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When a spleen weighs more than 1,600 grams or has a craniocaudal length larger than 21 cm, it is categorized as a supramassive spleen. Laparoscopic splenectomy for normal to moderately enlarged spleens has become the gold standard in elective splenectomy surgery. Its utility in large splenomegaly has not yet completely established, but has great advantage over open surgery. Here, we present a case of 17-year-old young male with a history of congenital heart disease who underwent a Rastelli open heart surgery in 2010 and pulmonary balloon valvulotomy in 2022 came with supramassive splenomegaly, hypersplenism and pancytopenia that was treated with laparoscopic splenectomy. Vaccinations were done two weeks prior to the surgery. Preoperative embolization of the splenic artery was performed 24 hours before splenectomy to reduce complications. The excised spleen measured about 24×15 cm.

The number of industries in a certain region is increasing year by year due to the increasing needs of people, and therefore intelligent industrialization automation can be used. Here the air quality in the industry and the number of products manufactured in the industry are monitored using gas detectors (to detect toxic or toxic gases) and IR sensors (to count the number of products manufactured) where there is no need for labor. Also to see estimated time of arrival of delivery vehicle GPS is used to get latitude, longitude and estimated time of delivery vehicle in real time. The branch of the delivery vehicle is displayed via the APP that can be built with Android Studio, this GPS is integrated in the NODE MCU. In the case of industrial fire accidents, this can be detected using the industry existing flame sensors built into the NODE MCU and the LCD screen where sprinklers are later activated.

The primary goal of the current work is to carry out Malware Detection for IoT devices by comparing the performance of different classifiers. Malware is software that causes harm to our systems or network. Random Forest Algorithm (RFA) and Decision Tree Algorithm (DTA) are two types of algorithms that can be considered. The methods were built and evaluated on a 19612 record dataset. With 10 example sizes, emphasis was performed on each gathering to accomplish better precision. The error rate power was utilized as 80% to perform G-power testing. The experiment’s findings revealed that the Random Forest Algorithm had a mean accuracy of 99.0320 and the Decision tree had a mean accuracy of 98.5140 for malware detection. Using independent sample t-tests, the statistically significant variance in accurateness between the two models was obtained as p = 0.030. This research aims to apply a novel technique to present Machine Learning Classifiers for malware detection. When comparing the Random Forest Algorithm to the Decision Tree Algorithm, the findings signify that the RFA outperforms the DTA.

Lime is the versatile mineral. Various forms of lime are used in environmental, metallurgical, construction, chemical/industrial applications, and more. It has been used for masonry mortars and plastering for centuries. Lime is usually obtained from lime stone. Places like Kerala where lime stone is scarce, lime is majorly obtained from seashells so they developed their own traditional method to extract lime. Shell lime was one of the major components in construction of most of the houses, temples, bridges, dams etc. in Kerala during the earlier days. People used shell lime not only as a replacement to cement but also as a plastering agent which helps to reduce temperature in the interiors. This dissertation is retrospection into the vernacular method of making lime mortar from seashells by visiting the workspace. The study also intends to analyse the challenges faced by this method and provide with necessary recommendations.