Prasan Kumar Sahoo
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View article: Automatic Image Recognition Meal Reporting Among Young Adults: Randomized Controlled Trial
Automatic Image Recognition Meal Reporting Among Young Adults: Randomized Controlled Trial Open
Background Advances in artificial intelligence technology have raised new possibilities for the effective evaluation of daily dietary intake, but more empirical study is needed for the use of such technologies under realistic meal scenario…
View article: Segmentation of ADPKD Computed Tomography Images with Deep Learning Approach for Predicting Total Kidney Volume
Segmentation of ADPKD Computed Tomography Images with Deep Learning Approach for Predicting Total Kidney Volume Open
Background: Total Kidney Volume (TKV) is widely used globally to predict the progressive loss of renal function in patients with Autosomal Dominant Polycystic Kidney Disease (ADPKD). Typically, TKV is calculated using Computed Tomography (…
View article: Leveraging Edge Computing for Video Data Streaming in UAV-Based Emergency Response Systems
Leveraging Edge Computing for Video Data Streaming in UAV-Based Emergency Response Systems Open
The rapid advancement of technology has greatly expanded the capabilities of unmanned aerial vehicles (UAVs) in wireless communication and edge computing domains. The primary objective of UAVs is the seamless transfer of video data streams…
View article: Smart Healthcare: Exploring the Internet of Medical Things with Ambient Intelligence
Smart Healthcare: Exploring the Internet of Medical Things with Ambient Intelligence Open
Ambient Intelligence (AMI) represents a significant advancement in information technology that is perceptive, adaptable, and finely attuned to human needs. It holds immense promise across diverse domains, with particular relevance to healt…
View article: Vision-Based Approach for Food Weight Estimation from 2D Images
Vision-Based Approach for Food Weight Estimation from 2D Images Open
In response to the increasing demand for efficient and non-invasive methods to estimate food weight, this paper presents a vision-based approach utilizing 2D images. The study employs a dataset of 2380 images comprising fourteen different …
View article: Automatic Image Recognition Meal Reporting among Young Adults: A Randomized Controlled Trial (Preprint)
Automatic Image Recognition Meal Reporting among Young Adults: A Randomized Controlled Trial (Preprint) Open
BACKGROUND Advances in artificial intelligence (AI) technology have raised new possibilities for the effective evaluation of daily dietary intake, but more empirical study is needed for the use of such technologies under realistic meal sc…
View article: Healthcare Big Data Analysis with Artificial Neural Network for Cardiac Disease Prediction
Healthcare Big Data Analysis with Artificial Neural Network for Cardiac Disease Prediction Open
The generation of a huge volume of structured, semi-structured and unstructured real-time health monitoring data and its storage in the form of electronic health records (EHRs) need to be processed and analyzed intelligently to provide tim…
View article: Localization of early infarction on non-contrast CT images in acute ischemic stroke with deep learning approach
Localization of early infarction on non-contrast CT images in acute ischemic stroke with deep learning approach Open
Localization of early infarction on first-line Non-contrast computed tomogram (NCCT) guides prompt treatment to improve stroke outcome. Our previous study has shown a good performance in the identification of ischemic injury on NCCT. In th…
View article: Localization of Colorectal Cancer Lesions in Contrast-Computed Tomography Images via a Deep Learning Approach
Localization of Colorectal Cancer Lesions in Contrast-Computed Tomography Images via a Deep Learning Approach Open
Abdominal computed tomography (CT) is a frequently used imaging modality for evaluating gastrointestinal diseases. The detection of colorectal cancer is often realized using CT before a more invasive colonoscopy. When a CT exam is performe…
View article: Artificial-Intelligence-Assisted Activities of Daily Living Recognition for Elderly in Smart Home
Artificial-Intelligence-Assisted Activities of Daily Living Recognition for Elderly in Smart Home Open
Activity Recognition (AR) is a method to identify a certain activity from the set of actions. It is commonly used to recognize a set of Activities of Daily Living (ADLs), which are performed by the elderly in a smart home environment. AR c…
View article: Automatic identification of early ischemic lesions on non-contrast CT with deep learning approach
Automatic identification of early ischemic lesions on non-contrast CT with deep learning approach Open
View article: Deep-Learning-Assisted Multi-Dish Food Recognition Application for Dietary Intake Reporting
Deep-Learning-Assisted Multi-Dish Food Recognition Application for Dietary Intake Reporting Open
Artificial intelligence (AI) is among the major emerging research areas and industrial application fields. An important area of its application is in the preventive healthcare domain, in which appropriate dietary intake reporting is critic…
View article: RRFT: A Rank-Based Resource Aware Fault Tolerant Strategy for Cloud Platforms
RRFT: A Rank-Based Resource Aware Fault Tolerant Strategy for Cloud Platforms Open
The applications that are deployed in the cloud to provide services to the users encompass a large number of interconnected dependent cloud components. Multiple identical components are scheduled to run concurrently in order to handle unex…
View article: Colon Tissues Classification and Localization in Whole Slide Images Using Deep Learning
Colon Tissues Classification and Localization in Whole Slide Images Using Deep Learning Open
Colorectal cancer is one of the leading causes of cancer-related death worldwide. The early diagnosis of colon cancer not only reduces mortality but also reduces the burden related to the treatment strategies such as chemotherapy and/or ra…
View article: Fog Computing Enabled Locality Based Product Demand Prediction and Decision Making Using Reinforcement Learning
Fog Computing Enabled Locality Based Product Demand Prediction and Decision Making Using Reinforcement Learning Open
Wastage of perishable and non-perishable products due to manual monitoring in shopping malls creates huge revenue loss in supermarket industry. Besides, internal and external factors such as calendar events and weather condition contribute…
View article: Deep Learning Assisted Localization of Polycystic Kidney on Contrast-Enhanced CT Images
Deep Learning Assisted Localization of Polycystic Kidney on Contrast-Enhanced CT Images Open
Total Kidney Volume (TKV) is essential for analyzing the progressive loss of renal function in Autosomal Dominant Polycystic Kidney Disease (ADPKD). Conventionally, to measure TKV from medical images, a radiologist needs to localize and se…
View article: Reinforcement Learning Based Passengers Assistance System for Crowded Public Transportation in Fog Enabled Smart City
Reinforcement Learning Based Passengers Assistance System for Crowded Public Transportation in Fog Enabled Smart City Open
Crowding in city public transportation systems is a primary issue that causes delay in the mobility of passengers. Moreover, scheduled and unscheduled events in a city lead to excess crowding situations at the metro or bus stations. The In…
View article: MUVINE: Multi-Stage Virtual Network Embedding in Cloud Data Centers Using Reinforcement Learning-Based Predictions
MUVINE: Multi-Stage Virtual Network Embedding in Cloud Data Centers Using Reinforcement Learning-Based Predictions Open
The recent advances in virtualization technology have enabled the sharing of\ncomputing and networking resources of cloud data centers among multiple users.\nVirtual Network Embedding (VNE) is highly important and is an integral part of\nt…
View article: Failure Aware Semi-Centralized Virtual Network Embedding in Cloud Computing Fat-Tree Data Center Networks
Failure Aware Semi-Centralized Virtual Network Embedding in Cloud Computing Fat-Tree Data Center Networks Open
In Cloud Computing, the tenants opting for the Infrastructure as a Service\n(IaaS) send the resource requirements to the Cloud Service Provider (CSP) in\nthe form of Virtual Network (VN) consisting of a set of inter-connected Virtual\nMach…
View article: Prediction of Colon Cancer Stages and Survival Period with Machine Learning Approach
Prediction of Colon Cancer Stages and Survival Period with Machine Learning Approach Open
The prediction of tumor in the TNM staging (tumor, node, and metastasis) stage of colon cancer using the most influential histopathology parameters and to predict the five years disease-free survival (DFS) period using machine learning (ML…
View article: A Novel Synchronous MAC Protocol for Wireless Sensor Networks with Performance Analysis
A Novel Synchronous MAC Protocol for Wireless Sensor Networks with Performance Analysis Open
Synchronous medium access control (MAC) protocols are highly essential for wireless sensor networks (WSN) to support transmissions with energy saving, quality services, and throughput in industrial, commercial and healthcare applications. …
View article: On the Design of an Efficient Cardiac Health Monitoring System Through Combined Analysis of ECG and SCG Signals
On the Design of an Efficient Cardiac Health Monitoring System Through Combined Analysis of ECG and SCG Signals Open
Cardiovascular disease (CVD) is a major public concern and socioeconomic problem across the globe. The popular high-end cardiac health monitoring systems such as magnetic resonance imaging (MRI), computerized tomography scan (CT scan), and…
View article: Pre-Scheduled and Self Organized Sleep-Scheduling Algorithms for Efficient K-Coverage in Wireless Sensor Networks
Pre-Scheduled and Self Organized Sleep-Scheduling Algorithms for Efficient K-Coverage in Wireless Sensor Networks Open
The K-coverage configuration that guarantees coverage of each location by at least K sensors is highly popular and is extensively used to monitor diversified applications in wireless sensor networks. Long network lifetime and high detectio…
View article: Design and Analysis of a Low Latency Deterministic Network MAC for Wireless Sensor Networks
Design and Analysis of a Low Latency Deterministic Network MAC for Wireless Sensor Networks Open
The IEEE 802.15.4e standard has four different superframe structures for different applications. Use of a low latency deterministic network (LLDN) superframe for the wireless sensor network is one of them, which can operate in a star topol…
View article: A Reliable Data Transmission Model for IEEE 802.15.4e Enabled Wireless Sensor Network under WiFi Interference
A Reliable Data Transmission Model for IEEE 802.15.4e Enabled Wireless Sensor Network under WiFi Interference Open
The IEEE 802.15.4e standard proposes Medium Access Control (MAC) to support collision-free wireless channel access mechanisms for industrial, commercial and healthcare applications. However, unnecessary wastage of energy and bandwidth cons…
View article: A Cardiac Early Warning System with Multi Channel SCG and ECG Monitoring for Mobile Health
A Cardiac Early Warning System with Multi Channel SCG and ECG Monitoring for Mobile Health Open
Use of information and communication technology such as smart phone, smart watch, smart glass and portable health monitoring devices for healthcare services has made Mobile Health (mHealth) an emerging research area. Coronary Heart Disease…
View article: A Novel IEEE 802.15.4e DSME MAC for Wireless Sensor Networks
A Novel IEEE 802.15.4e DSME MAC for Wireless Sensor Networks Open
IEEE 802.15.4e standard proposes Deterministic and Synchronous Multichannel Extension (DSME) mode for wireless sensor networks (WSNs) to support industrial, commercial and health care applications. In this paper, a new channel access schem…
View article: An Efficient Distributed Coverage Hole Detection Protocol for Wireless Sensor Networks
An Efficient Distributed Coverage Hole Detection Protocol for Wireless Sensor Networks Open
In wireless sensor networks (WSNs), certain areas of the monitoring region may have coverage holes and serious coverage overlapping due to the random deployment of sensors. The failure of electronic components, software bugs and destructiv…
View article: Analyzing Healthcare Big Data With Prediction for Future Health Condition
Analyzing Healthcare Big Data With Prediction for Future Health Condition Open
In healthcare management, a large volume of multi-structured patient data is generated from the clinical reports, doctor's notes, and wearable body sensors. The analysis of healthcare parameters and the prediction of the subsequent future …