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Internet of Things (IOT) is the network of physical objects that contain embedded technology to communicate and sense or interact with their internal states or the external environment and transfers data over a network without requiring human-to-human or human-to-computer interaction. This paper presents a highly sensitive and more secure management system for bus transport with a help of PIC microcontroller and various sensors. The proposed system provides information regarding moving bus to the owner of bus who is located outside the bus based on IOT. Major aim is to transport information like number of non-ticket holders in a bus, accident occurant places, location of moving bus, fuel level in bus and running speed of bus, pressure level in tires to a bus owner who is outside the bus based on IOT

Summary Analysis of a soil sample from Aizawl district of Mizoram, India, led to the discovery of Mulveyellus aizawlensis sp. n. The new species is presented with female morphological data and molecular data of the D2-D3 expansion segment of 28S and 18S of rDNA, and phylogenetic analysis data based on these sequences. Mulveyellus aizawlensis sp. n. is morphologically characterised by a ventrally arcuate female body, presence of minute transverse striations on cuticle, a barrel-shaped buccal cavity, a dorsal tooth at anterior half of the buccal cavity, toothless subventral wall, distinct cup-shaped amphids located at the level of the dorsal tooth, a tuberculate pharyngo-intestinal junction, bean-shaped pars refrigens vaginae, a didelphic-amphidelphic reproductive system, a conoid ventrally-arcuate tail, and absence of caudal glands and spinneret. This study presents molecular data of the genus Mulveyellus for the first time and revealed a close phylogenetic relationship of this genus with Prionchulus.

Nematological investigation of the order Tylenchida, super-family Criconematoidea and sub-family Macroposthoniinae revealed the presence of two species of the genus Mesocriconema i.e., Mesocriconema mamitensis n. sp. and M. medani, in the rhizospheres of lemongrass and pineapple, respectively, from Mamit district of Mizoram, India. Mesocriconema mamitensis n. sp. is characterized by body length = 0.34-0.45 mm, stylet length = 37.6-49.6 µm, R = 117-120, RV = 7-9, Rvan = 1-2, Ran = 5-7, Roes = 24-32, V = 91.6-93.2 µm, and VL/VB = 0.91-1.27 µm. Mesocriconema medani is characterized by body length = 0.37-0.47 mm, stylet length = 40.6-46.1 µm, R = 117-118, RV = 7-9, Rvan = 1-2, Ran = 5-7, Roes = 26-29, V = 90.4-91.6 µm, and VL/VB = 1.2-1.3 µm. The morphological characterizations of the two species have been done through light and scanning electron microscopy studies. Morphometrics, line illustrations, and information about their hosts and locality are also provided. In addition to the new species description, this study reports M. medani for the first time in Mizoram, India.

Object Detection and its analysis are used in various fields. Rice quality evaluation subtask in Agricultural industries is not exception for object Detection. Manual identification using image processing techniques, Machine Learning Techniques and Deep Learning is also used for the rice quality analysis. Due to Feature identification challenge machine Learning and Deep Learning are in the demand. As rice is mostly used agricultural product so it is important to have the proper analysis of the crops. In this study we proposed the used of image processing method with the help of Machine Learning model. Rice grain morphological characteristics are what define a grain’s quality analysis. The suggested method can operate efficiently with little expense.

Security and protection are the most crucial concerns in today’s quickly developing world. Deep Learning methods and computer vision assist in resolving both problems. One of the computer vision subtasks that allows us to recognise things is object detection. Videos are a source that is taken into account for detection, and image processing technology helps to increase the effectiveness of state-ofthe-art techniques. With all of these technologies, CCTV is recognised as a key element. Using a deep convolutional neural network, we accept CCTV data in real time in this article. The main objective is to make content the centre of things. Using the YOLO technique, we were able to detect the missing item with an improvement of 10% sparsity over the current state-of-the-art algorithm in the context of surveillance systems, where object detection is a crucial step. It can be utilised to take immediate additional action.

Customer segmentation is a method of categorizing corporate clients into groups based on shared characteristics. In this study, we looked at the different customer segmentation methods and execute RFM analysis by using various clustering algorithms. Based on RFM values (Recent, Frequency, and Cost) of customers, the successful classification of company customers is divided into groups with comparable behaviors. Customer retention is thought to be more significant than acquiring new clients are analyzed on two different databases. Results show the significance of each method. Comparison is helps for selection of better customer segmentation.

Background: Renal artery stenosis (RAS) may occur alone (isolated anatomical RAS) or in combination with hypertension (renovascular or essential hypertension), renal insufficiency (ischemic nephropathy), or both. Renal artery stenting can be performed safely with nearly uniform technical success without exposing them to significant incremental risk. Aims and Objectives: The objectives of the study are as follows: (A) To study the incidence of RAS in suspected coronary artery disease patients. (B) To study the hemodynamic significance of RAS in patients diagnosed having RAS. (C) Should patients undergoing coronary angiography be subjected to routine renal angiography during the procedure? Materials and Methods: We prospectively did renal angiography of consecutive 100 patients, who underwent coronary angiography for their suspected coronary artery disease. Data regarding risk factors were recorded for every patient. Results: Out of 12 patients with RAS, 10 had significant stenosis (>50%) out of which seven patients showed hemodynamically significant RAS on captopril renogram. These were the patients having stenosis of 70% or more on renal angiography. Three patients having RAS 50–70% on renal angiography were not having hemodynamically significant lesion on captopril renograms. Conclusion: Renal angiography should be performed in patients undergoing coronary angiography. Femoral artery should be the preferred access site for coronary angiography to approach renal arteries. The patients with RAS should undergo captopril renography to evaluate the hemodynamic significance of the stenosis.