This paper explores the usage of games to practice vocabulary in the teaching of English to young learner. Teaching vocabulary `through games was chosen as the focus area to enhance the interest of young learners to learn communication. Firstly, through the observation during course of my teaching practice at EFLU, I learned about usage of vocabulary and cultivate the interest in the mind of young learners through the games. The study was conducted with twenty-nine students in a junior college. According to my observation of how vocabulary is taught in colleges, it relies on drilling the vocabulary to get the students to produce the correct pronunciation of words. Other strategies such as implementing games are very occasionally used to teach vocabulary; however, they are only used for a limited to me. Using games is considered time consuming, so teachers prefer to use drilling as an immediate way of teaching and practicing vocabulary. In English class, students are encouraged to speak in English when they answer, and while they interact with their classmates. Translation is generally avoided, but it is sometimes used to clarify difficult linguistic concepts, and also to clarify meaning.

This work's primary goal was to formulate and assess an emulgel using extracts from Curcuma longa, Nigella sativa seeds, and aloevera while also examining the extract's microbiological activity and various characterizations. Curcuma longa is a member of the Zingiberaceae family. Turmeric, or Curcuma longa, is widely recognized. Curcuma longa comprises volatile oils and three primary curcuminoids: curcumin, demethoxycurcumin, and bisdemethoxycurcumin.Black cumin, or Nigella sativa Linn (Ranunculaceae), has a variety of pharmacological properties, including as anti-inflammatory, antibacterial, antifungal, and antihelmenthic properties.Succulent tropical plant Aloe barbadensis is a member of the Liliaceae family.Aloe vera gel is used to treat psoriasis by minimizing scaling and redness. It is used to create lotions and creams for topical use. In addition, aloe vera possesses anti-inflammatory, antioxidant, immunomodulatory, anti-fungal, and anti-tumor qualities. By raising collagen activity, it also facilitates wound healing and skin hydration. This helps to repair the detrimental effects of psoriatic skin.

Concrete is a principal building material used all over the globe. Concrete’s tensile strength is weak while its compressive strength is high. This necessitates the use of steel as a reinforcement material to make it strong in tension. –Steel is costly and easily corroded thereby leading to structure decay. Because of this, concrete can be replaced with bamboo because of their properties such as light weight, high strength, durable and easily renewable.-So that Bamboo replaces steel which was commonly used in construction industries for reinforcement purposes by traditional methods-The truth is that bamboo is an indigenous, affordable and plentiful resource.—Also It has necessary deflection and tensile strength—Bamboo reinforcement reduces the mid span deflections-Lastly performance of bamboo will be compared with that of steel so as to get the best result.

The Innovation of New Communication Technology - Aurora Guard Smart Watch epitomizes a ground breaking fusion of advanced communication and wearable technology. By harnessing the captivating patterns of the aurora borealis and aurora Australia, this smartwatch introduces a dynamic communication system with unparalleled security features. The use of aurora-based communication ensures a secure and globally connected experience, transcending the limitations of traditional networks. Key features include seamless connectivity with global coverage, enabling users to stay connected in remote or challenging environments. The smartwatch prioritizes health monitoring through real-time tracking of vital signs, sleep patterns, and physical activity, offering users a comprehensive wellness companion. Customizable watch faces, a dynamic display, and an energy-efficient design contribute to a unique and sustainable user experience. Implications for personal communication encompass heightened security, expanded connectivity in areas with limited network coverage, and reliability in emergency situations. The smartwatch's integration of communication and health features positions it as a transformative wearable device. As technology advances, the Aurora Guard Smart Watch serves as a catalyst for innovation, offering a glimpse into the future of seamlessly integrated, secure, and holistic wearable technology.

Due to its advantageous qualities, which include a high strength-to-weight ratio, light weight, high thermal property values, and resistance to corrosion, aluminium and its alloys are widely employed in a variety of sectors worldwide. On the other hand, some of the backgrounds are low part properties, including hardness and wear resistance. Advanced composite materials reinforced with one or more elements to create a distinctive combined effect are called Metal Matrix composite materials. This approach permits a greater degree of material design limit extension. In this current study, the main objective of this work was to evaluate physical and mechanical properties experimentally and numerically using finite element modelling (FEM). Iron nano particle and hydroxyapatite reinforced into aluminum 6061 alloy composites are fabricated simultaneously by adopting stir casting approach by changing weight percentages of filler powder from 0.0 wt.%, 1.00 wt.%, 1.5wt.% . On the opposite hand, fabrication of composite numerically was done through ANSYS Workbench 2020 R2. In result, void percentage of AA 6061 composites varied from 0.77 to 1.73 for 0 to 1.5 weight percent when filler was introduced and micro-hardness value raised from 13.9 HB to 24 HB with the increasing nano filler amount. Dry sliding wear tests were conducted for iron nano and hydroxyapatite filled alloy composites and there after implementing Taguchi approach at four distinct loads (30N – 60N), sliding speed ( 30 rpm – 60 rpm), Test run time duration (10-25 min) and filler powder weight percentages (0 wt.% - 1.5 wt.%) respectively using pin-on-disc machine. Finally, for finding some other characteristic properties mechanism of composite and for numerical approach the Finite Element Analysis was performed by using ANSYS 20.0 and various stresses such as maximum principal stresses, Von- Mises stresses, directional deflection, total deformation, and penetration, contact pressure surfaces, occurred throughout operating condition were evaluated.

This study explores the potential of various machine learning models in enhancing the security of banking applications by detecting and mitigating security threats. The comparative analysis of models such as ML based algorithms provides valuable insights into their effectiveness and suitability for real-world deployment. As the banking sector continues to face sophisticated cyber threats, the integration of machine learning models offers a promising avenue for strengthening security measures and safeguarding financial assets. This paper evaluates the effectiveness of various machine learning models in detecting security threats within banking applications. The models assessed include Random Forest, Decision Tree, K-Nearest Neighbours, AdaBoost, SGD Classifier, Extra Trees Classifier, and Gaussian Naive Bayes. Results demonstrate that Random Forest, SGD Classifier, Extra Trees Classifier, and Gaussian Naive Bayes achieve perfect accuracy, making them highly suitable for real-world deployment. Decision Tree, K-Nearest Neighbours, and AdaBoost also perform well, though slightly less accurately.

This paper provides a comprehensive review of the integration of machine learning (ML) techniques in the detection and prediction of infectious diseases, focusing on malaria and Covid-19. It evaluates the efficacy of various ML models such as k-NN, logistic regression, decision trees, random forests, gradient boosting, and support vector machines through rigorous accuracy assessments on training and test datasets. The study emphasizes the implementation of decision trees and fuzzy logic within MATLAB for real-time disease state forecasting in malaria cases. For Covid-19, the paper explores the application of data mining (DM) and ML in identifying patterns, risk factors, early detection, contact tracing, vaccine distribution strategies, and potential drug discoveries. It includes visual analyses of global Covid-19 cases and mortality rates, utilizing Holt-Winters' method for predictive modelling from June 2021 to June 2022. Overall, the insights underscore ML's pivotal role in revolutionizing disease management by enabling timely interventions and optimizing resource allocation. The findings contribute to advancing public health strategies, emphasizing the importance of innovative technological applications in mitigating the impact of infectious diseases on a global scale.