Internet of Things (IoT) paradigm became particularly popular in the last couple of years in such a way that the devices are present in almost every home across the globe. Using cheap components one can connect any device to the internet and enable information collecting from the environment, making everyday life a lot easier. Even though it does bring multiple advantages to the table, at the same time it brings certain challenges and vulnerabilities that need to be addressed. In this paper we focus on Distributed Denial of Service (DDoS) and Denial of Service (DoS) attacks and we provide a review of the current architecture of Internet of Things which is prone to these.

One of the biggest problems the maritime industry is currently experiencing is corrosion, resulting in short and long-term damages. Early prediction and proper corrosion monitoring can reduce economic losses. Traditional approaches used in corrosion prediction and detection are time-consuming and challenging to execute in inaccessible areas. Due to these reasons, artificial intelligence-based algorithms have become the most popular tools for researchers. This study discusses state-of-the-art artificial intelligence (AI) methods for marine-related corrosion prediction and detection: (1) predictive maintenance approaches and (2) computer vision and image processing approaches. Furthermore, a brief description of AI is described. The outcomes of this review will bring forward new knowledge about AI and the development of prediction models which can avoid unexpected failures during corrosion detection and maintenance. Moreover, it will expand the understanding of computer vision and image processing approaches for accurately detecting corrosion in images and videos.

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Design of a microstrip patch UHF reader parasitic array antenna for RFID (Radio Frequency Identification) applications is proposed, in which the design patches antenna realized by loading two truncated at the corner of the ordinary rectangular patch antenna. The patch was sorted in a 2 x 2 array configuration, meanwhile the feed network was constructed by coaxial feed concept. The parasitic elements are added on the same layer of the substrate and at the right and left side of the every patch. The physical parameters of the novel structure are simulated and optimized by using commercial computer simulation technology (CST) simulation packages. The simulation results show the high gain antenna is achieved which is 11.15 dBi. The measured results of the return losses and the radiation pattern achieved a good agreement with the simulated results.

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<span>This paper presents a compact microstrip ultra-high frequency (UHF) reader patch antenna with complementary split ring resonator (CSRR) for radio frequency identification (RFID). The total size of the antenna is 208 × 208 × 1.6 mm³. The proposed antenna is designed, fabricated and measured in order to verify the proposed concept. The characterization for radiation parameters, like return loss, radiation pattern and antenna gain have been done experimentally. The proposed antenna is operated at 921 MHz for and achieved a gain of 8.285 dBi. All simulations in this work have been carried out by means of the commercial computer simulation technology (CST) software. In compare to the simulated results, the measured outcomes are promised.</span>

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