The purpose of this study was to analyze the records patients diagnosed with essential hypertension using association rule mining (ARM).Patients (ICD code, I10) were extracted from a hospital's data warehouse and mart constructed for analysis. Apriori modeling ARM method web node in Clementine 12.0 program used patient data.Patients totaled 5,022 diagnostic those numbered 53,994. As result node, hypertension, non-insulin dependent diabetes mellitus (NIDDM), cerebral infarction shown be...

Mobile-edge computing (MEC) is expected to play an important role in the next-generation of Internet-of-Things (IoT) services with artificial intelligence (AI) by providing sustainable computation capability resource-constrained IoT devices. Since finite battery lifetime has been a longstanding challenge MEC system for services, wireless power transfer (WPT) technology recently developed order support perpetual operation In this article, we introduce two resource allocation problems...

With the recent explosive growth of Internet Things (IoT), edge computing is emerging as a modern paradigm that coexists with cloud to process massive amounts data particularly distributed at network. Meanwhile, directly permits use artificial intelligent (AI) models edge. Currently in numerous IoT applications, tremendous amount being measured and transmitted from sensors monitor surrounding information real-time. Considering continuous transmission sensed substantially requires high-energy...

In order to reduce unnecessary data transmissions from Internet of Things (IoT) sensors, this article proposes a multivariate-time-series-prediction-based adaptive transmission period control (PBATPC) algorithm for IoT networks. Based on the spatio-temporal correlation between multivariate time-series data, we developed novel encoding scheme utilizing proposed distance measure <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math...

This article proposes a novel deep learning-based robust Internet of Things (IoT) sensor data transmission period control (DL-RDTPC) framework in an IoT edge computing system. In general, as the sensors increases, energy consumption is reduced, and contrarily, amount un-transmitted (i.e., missing values) becomes continuously accumulated. Therefore, server charge accurately imputing these for reliable analysis. By addressing this issue, we newly design imputation accuracy prediction (IAP)...

The proliferation of community energy storage systems (CESSs) necessitates effective management to address financial concerns. This paper presents an efficient scheme for heterogeneous power consumers by analyzing various cost factors relevant the system. We propose authority transaction model based on a multi-leader multi-follower Stackelberg game, demonstrating existence unique equilibrium determine optimal bidding prices and allocate transactions. Our shows that implementing CESS can...

In a variety of Internet Things (IoT) applications, there is growing need to constantly transmit large amounts real-time data from IoT sensors enable precise environmental monitoring. However, this constant transmission can result in high energy consumption sensors, which presents significant challenge for systems. Therefore, article new approach controlling the period called imputation error cluster-based control (IEC-TPC) framework, with goal reducing while maintaining accurate collection....

As various Internet of Things technologies emerges, IoT monitoring services are rapidly developed. Most sensors deployed in an environment should reduce the energy consumption unnecessary data transmission. In this paper, we propose a accuracy pattern-based transmission period control algorithm. Restoration patterns time series that missing due to broadly extracted. These restoration vectors showing similar clustered into same cluster. The modeled based on logistic function form linear...

With the proliferation of Internet Things technologies, health care services that target a household equipped with IoT devices are widely emerging. In meantime, number global single households is expected to rapidly grow. Contactless radar-based sensors recently investigated as convenient and practical means collect biometric data subjects in households. this paper, collected by contactless installed elderly under uncontrolled environments analyzed, deep learning-based classification model...

For micro grids with renewable energy sources, the main goal is to optimize usage in a particular area based on prediction of consumption and production. However, error cannot be evaded it causes various problems operate microgrid system. To solve these problems, we are going propose two-stage operation model local In addition, by applying cooperative game theory Shapley-value algorithm, revenue payment determined real-time period actual contribution individual prosumer. Numerical anaylsis...

As the problems of existing fossil fuels are raised, importance renewable energy as a substitute is getting more emphasized. In order to solve this problem, various attempts have been made expand penetration rate based on monetary support polices under government initiative. Therefore, we analyze certificate, which compensation system for generation facility, and discuss rational decision consumers mathematical perspective. addition, combination second price seal-bid auction blockchain...

Leveraging the enormous amounts of real-world data collected through Internet Things (IoT) technologies, human activity recognition (HAR) has become a crucial component numerous human-centric applications, with aim enhancing quality life. While recent advancements in deep learning have significantly improved HAR, process labeling continues to remain significant challenge due substantial costs associated annotation for supervised model training. Active (AL) addresses this issue by...

Wireless power transmission (WPT) is expected to play an important role in the Internet of Things services by providing perpetual operation IoT sensors. However, prolong network's lifetime, efficient resource allocation algorithm required, particular, energy fairness issue among sensors has been a critical challenge WPT system. In this paper, considering as minimum received all poverty (EPISs), we allocate orthogonal frequency bands several EPISs and transfer RF on each band, using...

In this paper, we considered energy trading within a wireless power transmission system. Considering one hunger sensor device and battery operator, the operator uses electromagnetic wave to transfer device. device, rectifier is used convert such into DC power, an important part of deciding actual efficiency. nonlinear model discussed problem optimizing be transmitted. addition, considering price per game between operator.

With Internet of Things technologies, healthcare services for smart homes are emerging. In the meantime, number households single-living elderly who distant from using devices is increasing, and contactless radar-based sensors recently introduced to monitor users in single households. this paper, were installed over 100 collect their biometric data under uncontrolled environments. addition, a deep learning-based classification model proposed that estimates user status predefined classes....

With the recent advances in Internet of Things (IoT) technologies, various human-centered applications have proliferated and improved quality users' life. In meantime, human activity recognition (HAR) has been considered as an essential component IoT due to its capability providing substantial information about user states. Whereas deep learning-based HAR methods recently proposed, there are still rooms improve models, particularly from perspective IoT, models need be precise but resource...