Cybersecurity in Internet of Medical Vehicles: State-of-the-Art Analysis, Research Challenges and Future Perspectives.

The "Internet-of-Medical-Vehicles (IOMV)" is one of the special applications of the Internet of Things resulting from combining connected healthcare and connected vehicles. As the IOMV communicates with a variety of networks along its travel path, it incurs various security risks due to sophisticated cyber-attacks. This can endanger the onboard patient's life. So, it is critical to understand subjects related to "cybersecurity" in the IOMV to develop robust cybersecurity measures. In this paper, the goal is to evaluate recent trends and state-of-the-art publications, gaps, and future outlooks related to this research area. With this aim, a variety of publications between 2016 and 2023 from "Web-of-Science" and "Scopus" databases were analysed. Our analysis revealed that the IOMV is a niche and unexplored research area with few defined standards and frameworks, and there is a great need to implement robust cybersecurity measures. This paper will help researchers to gain a comprehensive idea of this niche research topic, as it presents an analysis of top journals and highly cited papers, their challenges and limitations, the system model and architecture of the IOMV, related applicable standards, potential cyber-attacks, factors causing cybersecurity risks, various artificial intelligence techniques for developing potential countermeasures, the assessment and parameterisation of cybersecurity risks, constraints and challenges, and future outlooks for implementing cybersecurity measures in the IOMV.

Advances in terahertz technology for cancer detection applications.

Currently, there is an increasing demand for the diagnostic techniques that provide functional and morphological information with early cancer detection capability. Novel modern medical imaging systems driven by the recent advancements in technology such as terahertz (THz) and infrared radiation-based imaging technologies which are complementary to conventional modalities are being developed, investigated, and validated. The THz cancer imaging techniques offer novel opportunities for label free, non-ionizing, non-invasive and early cancer detection. The observed image contrast in THz cancer imaging studies has been mostly attributed to higher refractive index, absorption coefficient and dielectric properties in cancer tissue than that in the normal tissue due the local increase of the water molecule content in tissue and increased blood supply to the cancer affected tissue. Additional image contrast parameters and cancer biomarkers that have been reported to contribute to THz image contrast include cell structural changes, molecular density, interactions between agents (e.g., contrast agents and embedding agents) and biological tissue as well as tissue substances like proteins, fiber and fat etc. In this paper, we have presented a systematic and comprehensive review of the advancements in the technological development of THz technology for cancer imaging applications. Initially, the fundamentals principles and techniques for THz radiation generation and detection, imaging and spectroscopy are introduced. Further, the application of THz imaging for detection of various cancers tissues are presented, with more focus on the in vivo imaging of skin cancer. The data processing techniques for THz data are briefly discussed. Also, we identify the advantages and existing challenges in THz based cancer detection and report the performance improvement techniques. The recent advancements towards THz systems which are optimized and miniaturized are also reported. Finally, the integration of THz systems with artificial intelligent (AI), internet of things (IoT), cloud computing, big data analytics, robotics etc. for more sophisticated systems is proposed. This will facilitate the large-scale clinical applications of THz for smart and connected next generation healthcare systems and provide a roadmap for future research.

Semantic segmentation in medical images through transfused convolution and transformer networks.

Recent decades have witnessed rapid development in the field of medical image segmentation. Deep learning-based fully convolution neural networks have played a significant role in the development of automated medical image segmentation models. Though immensely effective, such networks only take into account localized features and are unable to capitalize on the global context of medical image. In this paper, two deep learning based models have been proposed namely USegTransformer-P and USegTransformer-S. The proposed models capitalize upon local features and global features by amalgamating the transformer-based encoders and convolution-based encoders to segment medical images with high precision. Both the proposed models deliver promising results, performing better than the previous state of the art models in various segmentation tasks such as Brain tumor, Lung nodules, Skin lesion and Nuclei segmentation. The authors believe that the ability of USegTransformer-P and USegTransformer-S to perform segmentation with high precision could remarkably benefit medical practitioners and radiologists around the world.

Twisted Few-Mode Optical Fiber with Improved Height of Quasi-Step Refractive Index Profile.

This work presents designed and fabricated silica few-mode optical fiber (FMF) with induced twisting 10 and 66 revolutions per meter, core diameter 11 µm, typical "telecommunication" cladding diameter 125 µm, improved height of quasi-step refractive index profile and numerical aperture 0.22. Proposed FMF supports 4 guided modes over "C"-band. We discussed selection of specified optical fiber parameters to provide desired limited mode number over mentioned wavelength range. Some results of tests, performed with pilot samples of manufactured FMF, are represented, including experimentally measured spectral responses of laser-excited optical signals, that comprise researches and analysis of few-mode effects, occurring after fiber Bragg grating writing.

FSS superstrate antenna for satellite cynosure on IoT to combat COVID-19 pandemic.

The global pandemic, COVID-19 needs joint techniques and technology to combat it. The internet of things (IoT) has been at the forefront in solving problems, not only in the health care sector but in other sectors. It delivers accuracy with robustness in the developing service and application. However, it remains clear that the use of IoT is limited to coverage, longevity, security, connectivity issue, immediacy, and multicasting, we proposed in this paper frequency selective surface (FSS) as superstrate for rectangular microstrip antenna. An FSS design combine with the rectangular microstrip antenna for better performance is placed over FSS parallel configuration. The rectangular microstrip antenna was titled 45 degrees to change the band-stop. Analysis of the proposed performance in terms of gain, return loss, and directivity shows that the FSS structure's integration brings better results. With the help of a 3D electromagnetic computer simulation technology CST studio suite, we model the proposed antenna, perform the simulation with a frequency-domain solver, and validate it with a time-domain solver. The proposed impressive result is suitable for satellite networks, which hybrid with IoT can provide a sustainable long-time solution in fighting the COVID-19 pandemic.

Frequency-domain reconfigurable antenna for COVID-19 tracking.

The COVID -19 outbreak since inception has put the whole world in an unprecedented difficult situation by bringing life around the world to a frightening halt and claiming thousands of lives. Due to COVID-19's spreading across 212 countries globally, an increasing number of infected cases and death tolls rose to 146,841,882, and 3,104,743 (as of April 26, 2021), this remains a real threat to the public health system. This paper presents a novel design for the frequency-domain reconfigurable antenna at Ku and K-bands for satellite-internet of thing (IoT) tracking applications. Four reconfigurable antenna is proposed with the use of four different switch mechanisms. Furthermore, switches are used to change resonance frequency to Ku- and K-bands on the antenna surface with four stages. With the help of the 3D electromagnetic computer simulation technology (CST) studio suite, we model the proposed antenna, perform the simulation with a frequency-domain solver, and validate the results with a time-domain solver with both results obtained in agreement as the proposed reconfigurable antenna operates over a wide frequency range for the satellite-IoT network to track COVID-19 pandemic.

SMF/FSO integrated dual-rate reliable and energy efficient WDM optical access network for smart and urban communities.

To handle the massive high-speed internet traffic, free space optics (FSO) or single-mode fiber (SMF) based fiber optic communication is being used everywhere across the world. These technologies are capable of providing huge bandwidth and transmitting the data at very high speed with low energy consumption. FSO is a very convenient technology to quickly expand the legacy network in the adverse geographical areas. However, its link performance is highly dependent of inconsistent weather conditions. SMF based fiber optic link has a very low loss and its performance is almost independent on the weather conditions. Though, the installation and maintenance of fibers are quite complex and costly. Individually, FSO or SMF links have their limitations and have to be integrated to leverage their benefits. In this paper, we integrated FSO/SMF links and compared the performance of the proposed architecture which is capable of providing high-speed dual-rate data transmission. The proposed architecture transmits data over either FSO or SMF or both links simultaneously and has 100% more reliability against any one of the link failures. In case of operational link failure (FSO/SMF), data may be switched to the alternative working link (SMF/FSO), simply by tuning the transmitted signal by 50 GHz. The proposed architecture is also reliable against the optical line terminal transceiver (TRx) failure as each user located in the network can be served by two transceivers (1 Gbps and 10 Gbps). The proposed architecture also supports the wavelength division multiplexing overlay transmission for broadcasting the common signal to all the available users in the networks. The architecture reduces ~ 27% of the energy consumption by utilizing the appropriate link of hybrid architecture and TRx according to weather conditions and traffic load. The integrated architecture looks attractive for providing energy-efficient, high speed, and reliable internet coverage to the areas where there is a difficulty of laying fibers and has frequent fiber faults. The architecture is useful for strengthening and boosting rural and urban development.

Implementation of stacking based ARIMA model for prediction of Covid-19 cases in India.

BACKGROUND: Time-series forecasting has a critical role during pandemics as it provides essential information that can lead to abstaining from the spread of the disease. The novel coronavirus disease, COVID-19, is spreading rapidly all over the world. The countries with dense populations, in particular, such as India, await imminent risk in tackling the epidemic. Different forecasting models are being used to predict future cases of COVID-19. The predicament for most of them is that they are not able to capture both the linear and nonlinear features of the data solely. METHODS: We propose an ensemble model integrating an autoregressive integrated moving average model (ARIMA) and a nonlinear autoregressive neural network (NAR). ARIMA models are used to extract the linear correlations and the NAR neural network for modeling the residuals of ARIMA containing nonlinear components of the data. Comparison: Single ARIMA model, ARIMA-NAR model and few other existing models which have been applied on the COVID-19 data in different countries are compared based on performance evaluation parameters. RESULT: The hybrid combination displayed significant reduction in RMSE (16.23%), MAE (37.89%) and MAPE (39.53%) values when compared with single ARIMA model for daily observed cases. Similar results with reduced error percentages were found for daily reported deaths and cases of recovery as well. RMSE value of our hybrid model was lesser in comparison to other models used for forecasting COVID-19 in different countries. CONCLUSION: Results suggested the effectiveness of the new hybrid model over a single ARIMA model in capturing the linear as well as nonlinear patterns of the COVID-19 data.

3D-quantum interferometer using silicon microring-embedded gold grating circuit.

A 3D (three-dimensional) quantum interferometer consisting of a silicon microring circuit proposed. The interferometer based on the electron spin cloud projections generated by microring-embedded gold grating. The electron cloud oscillations result from the excitation of the gold grating at the center of the silicon microring by the dark soliton pulse of 1.50 µm center wavelength. The electron cloud spin-down, spin-up automatically formed in the two axes (x, y, respectively) and propagated along the z-axis. In this proposal, the sensing mechanism of the circuit is manipulated by varying the reflector gold lengths of the sensing arm. The electron cloud spin coupled and changed by changing the gold lengths. The sensitivity measurement of the 3D quantum interferometer for three gold layer lengths of 100 nm, 500 nm, and 1,000 nm is (47.62 nm fs-1 , ±0.4762 fs-1 , ±0.01 nm-1 ), (238.10 nm fs-1 , ±0.4762 fs-1 , ±0.002 nm-1 ), (476.20 nm fs-1 , ±0.4762 fs-1 , ±0.001 nm-1 ), respectively. The used circuit parameters are the real ones that can be fabricated by the currently available technology. Moreover, the silicon micro ring circuit acts as a plasmonic antenna, which can apply for wireless quantum communication. The electron cloud spin projection space-time control can apply for quantum cellular automata.

Supercontinuum generation at 1.55 µm in As2S3 core photonic crystal fiber.

This paper proposes a design and mathematical study of As2S3 chalcogenide photonic crystal fiber (PCF) for broadband supercontinuum generation. The proposed design offers a large nonlinearity coefficient and ultra-flattened dispersion. The proposed design was analyzed using the full-vectorial finite element method. Through this method, it is shown that an ultra-broad supercontinuum spectrum of 0.8-4.5 µm is attained using an As2S3 core PCF design with 20 fs pump pulse width and a length of 10 mm, having 3 kW power at a -40 dB spectral and temporal intensity. The proposed octagonal PCF has shown a low zero dispersion wavelength at the pump wavelength of 1.55 µm.

General method of extreme surfaces for geometry optimization of the linear electro-optic effect on an example of LiNbO3:MgO crystals.

A general method for determining the global maximum of the linear electro-optic effect in crystalline materials based on the construction and analysis of extreme surfaces obtained as a result of the optimization procedure is proposed. The electrically induced optical path length changes for ordinary and extraordinary waves as well as the optical path difference for orthogonally polarized waves were used as the objective functions in the optimization. The objective functions were determined for units of the electric field and crystal thickness in the light pass direction. In the example of LiNbO3:MgO, it is shown that the maximal achievable given values of the optical path length change (global maxima) for ordinary and extraordinary waves are 119 pm/V and 277 pm/V, respectively. The global maximum of the optical path difference for orthogonally polarized waves is 269 pm/V (for 632.8 nm wavelength and at room temperature). These global maxima are exceeded by ∼1.5, 1.7, and 2.3 times the respective maximum values on direct cut crystals of LiNbO3:MgO and are ∼5%, 9%, or 11% larger than the global maxima for undoped LiNbO3 crystal. This ensures a possibility to increase the energy efficiency by ∼2.9 or 5.3 times in the case of using of LiNbO3:MgO crystals with optimal cuts as sensitive elements of electro-optic devices.