IoMT-Based Smart Monitoring Hierarchical Fuzzy Inference System for Diagnosis of COVID-19

The prediction of human diseases, particularly COVID-19, is an extremely challenging task not only for medical experts but also for the technologists supporting them in diagnosis and treatment. To deal with the prediction and diagnosis of COVID-19, we propose an Internet of Medical Things-based Smart Monitoring Hierarchical Mamdani Fuzzy Inference System (IoMTSM-HMFIS). The proposed system determines the various factors like fever, cough, complete blood count, respiratory rate, Ct-chest, Erythrocyte sedimentation rate and C-reactive protein, family history, and antibody detection (lgG) that are directly involved in COVID-19. The expert system has two input variables in layer 1, and seven input variables in layer 2. In layer 1, the initial identification for COVID-19 is considered, whereas in layer 2, the different factors involved are studied. Finally, advanced lab tests are conducted to identify the actual current status of the disease. The major focus of this study is to build an IoMT-based smart monitoring system that can be used by anyone exposed to COVID-19; the system would evaluate the user’s health condition and inform them if they need consultation with a specialist for quarantining. MATLAB-2019a tool is used to conduct the simulation. The COVID-19 IoMTSM-HMFIS system has an overall accuracy of approximately 83%. Finally, to achieve improved performance, the analysis results of the system were shared with experts of the Lahore General Hospital, Lahore, Pakistan.     

Rotational Effect on the Propagation of Waves in a Magneto-Micropolar Thermoelastic Medium

The present paper aims to explore how the magnetic field, ramp parameter, and rotation affect a generalized micropolar thermoelastic medium that is standardized isotropic within the half-space. By employing normal mode analysis and Lame’s potential theory, the authors could express analytically the components of displacement, stress, couple stress, and temperature field in the physical domain. They calculated such manners of expression numerically and plotted the matching graphs to highlight and make comparisons with theoretical findings. The highlights of the paper cover the impacts of various parameters on the rotating micropolar thermoelastic half-space. Nevertheless, the non-dimensional temperature is not affected by the rotation and the magnetic field. Specific attention is paid to studying the impact of the magnetic field, rotation, and ramp parameter of the distribution of temperature, displacement, stress, and couple stress. The study highlighted the significant impact of the rotation, magnetic field, and ramp parameter on the micropolar thermoelastic medium. In conclusion, graphical presentations were provided to evaluate the impacts of different parameters on the propagation of plane waves in thermoelastic media of different nature. The study may help the designers and engineers develop a structural control system in several applied fields.     

An effective method for classification with missing values

Classification is one of the most important tasks in machine learning with a huge number of real-life applications. In many practical classification problems, the available information for making object classification is partial or incomplete because some attribute values can be missing due to various reasons. These missing values can significantly affect the efficacy of the classification model. So it is crucial to develop effective techniques to impute these missing values. A number of methods have been introduced for solving classification problem with missing values. However they have various problems. So, we introduce an effective method for imputing missing values using the correlation among the attributes. Other methods which consider correlation for imputing missing values works better either for categorical or numeric data, or designed for a particular application only. Moreover they will not work if all the records have at least one missing attribute. Our method, Model based Missing value Imputation using Correlation (MMIC), can effectively impute both categorical and numeric data. It uses an effective model based technique for filling the missing values attribute wise and reusing then effectively using the model. Extensive performance analyzes show that our proposed approach achieves high performance in imputing missing values and thus increases the efficacy of the classifier. The experimental results also show that our method outperforms various existing methods for handling missing data in classification.     

States of Sulfur in Alkali Borate Glasses

Simple binary alkali borate glasses of differing alkali content (alkali = Li, Na, or K) containing sulfur were prepared and their absorption spectra were measured in the range of 200 to 700 nm. The absorption bands obtained were used to determine the stable states of sulfur in these glasses by directly comparing them with published data. The following states of sulfur were identified and their ranges of stability were determined: the S₂ molecule in glasses containing at least 15 mol% alkali oxide, the S₃⁻ and S₂⁻ in glasses containing 20 to 30 mol% Na₂O or K₂O, and the polysulfide ion (S x ²⁻) in glasses of 30 to 35 mol% Na₂O or K₂O.     

Preparation and characterization of PPRC/EPDM thermoplastic vulcanizates: A comparative study

Thermoplastic vulcanizates (TPVs) of polypropylene random copolymer (PPRC) with ethylene–propylene diene monomer rubber (EPDM) were prepared through in situ and ex situ compatibilization techniques. Silanized silica as nanofiller was incorporated in the ex situ compatibilized TPVs. Mechanical properties were measured for different formulated TPVs with increasing loading of EPDM from 10 to 30 phr. A comparative data is generated to discuss the effect of two compatibilization techniques and addition of silica filler in the TPVs. The degradation studies were also carried out to check the stability of the blends under harsh ultraviolet environment. The in situ compatibilized TPVs provided better overall mechanical properties. Moreover, it is worth mentioning that the properties of ex situ compatiblized TPVs were enhanced by incorporation of silanized silica filler. Silanized silica filler helped in reducing the die swell significantly. © 2018 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2018 , 135, 46726.     

A comprehensive survey of network coding in vehicular ad-hoc networks

Network coding is a data processing technique in which the flow of digital data is optimized in a network by transmitting a composite of two or more messages to make the network more robust. Network coding has been used in traditional and emerging wireless networks to overcome the communications issues of these networks. It also plays an important role in the area of vehicular ad-hoc networks (VANETs) to meet the challenges like high mobility, rapidly changing topology, and intermittent connectivity. VANETs consist of network of vehicles in which they communicate with each other to ensure road safety, free flow of traffic, and ease of journey for the passengers. It is now considered to be the most valuable concept for improving efficiency and safety of future transportation. However, this field has a lot of challenges to deal with. This paper presents a comprehensive survey of network coding schemes in VANETs. We have classified different applications like content distribution, multimedia streaming, cooperative downloading, data dissemination, and summarized other key areas of VANETs in which network coding schemes are implemented. This research work will provide a clear understanding to the readers about how network coding is implemented in these schemes in VANETs to improve performance, reduce delay, and make the network more efficient.     

Green Adeptness in the Synthesis and Stabilization of Copper Nanoparticles: Catalytic,Antibacterial, Cytotoxicity,and Antioxidant Activities

Copper nanoparticles (CuNPs) are of great interest due to their extraordinary properties such as high surface-to-volume ratio, high yield strength, ductility, hardness, flexibility, and rigidity. CuNPs show catalytic, antibacterial, antioxidant, and antifungal activities along with cytotoxicity and anticancer properties in many different applications. Many physical and chemical methods have been used to synthesize nanoparticles including laser ablation, microwave-assisted process, sol-gel, co-precipitation, pulsed wire discharge, vacuum vapor deposition, high-energy irradiation, lithography, mechanical milling, photochemical reduction, electrochemistry, electrospray synthesis, hydrothermal reaction, microemulsion, and chemical reduction. Phytosynthesis of nanoparticles has been suggested as a valuable alternative to physical and chemical methods due to low cytotoxicity, economic prospects, environment-friendly, enhanced biocompatibility, and high antioxidant and antimicrobial activities. The review explains characterization techniques, their main role, limitations, and sensitivity used in the preparation of CuNPs. An overview of techniques used in the synthesis of CuNPs, synthesis procedure, reaction parameters which affect the properties of synthesized CuNPs, and a screening analysis which is used to identify phytochemicals in different plants is presented from the recent published literature which has been reviewed and summarized. Hypothetical mechanisms of reduction of the copper ion by quercetin, stabilization of copper nanoparticles by santin, antimicrobial activity, and reduction of 4-nitrophenol with diagrammatic illustrations are given. The main purpose of this review was to summarize the data of plants used for the synthesis of CuNPs and open a new pathway for researchers to investigate those plants which have not been used in the past.

Open image in new window

Graphical abstract Proposed Mechanism for Antibacterial activity of copper nanoparticles.

     

比例电磁式主动吸振器的设计方法研究

以电磁铁为作动器,开展了电磁式主动吸振器设计方法的研究。对主动吸振器电磁作动器进行了设计研究,针对基于E型电磁作动器的主动吸振器具有非对称驱动力的问题,设计了一种具有盘形磁极面的比例电磁作动器。采用有限元和试验验证的方法,对电磁作动器在不同磁极面结构参数组合下的电磁力进行了正交仿真计算和验证,以在一定的动铁心位移范围内电磁力波动最小为目标,获得了最优组合的磁极面结构参数。对主动吸振器动质量的动态位移进行了计算分析,并基于主动吸振器的工作频带和目标驱动力,设计了动铁心的静平衡位置。计算了主动吸振器设计刚度值,并分析了刚度参数对吸振器电磁力特性的影响。最后,结合理论计算和试验验证的方法,分析了比例电磁式主动吸振器近似对称的驱动力特性。     

Quantum secret sharing protocol through noisy channel with application in visual cryptography

This study presents a quantum secret sharing (QSS) protocol designed using Grover's search algorithm in a noisy environment. The proposed protocol utilizes Grover's three-particle quantum state. The proposed scheme is divided into secret information sharing and eavesdropping checking. The dealer prepares an encoded state by encoding the classical information as a marked state and shares the states' qubits between three participants. Using the amplitude-damping noise and the phase-damping noise as conventional noisy channels, it can be demonstrated that secret information can be conveyed between participants with some information lost. The security analysis shows the scheme is stringent against malicious participants or eavesdroppers. The simulation analysis is done on the cloud platform IBM-QE thereby showing the practical feasibility of the scheme. Finally, an application of the proposed scheme is demonstrated in visual cryptography using the GNEQR representation of images.     

A survey on trust based detection and isolation of malicious nodes in ad-hoc and sensor networks

Mobile ad-hoc networks (MANETs) and wireless sensor networks (WSNs) have gained remarkable appreciation and technological development over the last few years. Despite ease of deployment, tremendous applications and significant advantages, security has always been a challenging issue due to the nature of environments in which nodes operate. Nodes’ physical capture, malicious or selfish behavior cannot be detected by traditional security schemes. Trust and reputation based approaches have gained global recognition in providing additional means of security for decision making in sensor and ad-hoc networks. This paper provides an extensive literature review of trust and reputation based models both in sensor and ad-hoc networks. Based on the mechanism of trust establishment, we categorize the stateof-the-art into two groups namely node-centric trust models and system-centric trust models. Based on trust evidence, initialization, computation, propagation and weight assignments, we evaluate the efficacy of the existing schemes. Finally, we conclude our discussion with identification of some unresolved issues in pursuit of trust and reputation management.