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A six-port MIMO antenna system for forthcoming mobile applications (Sub 6 GHz) is presented in this paper. Four F-shaped antenna elements are placed at four extreme corners and two at the middle si...

A dual-band 10-port multiple input multiple output (MIMO) antenna array for 5G smartphone is proposed. Each antenna in the MIMO system can work from 3.4 to 3.6 GHz and 5 to 6 GHz with 10 dB (2:1 VSWR) impedance bandwidth. Nevertheless, for a 3:1 VSWR, the antenna operates from 3.3 to 3.8 GHz and 4.67 to 6.24 GHz. The MIMO system is formed by making 10 seven-shaped coupled fed slot antenna elements excited at two different resonant modes and integrated into the system circuit board. By implementing the spatial and polarization diversity techniques, high isolation better than 28 dB between any pair of antenna elements is achieved. The proposed 10-port MIMO antenna array is fabricated and measured. Significant radiation efficiency is obtained, ranging from 65 to 82% for both bands. The antenna gain in the required operating band is substantial, around 3–3.8 dBi. Further, the MIMO parameters such as envelope correlation co-efficient, channel capacity, and total active reflection co-efficient are calculated. The antenna's robustness is estimated by analyzing the user hand effects and specific absorption rate (SAR). The measured results are well agreed with the simulated results.

A ferrite-based four-port circulator is designed using two three-port circulators to operate at ultra-high frequency 3 GHz – 5 GHz. A ferrite disk of 1.5 mm thickness and 13.5 mm in diameter is incorporated into the circulator design. The internal magnetic field of 1380 Oersteds and saturation magnetization (4$\pi$M) of 3900 Gauss is applied onto the ferrite disk for anticlockwise oriented magnetic field rotation. Maximum isolation of 27.6 dB and insertion loss of 23.1 dB is obtained at 3.5 GHz, which lies in the 5G band of communication. Further, the parametric study is conducted to observe the variation in characteristics of a circulator.

This paper presents a compact multi-band microstrip antenna for Radar Cross Section reduction. The antenna comprises several microstrips to act as the main radiator. The proposed antenna is printed on 8.4 mm thick FR-4 substrate. The antenna can cover the frequency spectrum 1.2 GHz (358 MHz bandwidth), 1.8 GHz (573 MHz bandwidth), and 3.8 GHz (130 MHz bandwidth) in the 2:1 VSWR ratio. The proposed antenna has a stable and Omni-directional radiation pattern in all three bands of operation. The antenna is simulated using Keysight’s Advanced Design System (ADS), Electromagnetic Professional (EMPro) software. The antenna parameters like S-parameters, radiation pattern, efficiency, gain and directivity have been measured. The results show that the proposed antenna is a promising candidate for radar cross section reduction.

In this paper, we present U-shaped patch antenna with meander slot. The objective of the proposed antenna is for biomedical application. The operating frequency of the proposed antenna is 2.45 GHz. The designed antenna is of compact size of 35*25*1.5 mm3 with FR4 substrate which is possible by meandered slot. It is demonstrated that the antenna with meandered slots reveals low return loss at perfect resonant frequency which is suitable for bio medical applications. The bio medical application needs compact size of the antenna, which is attained by placing meandered slots above the surface of the radiating patch. The antenna simulation is carried out by advanced design system simulator.

Background: Toothbrush is habitually used as an oral hygiene aid to maintain good oral health. The contamination of toothbrushes leads to oral and systemic diseases. Awareness on toothbrush disinfection is essential for oral health-care professionals in order to educate people. Aim: The aim was to assess the knowledge, perceptions, and practices about toothbrush storage, contamination, and disinfection among dental professionals in Andhra Pradesh, South India. Materials and Methods: A cross-sectional study was conducted using a self-administered questionnaire among 450 oral health professionals categorized into three groups (faculty, postgraduates, and interns) in Andhra Pradesh. The statistics were computed with the Statistical Package of Social Sciences version 22. Chi-square test and analysis of variance were used for statistical analyses. P < 0.05 is considered statistically significant. Results: There was a statistically significant difference between the three groups regarding the P value denoted by (*) is considered as statistically significant, frequency of brushing, change of toothbrush, storage of toothbrush and knowledge on toothbrush disinfection (P value is 0.01), whereas knowledge on toothbrush contamination (P value is 0.04). P value denoted by (**) is considered as statistically highly significant. A highly statistical significance was noticed pertaining to the factors on type of toothpaste,reason behind change of toothbrush,contact between toothbrushes during storage and sharing of toothpaste with family members ( P value is

Big data is used to express the data in huge volume either structured or unstructured and is in an increasing state with respect to a business or historical records on an everyday basis. Analyzing huge level of data and identifying decision are vital process in dato day social activities, improvements in future prediction and analysis based on historical records and so on. This helps in Organizations to achieve consistency and higher accuracy on future works and prediction of data. Data management through the traditional approach is tedious process and the processing is also difficult task. Health data is one of the important dataset. The volume of Healthcare data includes variable content sorts, sounds, and pictures and is expanding every day. In this way, the capacity and preparing of the medical information is an important. In this paper, author discussed the importance of the bid data in medical science and the research opportunity in big data. It results the doctor to take Clinical Decision Support.

Disaster management is essential today as atmospheric condition stay unpredictable resulting in numerous natural disasters. Effect of disaster could be reduced by dissemination of disaster alert to a specific radius. The goal of disaster management is to make sure reliable, energy economical communication that is done at the earliest. Vehicular Ad hoc Network (VANET) is effectively used to communicate this disaster alert knowledge. Both Vehicle-to-Vehicle (V2V), Vehicle-to-Infrastructure (V2I) communication can be used to disseminate the messages. This work presents a study of literature for disaster management using VANET.

In the current world, one of the most predominant issues identified from children to older adults is hearing loss and it turns the attention of research community. The people identified with permanent sensori-neural hearing loss are required to use amplification devices, which is the most manageable option for them. This study brings out the causes and effects of hearing loss among teenagers and older adults and discusses the current IoT enabled techniques which provide the solution for hearing loss.

Tolvaptan (TVT) is a selective, competitive vasopressin receptor 2 antagonist used to treat hyponatremia. TVT was subjected to forced degradation under hydrolysis, oxidation, dry heat and photolysis conditions, in accordance with the ICH guideline Q1A (R2). The degradation products (DPs) formed have been characterized through UPLC-PDA and UPLC-Q-TOF-MS/MS studies. The chromatographic separation was achieved on an Acquity UPLC HSS T3 column (100 × 2.1 mm, 1.7 μm) with a mobile phase containing a gradient mixture of solvents A (0.1% formic acid) and B (acetonitrile) at a flow rate of 0.3 ml min−1 at 30 °C. The detection wavelength was set at 266 nm. The drug degraded under acid hydrolysis, base hydrolysis and oxidative conditions to form a total of 7 DPs. When methanol was used as the co-solvent during stress degradation, four additional DPs were formed which were absent when acetonitrile was used as the co-solvent. Comparison of the fragmentation pattern of the DPs with that of the drug helped in the elucidation of the structures of all the degradation products. The degradation pathway of the drug was established, which was duly justified by the mechanistic explanation. The developed UPLC method was validated as per ICH guidelines.

Due to inadequate energy resources, data aggregation from multiple sensors in Wireless Sensor Networks (WSN) is typically accomplished by clustering. But such data aggregation is recognized to be highly susceptible to clone attacks owing to the unattended nature of the network. Thus, ascertaining trustiness of the sensor nodes is crucial for WSN. Though numerous methods for cloned attack node isolation are provided in recent years, energy efficiency is the most significant issues to be handled. In this work, a Residual Energy and GSA based Simulated Annealing (RE-GSASA) for detecting and isolating the cloned attack node in WSN is given. Residual Energy-based Data Aggregation in WSN initially uses residual energy because the basis to perform aggregation technique with the sensor node possessing the maximum residual energy as the Cluster Head (CH). Next, Location-based Cloned attack on cluster nodes is given to enhance the clone detection probability rate. Here, the location and residual energy is taken into account to identify the presence of cloned attack nodes within the network. Finally, Gravitational Search Algorithm with global search ability is investigated to identify the cloned attack nodes and performs isolation through local optimal simulated annealing model. Simulation results demonstrate that RE-GSASA provides optimized energy consumption and improves cloned attack detection probability by minimizing the cloned attack detection time.

The retinal image diagnosis is an important methodology for diabetic retinopathy detection and analysis. in this paper, the morphological operations and svm classifier are used to detect and segment the blood vessels from the retinal image. the proposed system consists of three stages-first is preprocessing of retinal image to separate the green channel and second stage is retinal image enhancement and third stage is blood vessel segmentation using morphological operations and svm classifier. the performance of the proposed system is analyzed using publicly available dataset.

In order to organize the sensor nodes in a wireless communication network and to route the sensed information from the field sensors to a remote base station various techniques are available. The major problem of the sensor network is to increase the lifetime of the sensor nodes. For this reason many protocols have been established. In this paper we presents a new energy efficient clustering technique for large-scale sensor networks. By monitoring the received signal about power from its neighboring nodes, each node estimates the number of active nodes in real time and computes its optimal probability of becoming a cluster head. The goal is to select cluster heads that minimize transmission costs and energy usage. Based on the clustered architecture, we propose a new Energy Efficient Clustering Algorithm for the efficient Cluster Head selection by using a Cluster Manager (CMR). When compare to existing work the proposed technique work efficiently and reduces the energy consumption of sensor nodes.