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Respiratory tract infection is the most common infection worldwide in recent years which affect children frequently. This is mainly classified into upper respiratory tract infection and lower respiratory tract infection. Recurrent upper respiratory tract infection means defined as six or more than six serious attacks of symptoms of respiratory tract for minimum 1 year which will affect normal functioning. Asthma is a common public health problem around worldwide developed countries. About 300 million people have been affected globally due to bronchial asthma. Homoeopathy is a system which treats patients with individual symptoms by various methods of homoeopathic prescription to attain an exact cure.

The unmanned aerial vehicles (UAV’s) are widely used in smart logistic application. The optimal route prediction, however, is a fundamental prerequisite for UAV in commercial applications. This paper introduces an Improved Rapid random tree (IRRT*) algorithm with triangular inequality rewiring technique for finding collision free path for UAVs in a three-dimensional (3D) environment. The 3D building environments for navigation were developed using MATLAB/Simulink 2021, a virtual occupancy grid model. By considering UAV variable elements such as roll angle, air speed, flight path angle, and boundary threshold parameters, the suggested work aims to provide a comparative analysis of sampling algorithm-based optimal path. The proposed route planning control strategy is to identify the violation free path to locate the destination in 3D environment at variable altitude and air speed. Compared to the standard RRT and RRT* algorithms, the proposed IRRT* algorithm can shorten the planning time, reduce the cost distance and improve the algorithm’s applicability in the formation path planning problem. Simulation experiments with two environments and their different situations are carried out to determine the efficiency and performance of the proposed IRRT* algorithm. Statistical investigation supported the effectiveness of the IRRT* approach, which has low computational cost and a smooth travel trajectory that significantly resolves the unmanned aerial vehicle path planning issues in logistic applications.

Introduction: Acid peptic disorder (APD) is a condition which includes peptic ulcer and gastro esophageal reflux disease (GERD). The highest prevalence rate of gastric disorders had been found out between ages 45-50. Dyspepsia is a term used for reduced digestion or indigestion. GERD is referred to as condition where there is regurgitation of stomach contents to the esophagus. Around 58.7% of peoples are having acid regurgitation or heart burn yearly once and 19.8% weekly once. Worldwide functional gastrointestinal disorder are commonest now a days, Irritable Bowel Syndrome (IBS) is also one among them having frequent pain abdomen and altered bowel habits without any structural gut abnormalities. Homoeopathy is a system which is based on individualization, and has principles of “Like cures like” and law of nature. Materials and methods: A retrospective study had been conducted with those patients who had attended the gastroenterology OPD of NHRIMH, Kottayam, Kerala, for a period of 1 year (from January 2022 to December 2022). Data had been collected from the case records and it had been found that around 899 patients had visited for the symptoms like nausea, vomiting, abdominal pain, altered bowel movements (diarrhea and constipation), bleeding per rectum, dysuria and hesitancy in urination,etc for the past 1 year. Aim of the study is to find out the most frequent age group, diseases affected and to know the frequently indicated remedies in treating gastroenterology disorders. Results: 899 patients visited in the defined period with a highest number of patients (212) were from the age group of 51-60, female patients were more than male patients, 758 old patients and 141 new patients. 214 pateints had diagnosed as gastritis which is the highest frequency noted. The most frequently indicated remedies were Nuxvomica in 161 patients and Suphur in 118 patients. Conclusion:It is concluded from the study that gastritis is the most common condition among patients visiting the above OPD in the defined period and Nux vomica, Sulphur and Lycopodium were the most common indicated and prescribed remedies.

Gastrointestinal disorders are the one of the attention seeking conditions in day to day life which affects 10- 15% of total population. Gastrointestinal Symptom Rating Scale (GSRS) is a tool used to measure the severity and gradation of dyspepsia. Infections, gastrointestinal motor abnormalities, brain-gut interaction, visceral hypersensitivity, inflammation, central neural dysregulation, altered gut flora are main reasons for gastrointestinal disorders. Common presentations of gastro intestinal disorders are nausea, vomiting, heart burn, dyspepsia, pain abdomen, flatulency, bowel movement alteration (constipation, diarrhoea) and bleeding per rectum.Homoeopathy is asystem of medicine which is based on “Similia Similibus Curentur” and with the combination of constitutional prescription and law of similars the normal harmonious health will be maintained in all the patients.

Introduction: Gastro intestinal diseases are the most common disorders seen worldwide. Microbiota is a term used for eukaryotic and prokaryotic microorganisms. In case of infected persons, it can produce symptoms like diarrhea, vomiting, nausea, flatulency, pain abdomen, inflammation of intestine, etc. The most common presentations of Gastro intestinal disorders are heart burn, nausea and vomiting, dysphagia, indigestion, chronic recurrent pain abdomen, flatulency, belching, loss of weight, etc. Homoeopathy is a system where symptom similiarity and individualization is considered in remedy selection.The vulnerability and frequency of disease will decrease when medicine prescribed is based on individualization. This is a retrospective study analyzing the previous case history to assess the efficacy of homoeopathy in gastrointestinal disorders. Materials and Methods: Case records of 261 patients diagnosed with gastrointestinal disorders with symptoms like pain abdomen, nausea, vomiting, heart burn, flatulence, diarrhea, bleeding per rectum, dysuria, hesitancy in urine etc. who had visited OPD of NHRIMH Kottayam Kerala from January 2022 to May 2022 (5 months) had been retrospectively analyzed to find out the most common gastrointestinal disorders and frequently indicated useful remedies in managing the patient. Results and Discussion It has been found that in our study maximum affection is in the age group of 51-60 and least in the age group of 91-100. Females were most affected than males. 45 new patients and 216 old patients had visited. The most common gastro intestinal disorders for which patients visited were Cholelithiasis, Gastritis and GERD.Most frequently indicated medicines were Nux vomica (20.69%), Sulphur (16.48%), Bryonia (9.96%), Argentum nitricum (9.58%) and Lycopodium (9.20%).The study showed drastic improvement in all the patients which proves that homoeopathy is highly effectivein gastrointestinal disorders. Conclusion From the above retrospective study, it is clear that when the homoeopathic principles were followed properly in treating a patient we can arrive at a permanent cure in all patients without any side effects.

Background: Prevalence of Anemia is reported to be as high as about 90% in some segments of the population in India. Dharavi is arguably the largest slum in Asia. Due to its socioeconomic status, there is a possibility of malnutrition in this area. We have surveyed the area for the prevalence of anemia in Dharavi. Methods: The status was assessed with the help of Local Laboratories at Dharavi. Children from 5 to 15 years of age were surveyed from 7 different areas of Dharavi. Their name, age, gender, contact number and the hemoglobin level were collected in the survey and analysed based on WHO criteria of mild (11 – 11.4 g/ dL), moderate (8.1 – 10.9 g/dL) and severe anemia (

Autonomous transportation is a new paradigm of an Industry 5.0 cyber-physical system that provides a lot of opportunities in smart logistics applications. The safety and reliability of deep learning-driven systems are still a question under research. The safety of an autonomous guided vehicle is dependent on the proper selection of sensors and the transmission of reflex data. Several academics worked on sensor-based difficulties by developing a sensor correction system and fine-tuning algorithms to regulate the system’s efficiency and precision. In this paper, the introduction of vision sensor and its scene terrain classification using a deep learning algorithm is performed with proposed datasets during sensor failure conditions. The proposed classification technique is to identify the mobile robot obstacle and obstacle-free path for smart logistic vehicle application. To analyze the information from the acquired image datasets, the proposed classification algorithm employs segmentation techniques. The analysis of proposed dataset is validated with U-shaped convolutional network (U-Net) architecture and region-based convolutional neural network (Mask R-CNN) architecture model. Based on the results, the selection of 1400 raw image datasets is trained and validated using semantic segmentation classifier models. For various terrain dataset clusters, the Mask R-CNN classifier model method has the highest model accuracy of 93%, that is, 23% higher than the U-Net classifier model algorithm, which has the lowest model accuracy nearly 70%. As a result, the suggested Mask R-CNN technique has a significant potential of being used in autonomous vehicle applications.

A compact triple band antenna with stacked T-shaped strips inside a rectangular ring monopole has been proposed. This novel structure with a slot in the defected ground achieves triple band opration i.e. 2.47–2.77 GHz, 3.3–3.7 GHz and 5.10–6.62 GHz. These bands find application in important wireless communication standards like WiMAX (3.3–3.8 GHz, and 5.25–5.85 GHz, WLAN (2.4 G-2.5 GHz, 5.1–5.3 GHz, and 5.72–5.85 GHz). The antenna is printed on a FR-4 substrate with an overall dimension of $$33 \times 17 \times 1.6 \;{\text{mm}}^{3}$$ 33 × 17 × 1.6 mm 3 . An impedance bandwidth of 11% (2.47–2.77 GHz), 11% (3.3–3.7 GHz) and 25% (5.10–6.62 GHz) is obtained. A good conjunction between the simulated and measured results is inferred from the antenna design analysis.

Coronavirus Disease 19 (COVID-19) is a highly infectious viral disease affecting millions of people worldwide in 2020. Several studies have shown that COVID-19 results in a severe acute respiratory syndrome and may lead to death. In past research, a greater number of respiratory diseases has been caused by exposure to air pollution for long periods of time. This article investigates the spread of COVID-19 as a result of air pollution by applying linear regression in machine learning method based edge computing. The analysis in this investigation have been based on the death rates caused by COVID-19 as well as the region of death rates based on hazardous air pollution using data retrieved from the Copernicus Sentinel-5P satellite. The results obtained in the investigation prove that the mortality rate due to the spread of COVID-19 is 77% higher in areas with polluted air. This investigation also proves that COVID-19 severely affected 68% of the individuals who had been exposed to polluted air.

Attributable to the modernization of Artificial Intelligence (AI) procedures in healthcare services, various developments including Support Vector Machine (SVM), and profound learning. For example, Convolutional Neural systems (CNN) have prevalently engaged in a significant job of various classificational investigation in lung malignant growth, and different infections. In this paper, Parallel based SVM (P-SVM) and IoT has been utilized to examine the ideal order of lung infections caused by genomic sequence. The proposed method develops a new methodology to locate the ideal characterization of lung sicknesses and determine its growth in its early stages, to control the growth and prevent lung sickness. Further, in the investigation, the P-SVM calculation has been created for arranging high-dimensional distinctive lung ailment datasets. The data used in the assessment has been fetched from real-time data through cloud and IoT. The acquired outcome demonstrates that the developed P-SVM calculation has 83% higher accuracy and 88% precision in characterization with ideal informational collections when contrasted with other learning methods.

The increased demand and depletion of the fossil fuels for power generation led to the need for extracting power from the renewable energy resources (RERs). The microgrids (MGs) are designed with the help of effective power extracted from renewable sources such as solar, wind, tidal, and geothermal. The advent of DC MGs overcomes the conventional AC grids. The hybridization of the AC and DC MGs will provide more advantages for various levels of consumers. This article proposes the design and modeling of a hybrid DC/AC MG with the efficient use of RERs and it can reduce numerous power conversions. The solar energy is extracted through photovoltaic (PV) panels meritoriously using interval type 2 fuzzy logic technique as the maximum power point tracking algorithm. The AC grid is designed using wind energy source and tidal energy. The permanent magnet synchronous generator is used as the wind turbine. Various control mechanisms are employed in order to extract maximum power from the wind and tidal waves at varying conditions. These generated powers can supply the load and are connected to the utility grid. These are executed with the aid of MATLAB/SIMULINK software.

In this study, a heuristic algorithm is used to find an optimal route for smart logistics loading and unloading applications. Various environments, such as traditional building blocks, satellite images, terrain environments, and Google map environments are developed by converting into a binary occupancy grid and used to optimize the viable path in the smart mobile logistics application. The proposed autonomous vehicle (AV) route planning navigation approach is to forecast the AV’s path until it detects an imminent obstacle, at which point it should turn to the safest area before continuing on its route. To demonstrate the path navigation results of proposed algorithms, a navigational model is developed in the MATLAB/Simulink 2D virtual environment. The particle swarm optimization (PSO) method, the Bat search algorithm, and its proposed variants are used to identify a smooth and violation-free path for a given application environment. The proposed variants improve the algorithm’s effectiveness in finding a violation-free path while requiring less time complexity by using cubic spline curve interpolation and its improved constriction factor. Extensive simulation and benchmark validation results show the proposed standard PSO has a significantly shorter violation-free path, quick convergence rate and takes less time to compute the distance between loading and unloading environment locations than the cooperative coevolving PSO, Bat algorithm, or modified frequency Bat algorithms.

Operating wind power generation system at optimal power point is essential which is achieved by employing a Maximum Power Point Tracking (MPPT) control strategy. This literature focuses on developing a novel particle swarm optimization algorithm enhanced radial basis function neural network supported TSR based MPPT control strategy for Doubly Fed Induction Generator (DFIG) based wind power generation system. The proposed hybrid MPPT control strategy estimates the effective wind speed and estimates the optimal rotor speed of the wind power generation system to track the maximum power. The proposed controller extremely reduces the speed dissimilarity range of wind power generation system, which leads to rationalizing the pulse width inflection of DFIG rotor side converter. This in turn, increases the system's reliability and delivers an effective power tracking with reduced converter losses. Furthermore, by utilizing the proposed MPPT controller, the converter size can be reduced to 40%. Therefore, the overall cost of the system can be gradually decreased. To validate the performance of the proposed MPPT controller, an extensive simulation study has been carried out under medium and high wind speed conditions in MATLAB/Simulink. The obtained results have been justified using experimental analysis.

In this article, photonic crystal (PhC) based all-optical logic gates, namely AND, OR and EX-OR have been explored and their characteristics are reported. Two-dimensional (2D) PhC based logic gates are proposed using a hexagonal lattice with T-shaped structure by incorporating line defects. The total size of the device is 84 µm2 and it operates at a wavelength of 1550 nm (C band). The designed optical logic gates are investigated using 2D finite difference time domain simulators by means of the plane wave expansion method. Parameters, such as response time and contrast ratio of the designed all-optic logic gates, are analyzed. The proposed AND, OR and EX-OR logic gates offer a contrast ratio of 14.48 dB, 14.57 dB and 12.9 dB respectively with, in order, response times of 0.159 ps, 0.168 ps and 0.1672 ps. The designed logic gates work in the third optical window as they are operating at the 1550 nm wavelength. To specify the performance of the proposed logic gates, their field distribution has been determined and is exhibited. The designed logic gates are suitable for use in photonic integrated circuits, all optical computing and optical sensing applications.

Piezoelectric Energy Harvesting Systems play a vital role in energizing microelectronic devices with the low-frequency operation. Here, a novel piezoelectric energy harvesting device has been developed for low power electronic devices. The developed Piezoelectric Energy Harvesting Systems consists of a cantilever with poles projecting outwards and the cantilevers one end is connected to the wind-catcher, and another end is connected to the torsional spring. The developed Piezoelectric Energy Harvesting Systems signifies its application in energizing microelectronic devices. The cantilever is placed inwards to the piezoelectric crystal stack. When the wind strikes, a vortex is created in the windcatcher, which oscillates the cantilever and generates stress in the piezoelectric crystal stack to develop electric energy. The output voltage obtained from the Piezoelectric Energy Harvesting Systems does not affect any input frequency of the piezoelectric crystal. The result obtained shows that the developed Piezoelectric Energy Harvesting Systems generates 120–200 eV with 2.9 × 1016–4.84 × 1016 Hz frequency considering an elementary charge unit as 40 for a variable wind flow of 4–9 m/s. This research aims to develop an efficient wind-based Piezoelectric Energy Harvesting Systems for low powered microelectronic devices.

This literature presents an improved maximum power point tracking (MPPT) controller based on radial basis function neural network (RBFNN) control strategy to extract optimal power for wind power ge...

Torque ripple and harmonics in permanent magnet synchronous motor (PMSM) cause negative impacts on its speed control and overall efficiency. In this article, an Elman neural network (ENN)-controlled feedback linearization-based direct torque control strategy has been proposed to mitigate torque ripples and undesirable harmonics of PMSM. In this approach, the stator flux, stator flux position, and developed torque are used to generate a switching pulse to the impedance source inverter employing ENN controller. By changing the switching pattern of the impedance source inverter through modifying the pulse width modulation using the proposed control strategy. It is possible to control the armature current of the PMSM at various orders and corresponding time harmonics under different operating conditions. The outstanding aspect of the proposed control strategy is that it boosts the inverter operation and reduces the requirement of the DC-DC converter in boosting. For evaluating the performance of the developed control strategy, an extensive simulation study has been conducted in the MATLAB/Simulink environment, and experimental analysis is carried out using the Xilinx-FPGA kit.

Purpose Corona Virus Disease 2019 (COVID-19) is a deadly virus named after severe acute respiratory syndrome coronavirus 2; it affects the respiratory system of the human and sometimes leads to death. The COVID-19 mainly attacks the person with previous lung diseases; the major cause of lung diseases is the exposure to nitrogen dioxide (NO2) for a longer duration. NO2 is a gaseous air pollutant caused as an outcome of the vehicles, industrial smoke and other combustion processes. Exposure of NO2 for long-term leads to the risk of respiratory and cardiovascular diseases and sometimes leads to fatality. This paper aims to analyze the NO2 level impact in India during pre- and post-COVID-19 lockdown. The study also examines the relationship between the fatality rate of humans because of exposure to NO2 and COVID-19. Design/methodology/approach Spatial analysis has been conducted in India based on the mortality rate caused by the COVID-19 using the data obtained through Internet of Medical things. Meanwhile, the mortality rate because of the exposure of NO2 has been conducted in India to analyze the relationship. Further, NO2 level assessment is carried out using Copernicus Sentinel-5P satellite data. Moreover, aerosol optical depth analysis has been carried out based on NASA’s Earth Observing System data. Findings The results indicate that NO2 level has dropped 20-year low because of the COVID-19 lockdown. The results also determine that the mortality rate because of long-time exposure to NO2 is higher than COVID-19 and the mortality rate because of COVID-19 may be a circumlocutory effect owing to the inhalation of NO2. Originality/value Using the proposed approach, the COVID-19 spread can be identified by knowing the air pollution in major cities. The research also identifies that COVID-19 may have an effect because of the inhalation of NO2, which can severe the COVID-19 in the human body.

In this chapter, the role of conductive oxides in the fabrication of flexible electronic devices and their applications are reported elaborately. Due to changes from the rigid electronic world to flexible electronics, the researchers have started working on the materials, deposition technologies, and device fabrication in connection to the fabrication of flexible electronic devices. Flexible and printed electronics are lightweight materials that support portable displays, curved displays, and flexible or roll-up designs that can be manufactured using a roll-to-roll manufacturing process. Limited products such as curved televisions, bendable displays, and flexible antennas are available in the markets, but still a lot of issues have to be overcome in order to fulfill the dream of a flexible electronic world. Conductive oxides, which are considered as a backbone of flexible electronic devices, have challenges such as low conductivity, poor adhesive, instability, and high-temperature deposition, which have to be addressed. In this connection, this chapter deals with the deposition of conductive oxides in the flexible substrate and their role in the application of flexible electronic devices. Also, the issues and challenges faced during the deposition of the conductive oxides on the flexible substrate are also discussed in detail.