Weather forecasting refers to the prediction of atmospheric conditions depending on a given time and location. Weather prediction is essential and it plays a significant role in many sectors namely energy and utililities, marine transportation, aviation, agriculture and forestry to a greater extent. Accurate weather forecast mechanism help the farmers for suitable planning of farming operations that will prevent crop losses. In this work, the weather parameters namely precipitation, relative humidity, wind speed and solar radiation were predicted for few Indian locations using the conventional temperature based empirical models and machine learning algorithms such as linear regression, support-vector machine (SVM) and decision tree. Forecasting of weather parameters, on which agriculture depends, will increase the overall yield and it helps farmers and agricultural-based businesses to plan better. From the current results, it is observed that machine learning (ML) based methods had a better prediction results than the physics based conventional models for weather forecasting with mean square error of 0.1397 and correlation coefficient of 0.9259. The objective of this work is to arrive at an optimized end result and a better weather prediction using the Machine learning models with lesser computational effort.

Background: In the dental field, many people undergo an extreme fear of injections, which is referred to as trypanophobia. The medical procedures that involve injections in the dental field to create numbness raises a certain level of discomfort to all of the patients to an extent that the patients avoid treating their teeth or show an anxious or avoidance behavior. Hence, needle phobia is one of the more common phobias amongst people but was not officially recognized as a phobia in dentistry for a long time. In rural areas, some patients, mainly elderly people, might go away without treating their damaged tooth due to fear of injections. Aim: Thus, setting this as the major point of consideration, the researchers have put forth a new concept of dental treatment of creating desensitization without injections rather by adopting a new concept as “iontophoresis”, which causes the ions of specific charges to penetrate the semipermeable membrane, which helps in performing surgeries in the dental field. In the present manuscript, the ‘iontophoresis’ method, along with the imaging systems, was adopted and 45 tooth samples were taken and tested with four different ionic gels that are used in the dental field, and the results were analyzed using the imaging systems of SEM and EDAX for clear analysis. Results: The results through these imaging systems show that the ions have penetrated the tooth, which causes a desensitizing effect in the tooth and makes it numb, so that dental operations can be performed easier and with more perfection. The process of performing dental surgery with a needless process is that the patient to be treated by the dentist is exposed to a gel with electrodes wherein the ions penetrate the tooth, which causes numbness. Conclusion: The incorporation of needle-free injection through the concept of iontophoresis and imaging systems in the dental field introduces a new era in the field of dentistry, making the process simple.

Weather balloons are high-altitude meteorological balloons particularly used for carrying scientific payloads into the upper atmosphere. These data are obtained by using an instrument called as radiosonde which is attached to the helium filled weather balloon to measure the meteorological data as it ascends up into the atmosphere. For more than 100 years, weather balloons have given valuable information for climate and meteorological research. In this paper, the radiosonde module is designed with negligible risk of failure and cost effectiveness. The instruments to be fixed along with the weather balloon are logging camera, temperature sensor, pressure sensor, humidity sensor, global positioning system (GPS) module and a power source. This module is used to measure and log the basic weather parameters such as pressure, temperature, humidity and this also captures the picture of a particular locality with the help of a microcontroller. This proposed work is useful for observing high altitude weather data which is essential for predicting natural disasters. Further more, it is helpful to analyze the climatological and weather details of a particular region it also plays an important role in estimating agricultural models.