Volume 24 – 2024 – Issue 12 

Click here and insert your abstract text. A 35-year poor tribal lady named Smt.Sunita resides along with her husband and three children in Chiringa Kalyanpur village of Sarguja districts. She and her husband mainly depend on daily wages and agricultural work for their day to day livelihood.Sunita is having complained of pain in her chest and blood was noticed in her sputum during coughing. This situation continues till two to three weeks then her husband takes her to the nearest village doctor who provided some medicine to her. But there is no relief even if taking the medicine for two weeks.Sister Ellia was providing category-II anti TB drugs to Sunita regularly and taking almost care for not missing any medicine doses further. She is also providing drugs at agricultural field while Sunita is busy with her work. Mr. Viswanath field volunteer from RAHA was also visited Sunita time to time and monitor her that she is taking the drugs in time or not. Now Sunita is taking regularly the anti TB drugs and feeling much better than earlier. Sister Ellia is also directly monitoring Sunita,s health as a DOTS provider. Now Sunita is able to do her all domestic work and also perform all agricultural work in the field

Outliers are extreme values that deviate from other observations on data; they may indicate variability in a measurement, experimental errors or a novelty. In other words, an outlier is an observation that diverges from an overall pattern on a sample. Challenges in anomaly detection include appropriate feature extraction, defining normal behaviors, handling imbalanced distribution of normal and abnormal data, addressing the variations in abnormal behavior, sparse occurrence of abnormal events, environmental variations, camera movements, etc. With a view to successful outlier detection, the proposed PEP algorithm applies a provisional model that recognises an exceptional property par with the most suitable method of implementation. Several outlier identification methods have been developed for some domains and applications, but the approaches have been more general and are subject to confidentiality problems. The proposed concept essentially applies the Genetic Modal Based Approach, which is called the GENEX algorithm and the PEP algorithm for the identification of sub-population scores for both numerical and categorical datasets. In addition, the system performs the best fit method to find the best class based on score and mark. The proposed algorithm will minimise the cost of computing and the lack of accuracy of the problem by applying the best data mining and appropriate pruning techniques. Experiments and outcomes have the best match values for the moderate and extreme outlier ranges.

In this paper, the state of the art of Steel Castellated Beams' manufacturing, applications, and its failure pattern is explained. The current research status of castellated beam activity is not mature and needs a lot to be researched in relation to beams without web openings. The prese nce of different opening forms such as square, hexagonal, rectan-gular, octagonal and oval etc. in the web beams introduces several additional failure modes, namely; lateral-torsional buckling of web posts, shear force web post buckling, forming of four plastic hinges around the opening corners, rupture of welded joints over traditional steel beams in the castellated beams. To ensure a effective web opening of the castellated beam optimization techniques such as tug of war algorithm, charged system algorithm in MATLAB coding or genetic algorithm are introduced in this paper. Apart from this FEM analysis of experimental and theoretical studies are mentioned considering the impact of different parameters, such as opening forms, opening distance, opening spacing, different number of openings etc

With the popularity of cloud computing, mobile devices can store/retrieve personal data from anywhere at any time. Consequently, the data security problem in mobile cloud becomes more and more severe and prevents further development of mobile cloud. There are substantial studies that have been conducted to improve the cloud security. However, most of them are not applicable for mobile cloud since mobile devices only have limited computing resources and power. Solutions with low computational overhead are in great need for mobile cloud applications. In this paper, we propose a lightweight data sharing scheme (LDSS) for mobile cloud computing. It adopts CP-ABE, an access control technology used in normal cloud environment, but changes the structure of access control tree to make it suitable for mobile cloud environments

A Digital fuel gauge implemented in automobiles are bar graphs or gauge displays. They indicate a rough value of the fuel present in the tanks using float sensors. They lack both linearity and precision. A load cell however gives an edge over this problem as it overcomes the problem, giving the exact volume as an effect and combining with IOT to get a good monitoring and tracking system. Used in both indication, Alerts, and Data Acquisition using a Microcontroller and IOT Devices

We have developed a deep learning network for classification of different flowers. For this, we have used Visual Geometry Group’s 102 category flower data-set having 8189 images of 102 categories from Oxford University. In this method we have used Convolutional Neural Network architecture for the classification purpose. By keeping all hyper-parameters for the architecture, we have found the Training Accuracy of and Testing Accuracy of . These results are extremely good when compared to random classification accuracy of 0.98%. This method for classification of flowers can be implemented in realtime applications and can be used to help botanists for their research as well as camping enthusiasts