day. The data generated from sensor-based devices need confidentiality, integrity, authenticity, and end-to-end security for safe communication over the public network. IoT-based health monitoring systems work in a layered manner, comprising a perception layer, a network layer, and an application layer. Each layer has some security, and privacy concerns that need to be addressed accordingly. A lot of research has been conducted to resolve these security issues in different domains of IoT. Several frameworks for the security of IoT-based e-health systems have also been developed. This paper introduces a security framework for real-time health monitoring systems to ensure data confidentiality, integrity, and authenticity by using two common IoT protocols, namely constrained application protocol (CoAP) and message query telemetry transports (MQTT). This security framework aims to defend sensor data against the security loopholes while it is continuously transmitting over the layers and uses hypertext transfer protocols (HTTPs) for this purpose. As a result, it shields from the breach with a very low ratio of risk. The methodology of this paper focuses on how the security framework of IoT-based real-time health systems is protected under the tiers of CoAP and HTTPs. CoAP works alongside HTTPs and is responsible for providing end-to-end security solutions.

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Abstract-This paper presents a deep analysis of literature on the problems of optimization of parameters and structure of the neural networks and the basic disadvantages that are present in the observed algorithms and methods. As a result, there is suggested a new algorithm for neural network structure optimization, which is free of the major shortcomings of other algorithms. The paper describes a detailed description of the algorithm, its implementation and application for recognition problems.