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Artificial neural networks

Luis F Valdez, Juan Manuel Gutiérrez
In this work, we will analyze the response of a Metal Oxide Gas Sensor (MOGS) array to a flow controlled stimulus generated in a pressure controlled canister produced by a homemade olfactometer to build an E-nose. The built E-nose is capable of chocolate identification between the 26 analyzed chocolate bar samples and four features recognition (chocolate type, extra ingredient, sweetener and expiration date status). The data analysis tools used were Principal Components Analysis (PCA) and Artificial Neural Networks (ANNs)...
October 20, 2016: Sensors
Reddi Kamesh, Kalipatnapu Yamuna Rani
In this paper, a novel formulation for nonlinear model predictive control (MPC) has been proposed incorporating the extended Kalman filter (EKF) control concept using a purely data-driven artificial neural network (ANN) model based on measurements for supervisory control. The proposed scheme consists of two modules focusing on online parameter estimation based on past measurements and control estimation over control horizon based on minimizing the deviation of model output predictions from set points along the prediction horizon...
October 13, 2016: IEEE Transactions on Neural Networks and Learning Systems
Xuewu Li, Tian Shi, Cong Liu, Qiaoxin Zhang, Xingjiu Huang
Aluminum alloys are vulnerable to penetrating and peeling failures in seawater and preparing a barrier coating to isolate the substrate from corrosive medium is an effective anticorrosion method. Inspired by the lotus leaves effect, a wetting alloy surface with enhanced anticorrosion behavior has been prepared via etch, deposition, and low-surface-energy modification. Results indicate that excellent superamphiphobicity has been achieved after the modification of the constructed hierarchical labyrinth-like microstructures and dendritic nanostructures...
October 24, 2016: Scientific Reports
Ebrahim Alipanahpour Dil, Mehrorang Ghaedi, Arash Asfaram
The present research is focused on the synthesis and characterization of zinc (II) oxide nanorods loaded on activated carbon (ZnO-NRs-AC) to prepare an outstanding adsorbent for the simultaneous adsorption of heavy metals and dyes as hazardous pollutant using ultrasound energy. The adsorbent was identified by Scanning Electron Microscope (SEM), Transmission Electron Microscopy (TEM), Energy-dispersive X-ray spectroscopy (EDS) and X-ray diffraction (XRD) analysis. The individual effects and possible interactions between the most effective variables including initial metal ions (Cd(2+) and Co(2+)) and azo dyes (methylene blue (MB) and crystal violet (CV)) concentration, adsorbent dosage and ultrasonic time on the responses were investigated by response surface methodology (RSM) and optimum conditions was fixed at Cd(2+), Co(2+), MB and CV concentrations were 25, 24, 18 and 14mgL(-1), respectively, 0...
January 2017: Ultrasonics Sonochemistry
Ebrahim Alipanahpour Dil, Mehrorang Ghaedi, Arash Asfaram, Shaaker Hajati, Fatemeh Mehrabi, Alireza Goudarzi
Copper oxide nanoparticle-loaded activated carbon (CuO-NP-AC) was synthesized and characterized using different techniques such as FE-SEM, XRD and FT-IR. It was successfully applied for the ultrasound-assisted simultaneous removal of Pb(2+) ions and malachite green (MG) dye in binary system from aqueous solution. The effect of important parameters was modeled and optimized by artificial neural network (ANN) and response surface methodology (RSM). Maximum simultaneous removal percentages (>99.0%) were found at 25mgL(-1), 20mgL(-1), 0...
January 2017: Ultrasonics Sonochemistry
Mahsa Dindarsafa, Alireza Khataee, Baris Kaymak, Behrouz Vahid, Atefeh Karimi, Amir Rahmani
High energy planetary ball milling was applied to prepare sono-Fenton nanocatalyst from natural martite (NM). The NM samples were milled for 2-6h at the speed of 320rpm for production of various ball milled martite (BMM) samples. The catalytic performance of the BMMs was greater than the NM for treatment of Acid Blue 92 (AB92) in heterogeneous sono-Fenton-like process. The NM and the BMM samples were characterized by XRD, FT-IR, SEM, EDX and BET analyses. The particle size distribution of the 6h-milled martite (BMM3) was in the range of 10-90nm, which had the highest surface area compared to the other samples...
January 2017: Ultrasonics Sonochemistry
Ebrahim Alipanahpour Dil, Mehrorang Ghaedi, Arash Asfaram
Present study is based on describing an ultrasound-assisted dispersive liquid-liquid microextraction coupled with derivative spectrophotometry (UAS-DLLME-UV-vis) as useful technique for selective determination of crystal violet (CV) and azure b (Az-B). The significant factors like pH, extractor volume, disperser value and extraction time contribution and their numerical coefficient in quadratic model were calculated according to central composite design (CCD). According to desirability function (DF) as good criterion the best experimental conditions was adjusted and selected at pH of 7...
January 2017: Ultrasonics Sonochemistry
Noemí León-Roque, Mohamed Abderrahim, Luis Nuñez-Alejos, Silvia M Arribas, Luis Condezo-Hoyos
Several procedures are currently used to assess fermentation index (FI) of cocoa beans (Theobroma cacao L.) for quality control. However, all of them present several drawbacks. The aim of the present work was to develop and validate a simple image based quantitative procedure, using color measurement and artificial neural network (ANNs). ANN models based on color measurements were tested to predict fermentation index (FI) of fermented cocoa beans. The RGB values were measured from surface and center region of fermented beans in images obtained by camera and desktop scanner...
December 1, 2016: Talanta
Regina Aroca-Santos, John C Cancilla, Enrique S Pariente, José S Torrecilla
The identification and quantification of binary blends of refined olive oil with four different extra virgin olive oil (EVOO) varietals (Picual, Cornicabra, Hojiblanca and Arbequina) was carried out with a simple method based on combining visible spectroscopy and non-linear artificial neural networks (ANNs). The data obtained from the spectroscopic analysis was treated and prepared to be used as independent variables for a multilayer perceptron (MLP) model. The model was able to perfectly classify the EVOO varietal (100% identification rate), whereas the error for the quantification of EVOO in the mixtures containing between 0% and 20% of refined olive oil, in terms of the mean prediction error (MPE), was 2...
December 1, 2016: Talanta
Xiaoran Duan, Yongli Yang, Shanjuan Tan, Sihua Wang, Xiaolei Feng, Liuxin Cui, Feifei Feng, Songcheng Yu, Wei Wang, Yongjun Wu
The purpose of the study was to explore the application of artificial neural network model in the auxiliary diagnosis of lung cancer and compare the effects of back-propagation (BP) neural network with Fisher discrimination model for lung cancer screening by the combined detections of four biomarkers of p16, RASSF1A and FHIT gene promoter methylation levels and the relative telomere length. Real-time quantitative methylation-specific PCR was used to detect the levels of three-gene promoter methylation, and real-time PCR method was applied to determine the relative telomere length...
October 20, 2016: Medical & Biological Engineering & Computing
Abdul Akbar, Ananya Kuanar, Raj K Joshi, I S Sandeep, Sujata Mohanty, Pradeep K Naik, Antaryami Mishra, Sanghamitra Nayak
The drug yielding potential of turmeric (Curcuma longa L.) is largely due to the presence of phyto-constituent 'curcumin.' Curcumin has been found to possess a myriad of therapeutic activities ranging from anti-inflammatory to neuroprotective. Lack of requisite high curcumin containing genotypes and variation in the curcumin content of turmeric at different agro climatic regions are the major stumbling blocks in commercial production of turmeric. Curcumin content of turmeric is greatly influenced by environmental factors...
2016: Frontiers in Plant Science
Giulio Binetti, Laura Del Coco, Rosa Ragone, Samanta Zelasco, Enzo Perri, Cinzia Montemurro, Raffaele Valentini, David Naso, Francesco Paolo Fanizzi, Francesco Paolo Schena
The development of an efficient and accurate method for extra-virgin olive oils cultivar and origin authentication is complicated by the broad range of variables (e.g., multiplicity of varieties, pedo-climatic aspects, production and storage conditions) influencing their properties. In this study, artificial neural networks (ANNs) were applied on several analytical datasets, namely standard merceological parameters, near-infra red data and (1)H nuclear magnetic resonance (NMR) fingerprints, obtained on mono-cultivar olive oils of four representative Apulian varieties (Coratina, Ogliarola, Cima di Mola, Peranzana)...
March 15, 2017: Food Chemistry
Laiyuan Wang, Zhiyong Wang, Jinyi Lin, Jie Yang, Linghai Xie, Mingdong Yi, Wen Li, Haifeng Ling, Changjin Ou, Wei Huang
Most simulations of neuroplasticity in memristors, which are potentially used to develop artificial synapses, are confined to the basic biological Hebbian rules. However, the simplex rules potentially can induce excessive excitation/inhibition, even collapse of neural activities, because they neglect the properties of long-term homeostasis involved in the frameworks of realistic neural networks. Here, we develop organic CuPc-based memristors of which excitatory and inhibitory conductivities can implement both Hebbian rules and homeostatic plasticity, complementary to Hebbian patterns and conductive to the long-term homeostasis...
October 20, 2016: Scientific Reports
Osman Aydoğan, Ali Öter, Kerim Güney, M Kemal Kıymık, Deniz Tuncel
Obstructive sleep apnea is a sleep disorder which may lead to various results. While some studies used real-time systems, there are also numerous studies which focus on diagnosing Obstructive Sleep Apnea via signals obtained by polysomnography from apnea patients who spend the night in sleep laboratory. The mean, frequency and power of signals obtained from patients are frequently used. Obstructive Sleep Apnea of 74 patients were scored in this study. A visual-scoring based algorithm and a morphological filter via Artificial Neural Networks were used in order to diagnose Obstructive Sleep Apnea...
December 2016: Journal of Medical Systems
Naushad Shaik Mohammad, P Sai Shruti, Venkat Bharathi, Chintakindi Krishna Prasad, Tajamul Hussain, Salman A Alrokayan, Usha Naik, Akella Radha Rama Devi
BACKGROUND: The rationale of the current study was to test the clinical utility of the folate pathway genetic polymorphisms in predicting the risk for autism spectrum disorders (ASD) and to address the inconsistencies in the association of MTHFR C677T and hyperhomocysteinemia with ASD. PATIENTS AND METHODS: An artificial neural network (ANN) model was developed from the data of 138 autistic and 138 nonautistic children using GCPII C1561T, SHMT1 C1420T, MTHFR C677T, MTR A2756G, and MTRR A66G as the predictors of autism risk...
October 17, 2016: Psychiatric Genetics
Patricia Melin, German Prado-Arechiga, Martha Pulido, Ivette Miramontes
OBJECTIVE: The development of an artificial modular neural network (MNN) method for diagnosing and classification of arterial Hypertension based on the level of the blood pressure (BP) of a patient is presented. The main goal is to diagnose the degree of hypertension based on the BP values using MNN applying response integration via a gating network approach. DESIGN AND METHOD: This study was performed with 28 patients to classify the BP levels, based on the European Society of Hypertension (ESH) and the European Society of Cardiology (ESC) Guidelines of Hypertension...
September 2016: Journal of Hypertension
Jaya Sanyal, Shiek S S J Ahmed, Hon Keung Tony Ng, Tufan Naiya, Epsita Ghosh, Tapas Kumar Banerjee, Jaya Lakshmi, Gautam Guha, Vadlamudi Raghavendra Rao
Parkinson's disease (PD) is a neurodegenerative disease with the absence of markers for diagnosis. Several studies on PD reported the elements imbalance in biofluids as biomarkers. However, their results remained inconclusive. This study integrates metallomics, multivariate and artificial neural network (ANN) to understand element variations in CSF and serum of PD patients from the largest cohort of Indian population to solve the inconsistent results of previous studies. Also, this study is aimed to (1) ascertain a common element signature between CSF and serum...
October 18, 2016: Scientific Reports
Negisa Darajeh, Azni Idris, Hamid Reza Fard Masoumi, Abolfazl Nourani, Paul Truong, Shahabaldin Rezania
Artificial neural networks (ANN) have been widely used to solve the problems because of their reliable, robust, and salient characteristics in capturing the non-linear relationships between variables in complex systems. In this study ANN was applied for modeling of COD and BOD removal from Palm Oil Mill Secondary Effluent (POMSE) by Vetiver system. The independent variable including POMSE concentration, Vetiver slips density, and removal time has been considered as input parameters to optimize the network, while the removal percentage of COD and BOD were selected as output...
October 17, 2016: International Journal of Phytoremediation
Yi Yang, Juan Wen, Liqiang Guo, Xiang Wan, Peifu Du, Ping Feng, Yi Shi, Qing Wan
Emulating neural behaviors at the synaptic level is of great significance for building neuromorphic computational systems and realizing artificial intelligence. Here, oxide-based electric-double-layer (EDL) thin-film transistors were fabricated by using 3-triethoxysilylpropylamine modified graphene oxide (KH550-GO) electrolyte as the gate dielectrics. Resulting from the EDL effect and electrochemical doping between mobile protons and the indium-zinc-oxide channel layer, long-term synaptic plasticity was emulated in our devices...
October 17, 2016: ACS Applied Materials & Interfaces
Chuanchuan Zheng, Yong Xia, Yongsheng Pan, Jinhu Chen
In this review paper, we summarized the automated dementia identification algorithms in the literature from a pattern classification perspective. Since most of those algorithms consist of both feature extraction and classification, we provide a survey on three categories of feature extraction methods, including the voxel-, vertex- and ROI-based ones, and four categories of classifiers, including the linear discriminant analysis, Bayes classifiers, support vector machines, and artificial neural networks. We also compare the reported performance of many recently published dementia identification algorithms...
March 2016: Brain Informatics
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