Nowadays, a lot of people indulge themselves in the world of social media. With the current pandemic scenario, this engagement has only increased as people often rely on social media platforms to express their emotions, find comfort, find like-minded individuals, and form communities. With this extensive use of social media comes many downsides and one of the downsides is cyberbully. Cyberbullying is a form of online harassment that is both unsettling and troubling. It can take many forms, but the most common is a textual format. Cyberbullying is common on social media, and people often end up in a mental breakdown state instead of taking action against the bully. On the majority of social networks, automated detection of these situations necessitates the use of intelligent systems. We have proposed a cyberbullying detection system to address this issue. In this work, we proposed a deep learning framework that will evaluate real-time twitter tweets or social media posts as well as correctly identify any cyberbullying content in them. Recent studies has shown that deep neural network-based approaches are more effective than conventional techniques at detecting cyberbullying texts. Additionally, our application can recognise cyberbullying posts which were written in English, Hindi, and Hinglish (Multilingual data).
Processing of citrus fruits results in production of a large amount of by product and a major part of this by product is its peels. These peels have the potential of acting as a good nutraceutical resource owing to its high dietary fibre content and phenolic content. However, these peels are under-utilised despite their claimed health benefits. This study evaluates the morphological structure, functional properties and sensory attributes of sweet lime peel and orange peel powder with a aim of providing an economical ingredient for the development of functional foods. Peels of sweet lime and orange were transformed into powder through solar drying followed by grinding. In the present study, we have compared the morphology and organoleptic constituents of orange peel powder (OPP) and sweet lime peel powder (SLPP). The morphology of the two samples was studied by SEM and element composition was studied and analysed by EDX. Organoleptic and sensory attributes were analyzed by a 9 pointer hedonic scale rating. Peel powders were also compared for two functional properties i.e. their Solubility Index and Swelling Power. Orange peel powder (OPP) had a better sensory rating than Sweet lime peel powder (SLPP). The morphology of both powders was same but SLPP had a slightly rough texture than OPP.
As we know,shaking due to seismic waves causes damage to buildings. The damage maybe influenced by the characteristics of soil in the affected area.The objective of the paper is to show the effect of the earthquake on different types of foundations such as shallow, mat/raft, pile and structures like gravity dam, arch dam etc. The reaction of soil to the loading of the building when a building undergoes an earthquake disturbance as a behaviour of deflection is known as the soil structure interaction. The movement of ground during theearthquake induces kinematic and inertial loading which decreases the bearing capacity and increments the settlement of shallow foundations. In seismic regions, where kinematic interactions have been observed, the mat foundations experiences overturning moments. Pile foundations are influenced by both kinematic and inertial interactions which causes many failures. The convoluted oscillating arrangement of acceleration and ground motion in a gravity dam,developing ephemeral dynamic loads because of inertia of dam and confined water is the seismic activity generated in these dams. The arch dam foundations undergoes effects of inertia and flexibility due to the propagation of seismicwaves.
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