An efficient human activity recognition model based on deep learning approaches

Human Activity Recognition (HAR) has gained traction in recent years in diverse areas such as observation, entertainment, teaching and healthcare, using wearable and smartphone sensors. Such environments and systems necessitate and subsume activity recognition, aimed at recognizing the actions, characteristics, and goals of one or more individuals from a temporal series of observations streamed from one or more sensors. Different developed models for HAR have been explained in literature. Deep learning systems and algorithms were shown to perform highly in HAR in recent years, but these algorithms need lots of computerization to be deployed efficiently in applications. This paper presents a HAR lightweight, low computing capacity, deep learning model, which is ideal for use in real-time applications. The generic HAR framework for smartphone sensor data is proposed, based on Long Short-Term Memory (LSTM) networks for time-series domains and standard Convolutional Neural Network (CNN) used for classification. The findings demonstrate that many of the deployed deep learning and machine learning techniques are surpassed by the proposed model. TRANSLATE with x English ArabicHebrewPolishBulgarianHindiPortugueseCatalanHmong DawRomanianChinese SimplifiedHungarianRussianChinese TraditionalIndonesianSlovakCzechItalianSlovenianDanishJapaneseSpanishDutchKlingonSwedishEnglishKoreanThaiEstonianLatvianTurkishFinnishLithuanianUkrainianFrenchMalayUrduGermanMalteseVietnameseGreekNorwegianWelshHaitian CreolePersian // TRANSLATE with COPY THE URL BELOW Back EMBED THE SNIPPET BELOW IN YOUR SITE Enable collaborative features and customize widget: Bing Webmaster Portal Back /

Design of Power-Efficient Structures of the CAM Cell using a New Approach in QCA Nanoelectronics Technology

Quantum-dot Cellular Automata (QCA) is a new emerging nano-electronic technology. Owing to its many fa-vorable features such as low energy requirements, high speed, and small size, QCA is being actively suggested as a future CMOS replacement by researchers. Many digital circuits have been introduced in QCA technology, most of them aiming to reach the function with optimum construction in terms of area, cell count and power consumption. The memory circuit is the main building block in the digital system therefore the researchers paid attention to design the memory cells with minimum requirements. In this paper, a new methodology is intro-duced to design two forms of CAM cell. The proposed designs required two 2:1 multiplexers, one OR gate and one inverter. The first proposed design reduces the power consumption by 53.3%, 35% and 25.9% at (0.5 Ek, 1 Ek, and 1.5 Ek) while the second design by 53.2%, 31.9% and 20.5% (0.5 Ek, 1 Ek, and 1.5 Ek) respectively

Simulated real time controller using modified hill climbing algorithm on fixed wing airplane

In dynamic systems, it is very difficult to have models with good accuracy that are sufficient to predict the plant behavior in a way that an acceptably controlled performance can be produced. Sometimes even if mathematical models are sufficiently accurate in a way that a good controlled performance can be obtained, long term operation (or even short term in some cases) gradually increases the difference between the plant and its dynamical model. That, in turn, would lead to a degraded performance. It is a common task in industrial applications to recalibrate the control system periodically, as the plant parameters suffer various fluctuations from their original values that were used in designing the control system. The calibration procedure usually requires professional attendance, which adds up to more maintenance costs. Also, the experimental nature of the manual calibration often requires at least part of the plant operations to be halted. Adapted from MRAC framework using PID and fuzzy controller, a modified climbing algorithm was introduced in order to compensate the signal. This simulation was applied in fixed-wing airplane pitch angle in Simulink MATLAB. The result demonstrated that effectiveness of the proposed tuning algorithm and improvement over the initial non-tuned response of the process

Effect of organic acids on CO2-rock and water-rock interfacial tension: Implications for CO2 geo-storage

A small concentration of organic acid in carbon dioxide (CO2) storage formations and caprocks could significantly alter the wettability of such formations into less water-wet conditions, decreasing the CO2-storage potential and containment security. Recent studies have attempted to infer the influence of the organic acid concentration on the wettability of rock–CO2–brine systems by measuring advancing and receding contact angles. However, no studies have investigated the influence of organic acid contamination on CO2-storage capacities from rock-fluid interfacial tension (IFT) data because solid-brine and solid-CO2 IFT values cannot be experimentally measured. Equilibrium contact angles and rock-fluid IFT datasets were used to evaluate the viability of CO2 storage in storage rocks and caprocks. First, the contact angles of rock in brine-CO2 systems were measured to compute Young\u27s equilibrium contact angles. Subsequently, rock-brine and rock-gas IFT values at CO2 geo-storage conditions were computed via a modified form of Neumann\u27s equation of state. For two storage-rock minerals (quartz and calcite) and one caprock mineral (mica), the results demonstrated high CO2-brine equilibrium contact angles at high pressure (0.1–25 MPa) and increasing concentrations of stearic acid (10−5 to 10−2 mol/L). Rock-brine IFT increased with the increased stearic acid concentration but remained constant with increased pressure. In all conditions, the order of increasing hydrophobicity of the mineral surfaces is calcite \u3e mica \u3e quartz. At 323 K, 25 MPa, and a stearic acid concentration of 10−2 mol/L, quartz became intermediate-wet with a CO2-brine equilibrium contact angle of 89.8°, whereas mica and calcite became CO2-wet with CO2-brine equilibrium contact angles of 117.5° and 136.5°, respectively. This work provides insight into the effects of organic acids inherent in CO2 geo-storage formations and caprocks on rock wettability and rock-fluid interfacial interactions

Health-related quality of life as a predictor of tuberculosis treatment outcomes in Iraq

Summary ObjectivesTo determine how tuberculosis (TB) treatment affects the health-related quality of life (HRQL) of patients with pulmonary TB and to identify the predictors of favourable TB treatment outcomes in Baghdad, Iraq. MethodsThe Functional Assessment of Chronic Illness Therapy – Tuberculosis (FACIT-TB), a new TB-specific quality of life instrument derived from the internationally recognized FACIT measurement system for the assessment of HRQL, was administered. The mean total and subscale scores of the FACIT-TB at baseline, end of the intensive phase, and end of TB treatment were compared. ResultsAfter the 2-month intensive phase, physical well-being, functional well-being, and the overall total scores were significantly increased (p<0.01). Furthermore, at completion of TB treatment, there were significant improvements in the overall HRQL as indicated by the FACIT-TB total score and all subscales, except social and economic well-being and spiritual well-being. In a direct logistic regression model, only the FACIT-TB total score made a statistically significant contribution towards predicting the likelihood that a patient would have a favourable TB treatment outcome. ConclusionsTherapeutic intervention had a positive impact on patient HRQL. We conclude that FACIT-TB is a reliable tool to monitor HRQL during the course of TB treatment.Universiti Sains Malaysia, Research University Postgraduate Research Grant Scheme (USM-RU-PRGS; grant number 1001/PFARMASI/845040)

Simulated Real-Time Controller for Tuning Algorithm Using Modified Hill Climbing Approach Based on Model Reference Adaptive Control System

In this chapter, an intelligent algorithmic tuning technique suitable for real-time system tuning based on hill climbing optimization algorithm and model reference adaptive control (MRAC) system technique is proposed. Although many adaptive control tuning methodologies depend partially or completely on online plant system identification, the proposed method uses only the model that is used to design the original controller, leading to simplified calculations that do not require neither high processing power nor long processing time, as opposed to identification technique calculations. Additionally, a modified hill climbing algorithm that is developed in this research is specifically designed, configured and tailored for the automatic tuning of control systems. The modified hill climbing algorithm uses a systematic movement when searching for new solution candidates. The algorithm measures the quality of the solution candidate based on error function. The error function is generated by comparing the system response with a desired reference response. The algorithm tests new solution candidates using step signals iteratively. The results showed the algorithm effectiveness to drive the system response. The simulation results illustrate that the method schemes proposed in this study show a viable and versatile solution to deal with controller tuning for systems with model inaccuracies as well as controller real-time calibration problem

Controlling the pitch and yaw angles of twin rotor MIMO system in simulation-based platform using fuzzy logic controller and PID controller

In this paper, the PID and fuzzy logic controllers are designed to control the pitch and yaw angles of a twin rotor MIMO system (TRMS) in simulation-based platform. Two controllers were used in each case, one for pitch angle and one for yaw angle. The twin rotor MIMO system designed as decoupling system in simplification. The tuned controllers gave a very good response in the simulation. These results will provide a solid base for designing the final optimized real-time controller in the next stages of the research

Simulating an induction motor multi-operating point speed control using PI controller with neural network

The Induction Motors (IM) speed widely influenced due to various motor loading conditions. When the load is applied the motor speed is reduced from the reference speed. This work presents a Matlab simulation of a Proportional Integral (PI) controller incorporating Neural Network for IM speed controls. The motor speed response profile under this control is improved and still constant at the point of load applied. Also, this controller stilled operates efficiently at a wide range of operating frequencies when compared with the traditional PI controller

Management of Major Trauma and the Role of Interventional Radiology

This study aimed at exploring the management of major trauma and analyzing the role of interventional radiology for major trauma patients. As there are no prospective randomized controlled trials of interventional radiology in major trauma. Therefore, this review aims to summarize the evidence supporting the use of interventional radiological techniques in the management of major trauma. The study concluded that interventional radiology has become an essential part of the modern trauma unit. Roles in pelvic haemorrhage and aortic injury are now well established and have contributed to improving patient survival and reducing long-term morbidity