In human body, different types of diseases can be found while examining blood samples. this paper, the main aim is to detect leukocytes from blood. These protect body infectious diseases. If there any type disturbances in count, then it may signify presence some cancer. Due reason, earlier many hematological experts examined samples by using medical instruments such as flow cytometer, for determining what disease present body. Since, manual segmentation remains a very soporific, tiresome and...

Potholes are a common road hazard that may cause significant damage to vehicles and pose risks drivers pedestrians. The detection classification of potholes in images can aid effective maintenance repair infrastructure. In this study, the training YOLOv8, an advanced object algorithm, on pothole image dataset is presented. consists diverse captured from various conditions environments. annotated with bounding boxes around instances facilitate supervised learning. known for its accuracy...

The extraction of nucleus from the blood smear images white cells (WBC) provides valuable information to doctors for identification different kinds diseases as most present in body can be identified by analyzing blood. Manually it very soporific and tiresome segment after that classification is done on basis besides instruments which are used experts segmentation not affordable every hospitals clinics, so automatic system preferable reduces times classification. In our research we focus...

The White blood cell detection is most important in of various kinds diseases human body as it provide valuable information to doctors for diagnosis diseases. This paper focuses on automatic extraction leukocytes using image processing techniques such color segmentation, thresholding and mathematical morphing. We have used the K-Mean clustering based segmentation detect white nucleus a set 480*640*3 images. Since manual very tedious, tardy sometime prone error, besides that medical...

The rapid pace of urbanization worldwide has led to increased challenges in achieving sustainability and efficiency within urban environments.This research investigates the pivotal role Internet Things (IoT) addressing these by exploring its applications contributions creating sustainable efficient spaces.The study delves into various aspects IoT technology, including sensors, actuators, platforms, communication protocols, examines their integration settings.Focusing on key areas such as...

Context: Children with special needs face unique challenges in day-to-day practice. They are dependent on their close ones for everything. To improve oral hygiene such visually impaired children, undue training and education required. Braille is an important language reading writing the impaired. It helps them understand visualize world via touch. Audio aids being used to impart health Tactile models help perceive things which they cannot hence learning tool. Aim: This study aimed assess...

Microwaves and Radiowaves are the non ionizing electromagnetic radiations ranging between 300MHz to 300 GHz KHz MHz respectively. They used in various fields, however, they gaining marked popularity food technology nowadays. This paper reviewed history, basic principles, advantages, disadvantages, uses applications of microwaves radiowaves field preservation processing as these technologies have increased amount nutrient retention treated with increase shelf life along less use preservatives.

Velocity of data generation has increased over a period decade which is expected to further increase exponentially with the passage time. To mine useful nuggets information, satisfying large community users it preferred capture interest user, i.e., create user profile, and then filter content according his taste. A may traverse through number documents, requiring profiling technique support scalability growing documents. This paper proposes novel - Map Reduce based Vector Space Model...

Big Data is a collection of datasets containing massive amount data in the range zettabytes and yottabytes. Organizations are facing difficulties manipulating managing this as existing traditional database software techniques unable to process analyze voluminous data. Dealing with requires new tools that can extract valuable information using some analytic process. Volume, Variety, Velocity, Value, Veracity, Variability Complexity attributes associated various works literature. In paper, we...

Recommender systems assist users to narrow down the choices from plethora of options available them, by recommending most suitable their profile. Traditional Collaborative Filtering (CF) technique suffers problem popularity bias as a result which items recommended lack novelty in them. The need today is, incorporate novel list items, popular are apparent and novelty. This paper proposes new Novelty Score (NS) metric based on item frequency inverse user for unseen items. also Modified...

This paper researches the underlying period of AI-based advancement applications and their impact on clinical thought business. Notwithstanding a nitty gritty conversation parts, this examination zeroed in couple certifiable examples AI use medical services settings. The findings demonstrate that critical crisis facilities are now utilizing AI-enabled technologies to expand personnel continuous discovering therapy procedures for wide range illnesses. Furthermore, Artificial intelligence (AI)...

Deep learning methods for univariate time series classification (TSC) are recently gaining attention. Especially, convolutional neural network (CNN) is utilized to solve the problem of predicting class labels obtained through various important applications, such as engineering, biomedical, and finance. In this work, a novel CNN model proposed with validation-based stopping rule (VSR) named CNN-VSR, TSC using 2-D convolution operation, inspired by image processing properties. For this, first,...