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https://www.readbyqxmd.com/read/29018638/automatic-sleep-monitoring-using-ear-eeg
#1
Takashi Nakamura, Valentin Goverdovsky, Mary J Morrell, Danilo P Mandic
The monitoring of sleep patterns without patient's inconvenience or involvement of a medical specialist is a clinical question of significant importance. To this end, we propose an automatic sleep stage monitoring system based on an affordable, unobtrusive, discreet, and long-term wearable in-ear sensor for recording the electroencephalogram (ear-EEG). The selected features for sleep pattern classification from a single ear-EEG channel include the spectral edge frequency and multi-scale fuzzy entropy, a structural complexity feature...
2017: IEEE Journal of Translational Engineering in Health and Medicine
https://www.readbyqxmd.com/read/29017869/risk-assessment-and-quality-improvement-of-liquid-waste-management-in-taiwan-university-chemical-laboratories
#2
Chao-Chung Ho, Ming-Shu Chen
The policy of establishing new universities across Taiwan has led to an increase in the number of universities, and many schools have constructed new laboratories to meet students' academic needs. In recent years, there has been an increase in the number of laboratory accidents from the liquid waste in universities. Therefore, how to build a safety system for laboratory liquid waste disposal has become an important issue in the environmental protection, safety, and hygiene of all universities. This study identifies the risk factors of liquid waste disposal and presents an agenda for practices to laboratory managers...
October 7, 2017: Waste Management
https://www.readbyqxmd.com/read/28994698/priority-of-a-hesitant-fuzzy-linguistic-preference-relation-with-a-normal-distribution-in-meteorological-disaster-risk-assessment
#3
Lihong Wang, Zaiwu Gong
As meteorological disaster systems are large complex systems, disaster reduction programs must be based on risk analysis. Consequently, judgment by an expert based on his or her experience (also known as qualitative evaluation) is an important link in meteorological disaster risk assessment. In some complex and non-procedural meteorological disaster risk assessments, a hesitant fuzzy linguistic preference relation (HFLPR) is often used to deal with a situation in which experts may be hesitant while providing preference information of a pairwise comparison of alternatives, that is, the degree of preference of one alternative over another...
October 10, 2017: International Journal of Environmental Research and Public Health
https://www.readbyqxmd.com/read/28993878/fuzzy-neuronal-model-of-motor-control-inspired-by-cerebellar-pathways-to-online-and-gradually-learn-inverse-biomechanical-functions-in-the-presence-of-delay
#4
Armin Salimi-Badr, Mohammad Mehdi Ebadzadeh, Christian Darlot
Contrary to forward biomechanical functions, which are deterministic, inverse biomechanical functions are generally not. Calculating an inverse biomechanical function is an ill-posed problem, which has no unique solution for a manipulator with several degrees of freedom. Studies of the command and control of biological movements suggest that the cerebellum takes part in the computation of approximate inverse functions, and this ability can control fast movements by predicting the consequence of current motor command...
October 9, 2017: Biological Cybernetics
https://www.readbyqxmd.com/read/28993124/learning-ensemble-classifiers-for-diabetic-retinopathy-assessment
#5
Emran Saleh, Jerzy Błaszczyński, Antonio Moreno, Aida Valls, Pedro Romero-Aroca, Sofia de la Riva-Fernández, Roman Słowiński
Diabetic retinopathy is one of the most common comorbidities of diabetes. Unfortunately, the recommended annual screening of the eye fundus of diabetic patients is too resource-consuming. Therefore, it is necessary to develop tools that may help doctors to determine the risk of each patient to attain this condition, so that patients with a low risk may be screened less frequently and the use of resources can be improved. This paper explores the use of two kinds of ensemble classifiers learned from data: fuzzy random forest and dominance-based rough set balanced rule ensemble...
October 6, 2017: Artificial Intelligence in Medicine
https://www.readbyqxmd.com/read/28991790/prediction-of-biochemical-oxygen-demand-at-the-upstream-catchment-of-a-reservoir-using-adaptive-neuro-fuzzy-inference-system
#6
Yung-Chia Chiu, Chih-Wei Chiang, Tsung-Yu Lee
The aim of this study is to examine the potential of adaptive neuro fuzzy inference system (ANFIS) to estimate biochemical oxygen demand (BOD). To illustrate the applicability of ANFIS method, the upstream catchment of Feitsui Reservoir in Taiwan is chosen as the case study area. The appropriate input variables used to develop the ANFIS models are determined based on the t-test. The results obtained by ANFIS are compared with those by multiple linear regression (MLR) and artificial neural networks (ANNs). Simulated results show that the identified ANFIS model is superior to the traditional MLR and nonlinear ANNs models in terms of the performance evaluated by the Pearson coefficient of correlation, the root mean square error, the mean absolute percentage, and the mean absolute error...
October 2017: Water Science and Technology: a Journal of the International Association on Water Pollution Research
https://www.readbyqxmd.com/read/28991747/dna-implementation-of-fuzzy-inference-engine-towards-dna-decision-making-systems
#7
Aby K George, Harpreet Singh
Decision-making systems are an integral part of any autonomous device. With the recent developments in bionanorobots, smart drugs, and engineered viruses, there is an immediate need of decision-making systems which are biocompatible in nature. DNA is considered a perfect candidate for designing the computing systems in such decision-making systems because of their bio-compatibility and programmability. Complex biological systems can be easily modeled/controlled using fuzzy logic operations with the help of linguistic rules...
October 9, 2017: IEEE Transactions on Nanobioscience
https://www.readbyqxmd.com/read/28990115/an-inexact-multistage-fuzzy-stochastic-programming-for-regional-electric-power-system-management-constrained-by-environmental-quality
#8
Zhenghui Fu, Han Wang, Wentao Lu, Huaicheng Guo, Wei Li
Electric power system involves different fields and disciplines which addressed the economic system, energy system, and environment system. Inner uncertainty of this compound system would be an inevitable problem. Therefore, an inexact multistage fuzzy-stochastic programming (IMFSP) was developed for regional electric power system management constrained by environmental quality. A model which concluded interval-parameter programming, multistage stochastic programming, and fuzzy probability distribution was built to reflect the uncertain information and dynamic variation in the case study, and the scenarios under different credibility degrees were considered...
October 9, 2017: Environmental Science and Pollution Research International
https://www.readbyqxmd.com/read/28988080/flood-susceptibility-mapping-using-novel-ensembles-of-adaptive-neuro-fuzzy-inference-system-and-metaheuristic-algorithms
#9
Seyed Vahid Razavi Termeh, Aiding Kornejady, Hamid Reza Pourghasemi, Saskia Keesstra
Flood is one of the most destructive natural disasters which cause great financial and life losses per year. Therefore, producing susceptibility maps for flood management are necessary in order to reduce its harmful effects. The aim of the present study is to map flood hazard over the Jahrom Township in Fars Province using a combination of adaptive neuro-fuzzy inference systems (ANFIS) with different metaheuristics algorithms such as ant colony optimization (ACO), genetic algorithm (GA), and particle swarm optimization (PSO) and comparing their accuracy...
October 4, 2017: Science of the Total Environment
https://www.readbyqxmd.com/read/28987988/optimal-feature-selection-using-a-modified-differential-evolution-algorithm-and-its-effectiveness-for-prediction-of-heart-disease
#10
T Vivekanandan, N Ch Sriman Narayana Iyengar
Enormous data growth in multiple domains has posed a great challenge for data processing and analysis techniques. In particular, the traditional record maintenance strategy has been replaced in the healthcare system. It is vital to develop a model that is able to handle the huge amount of e-healthcare data efficiently. In this paper, the challenging tasks of selecting critical features from the enormous set of available features and diagnosing heart disease are carried out. Feature selection is one of the most widely used pre-processing steps in classification problems...
September 19, 2017: Computers in Biology and Medicine
https://www.readbyqxmd.com/read/28982076/river-suspended-sediment-modelling-using-the-cart-model-a-comparative-study-of-machine-learning-techniques
#11
Bahram Choubin, Hamid Darabi, Omid Rahmati, Farzaneh Sajedi-Hosseini, Bjørn Kløve
Suspended sediment load (SSL) modelling is an important issue in integrated environmental and water resources management, as sediment affects water quality and aquatic habitats. Although classification and regression tree (CART) algorithms have been applied successfully to ecological and geomorphological modelling, their applicability to SSL estimation in rivers has not yet been investigated. In this study, we evaluated use of a CART model to estimate SSL based on hydro-meteorological data. We also compared the accuracy of the CART model with that of the four most commonly used models for time series modelling of SSL, i...
October 2, 2017: Science of the Total Environment
https://www.readbyqxmd.com/read/28981437/robust-fault-detection-for-switched-fuzzy-systems-with-unknown-input
#12
Jian Han, Huaguang Zhang, Yingchun Wang, Xun Sun
This paper investigates the fault detection problem for a class of switched nonlinear systems in the T-S fuzzy framework. The unknown input is considered in the systems. A novel fault detection unknown input observer design method is proposed. Based on the proposed observer, the unknown input can be removed from the fault detection residual. The weighted H∞ performance level is considered to ensure the robustness. In addition, the weighted H₋ performance level is introduced, which can increase the sensibility of the proposed detection method...
October 3, 2017: IEEE Transactions on Cybernetics
https://www.readbyqxmd.com/read/28971393/an-approach-of-non-linear-systems-through-fuzzy-control-based-on-takagi-sugeno-method
#13
Andreas Giannakis, Konstantinos Giannakis, Athanasios Karlis
Today, the advanced technology is a part of the everyday's life. As a result, most of the applications used require a more complex system in order to achieve a better performance. These systems have a mathematic background indicating the need of a better mathematical tool to increase the reliability of them. One of the most significant problems coming up against these systems is undoubtedly the non-linearity of the equations governing them. Herein, a linearization method is proposed and studied through intelligent control...
2017: Advances in Experimental Medicine and Biology
https://www.readbyqxmd.com/read/28971313/validating-an-image-segmentation-program-devised-for-staging-lymphoma
#14
Anthony Slattery
Hybrid positron emission tomography-computed tomography (PET-CT) imaging systems are an important tool for assessing the progression of lymphoma. PET-CT systems offer the ability to quantitatively assess lymphocytic bone involvement throughout the body. There is no standard methodology for staging lymphoma patients using PET-CT images. Automatic image segmentation algorithms could offer medical specialists a means to evaluate bone involvement from PET-CT images in a consistent manner. To devise and validate an image segmentation program that may assist staging lymphoma by determining the degree of bone involvement based from PET-CT studies...
October 2, 2017: Australasian Physical & Engineering Sciences in Medicine
https://www.readbyqxmd.com/read/28967391/indirect-predictive-type-2-fuzzy-neural-network-controller-for-a-class-of-nonlinear-input-delay-systems
#15
Kamel Sabahi, Sehraneh Ghaemi, Jianxing Liu, Mohammad Ali Badamchizadeh
In this paper a new indirect type-2 fuzzy neural network predictive (T2FNNP) controller has been proposed for a class of nonlinear systems with input-delay in presence of unknown disturbance and uncertainties. In this method, the predictor has been utilized to estimate the future state variables of the controlled system to compensate for the time-varying delay. The T2FNN is used to estimate some unknown nonlinear functions to construct the controller. By introducing a new adaptive compensator for the predictor and controller, the effects of the external disturbance, estimation errors of the unknown nonlinear functions, and future sate estimation errors have been eliminated...
September 26, 2017: ISA Transactions
https://www.readbyqxmd.com/read/28961219/a-novel-online-data-driven-algorithm-for-detecting-uav-navigation-sensor-faults
#16
Rui Sun, Qi Cheng, Guanyu Wang, Washington Yotto Ochieng
The use of Unmanned Aerial Vehicles (UAVs) has increased significantly in recent years. On-board integrated navigation sensors are a key component of UAVs' flight control systems and are essential for flight safety. In order to ensure flight safety, timely and effective navigation sensor fault detection capability is required. In this paper, a novel data-driven Adaptive Neuron Fuzzy Inference System (ANFIS)-based approach is presented for the detection of on-board navigation sensor faults in UAVs. Contrary to the classic UAV sensor fault detection algorithms, based on predefined or modelled faults, the proposed algorithm combines an online data training mechanism with the ANFIS-based decision system...
September 29, 2017: Sensors
https://www.readbyqxmd.com/read/28959000/detection-of-small-bowel-tumor-in-wireless-capsule-endoscopy-images-using-an-adaptive-neuro-fuzzy-inference-system
#17
Mahdi Alizadeh, Omid Haji Maghsoudi, Kaveh Sharzehi, Hamid Reza Hemati, Alireza Kamali Asl, Alireza Talebpour
Automatic diagnosis tool helps physicians to evaluate capsule endoscopic examinations faster and more accurate. The purpose of this study was to evaluate the validity and reliability of an automatic post-processing method for identifying and classifying wireless capsule endoscopic images, and investigate statistical measures to differentiate normal and abnormal images. The proposed technique consists of two main stages, namely, feature extraction and classification. Primarily, 32 features incorporating four statistical measures (contrast, correlation, homogeneity and energy) calculated from co-occurrence metrics were computed...
September 26, 2017: Journal of Biomedical Research
https://www.readbyqxmd.com/read/28958450/experimental-and-ai-based-numerical-modeling-of-contaminant-transport-in-porous-media
#18
Vahid Nourani, Shahram Mousavi, Fahreddin Sadikoglu, Vijay P Singh
This study developed a new hybrid artificial intelligence (AI)-meshless approach for modeling contaminant transport in porous media. The key innovation of the proposed approach is that both black box and physically-based models are combined for modeling contaminant transport. The effectiveness of the approach was evaluated using experimental and real world data. Artificial neural network (ANN) and adaptive neuro-fuzzy inference system (ANFIS) were calibrated to predict temporal contaminant concentrations (CCs), and the effect of noisy and de-noised data on the model performance was evaluated...
September 21, 2017: Journal of Contaminant Hydrology
https://www.readbyqxmd.com/read/28952953/a-novel-finite-sum-inequality-based-method-for-robust-h%C3%A2-control-of-uncertain-discrete-time-takagi-sugeno-fuzzy-systems-with-interval-like-time-varying-delays
#19
Xian-Ming Zhang, Qing-Long Han, Xiaohua Ge
This paper is concerned with the problem of robust H∞ control of an uncertain discrete-time Takagi-Sugeno fuzzy system with an interval-like time-varying delay. A novel finite-sum inequality-based method is proposed to provide a tighter estimation on the forward difference of certain Lyapunov functional, leading to a less conservative result. First, an auxiliary vector function is used to establish two finite-sum inequalities, which can produce tighter bounds for the finite-sum terms appearing in the forward difference of the Lyapunov functional...
September 22, 2017: IEEE Transactions on Cybernetics
https://www.readbyqxmd.com/read/28951803/safety-of-workers-in-indian-mines-study-analysis-and-prediction
#20
Shikha Verma, Sharad Chaudhari
BACKGROUND: The mining industry is known worldwide for its highly risky and hazardous working environment. Technological advancement in ore extraction techniques for proliferation of production levels has caused further concern for safety in this industry. Research so far in the area of safety has revealed that the majority of incidents in hazardous industry take place because of human error, the control of which would enhance safety levels in working sites to a considerable extent. METHODS: The present work focuses upon the analysis of human factors such as unsafe acts, preconditions for unsafe acts, unsafe leadership, and organizational influences...
September 2017: Safety and Health At Work
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