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This study explored the hidden biomedical information from knee MR images for osteoarthritis prediction. We have computed the Cartilage Damage Index (CDI) information from 36 informative locations on tibiofemoral compartment from 3D MR imaging reconstruction and used PCA analysis to process the feature set. The processed feature set and original raw feature set were severed as input to four machine...
In recent years identification and control algorithms applied to heating, ventilation and air conditioning (HVAC) systems have been paid an increasing attention. The main idea of this paper is to exploit the learning capacity of Radial Basic Function Neural Networks (RBFNN) for adaptation and control of multi-zone building heating regulation. Several inputs and disturbances that influence the indoor...
This paper presents a decision support system for classification of hotel guests in the terms of additional spending. The research is conducted on three stars medium-sized hotel. Guests are classified on arrival, during check-in, in one of the two groups: low spending group or high spending group. A low spending group consists of visitors that are anticipated to spend less than 25 Euros per day for...
Forecasting the returns of stock markets is gaining importance nowadays in finance. For this aim, in the last decade, Artificial Neural Networks (ANN) have been widely used to forecast stock market movements. In Baltic countries, artificial neural networks are not commonly used in predicting financial failures. This study aims using artificial neural networks to predict OMX Baltic Benchmark GI (OMXBBGI)...
In this study, a model was developed to estimate monthly-average daily solar radiation over Turkey. Artificial neural network method was used in improved model. The solar radiation values of 53 different locations over Turkey were taken as data. Land surface temperature, altitude, latitude, longitude and month values were used as input variables for modeling artificial neural network and solar radiation...
Financial market dynamics forecasting has long been a focus of economic research. A hybridizing functional link artificial neural network (FLANN) and improved particle warm optimization (PSO) based on wavelet mutation (WM), named as IWM-PSO-FLANN, for forecasting the CSI 300 index is proposed in this paper. In the training model, it expands a wider mutation range while apply wavelet theory to the...
Wireless Sensor Network has constraint with energy and computation. Network Life is based on the way the energy in the battery is used. Continuously sending data along a specific path for long intervals of time, results in large amount of energy consumption. This could eventually lead to network partitioning, which in turn will create a path loss between the sender and receiver. Though several (sensor)...
This paper presents a novel feature extraction framework for content-based image retrieval (CBIR). Discrete wavelet transform (DWT) based Local tetra pattern (LTrP) is used to obtain the feature map from an input image. Decomposition of DWT up to single level and the features obtained from it would make the CBIR system very sensitive to noise. Therefore, decomposition up to three scales is used to...
In this paper, we construct the financial risk early warning model based on BP neural network, make an empirical analysis of the data between January 2004 and October 2015, proves the reliability of the model prediction results through the training and test of the financial risk early warning model and finally put forward the following suggestions for preventing China's financial risks under the new...
A necessary and sufficient condition for the existence of an OPV frame has been given. Also, we obtain conditions under which an OPV frame is a Riesz (orthonormal) OPV frame. Further, we show that an OPV frame is a compression of Riesz OPV frame and Parseval OPV frame is a compression of orthonormal OPV frame. Finally, we obtain Choi-Kraus representations of quantum channels using OPV frames.
Establishment of protected areas is one of the most important approaches for biodiversity conservation. Up to 2015, China has established 2740 sites for nature reserves with a total area of 1470300 km2, covering 14.8% of Chinese land surface. Based on remote sensing inversion, model simulation and spatial analysis methods, we analyzed spatial and temporal variations of habitat from the vegetation...
Radio Frequency Interference (RFI) is a threat to passive microwave measurements and if undetected, can corrupt science retrievals. The sparse component analysis (SCA) for blind source separation has been investigated to detect RFI in microwave radiometer data. Various techniques using SCA have been simulated to determine detection performance with continuous wave (CW) RFI.
Cardiac function is reduced after acute myocardial infarction due to myocardial injury and to changes in the viable non-ischemic myocardium, a process known as cardiac remodeling. Current treatment of patients with acute myocardial infarction (AMI) reduces infarct size, preserves left ventricular function, and improves survival. However, it does not prevent remodeling which leads to heart failure...
The severity of global magnetic disturbances in Near-Earth space can crucially affect human life. These geomagnetic disturbances are often indicated by a Kp index, which is derived from magnetic field data from ground stations, and is known to be correlated with solar wind observations. Forecasting of Kp index is important for understanding the dynamic relationship between the magnetosphere and solar...
This work presents the development and evaluation of a new scheme based on Artificial Neural Network (ANN) for fault detection and fault location in distribution systems with distributed generator. Two different ANNs are used, where the first one is able to detect which part of the distribution system the fault occurred and the second one is able to precisely locate the fault along the faulty line...
At present, the researches on credit risk analysis mainly focus on commercial bank loan or consumer credit risk, and there is little research about the credit risk of rural credit cooperatives. The purpose of this paper is to evaluate credit risk for the rural credit cooperatives using artificial neural network model. We establish credit risk assessment index system for rural credit cooperatives....
We consider two-user relay-aided uplink nonorthogonal multiple access (NOMA) with noisy network coding (NNC) at the relay. The NNC-based cooperation strategy at the relay relies on noisy quantization followed by joint source-channel coding, while at the destination it utilizes joint decoding using the non-orthogonal signals received from the sources and the relay. After presenting the information...
Refinery hydrogen consumers (i.e. hydrocracker, hydro-treater) are operated in high pressure. The makeup hydrogen and recycle hydrogen compressors are placed to increase the pressure of hydrogen streams. It leads to a large contribution on compression work and operating cost. Therefore, except for the minimizing the flowrate of hydrogen utility, it is extremely important to reduce the compression...
Support vector machines (SVMs) are promising methods for the prediction of the financial time-series because they use a risk function, consisting of an empirical error and a regularized term, which is derived from the structural risk minimization principle. This study applies SVM for predicting the stock price index. In addition, this study examines the feasibility of the applying SVM in financial...
One decision in Stock Market can make huge impact on an investor's life. The stock market is a complex system and often covered in mystery, it is therefore, very difficult to analyze all the impacting factors before making a decision. In this research, we have tried to design a stock market prediction model which is based on different factors. The model was built to predict performance of KSE-100...
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