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In this paper, a joint synchronization and Doppler scaling factor estimation algorithm has been proposed for underwater acoustic communications. The training sequence, which consists of two Zadoff-Chu (ZC) sequences being conjugate with each other, is utilized to synchronize and estimate Doppler scaling factor, time delay and carrier frequency offsets (CFOs). ZC sequences are well designed to show...
Context-Aware Recommendation Systems has gained lots of attention in both industry and academic research. Factorization Machines (FM) based recommendation has been successfully used in sparse industrial datasets for user personalized video recommendations. FM is a collaborative filtering technique for predicting a target such as user rating, given observations of interaction between some users and...
To try to decrease the preference of the attribute values for information gain and information gain ratio, in the paper, the authors puts forward a improved algorithm of C4.5 decision tree on the selection classification attribute. The basic thought of the algorithm is as follows: Firstly, computing the information gain of selection classification attribute, and then get an attribute of the information...
Deep neural networks (DNNs) usually demand a large amount of operations for real-time inference. Especially, fully-connected layers contain a large number of weights, thus they usually need many off-chip memory accesses for inference. We propose a weight compression method for deep neural networks, which allows values of +1 or −1 only at predetermined positions of the weights so that decoding using...
A ship maneuvering simulator is elïective training tool for navigation officers. An instructor of simulator training executes the evaluation based on the check list. The trainee is told the evaluation at the de-briefing, and obtains the chance to improve his maneuvering skill. On the other hand, some objective evaluation methods for the simulator training were proposed, and also a method for estimating...
Links between issue reports and corresponding fix commits are widely used in software maintenance. The quality of links directly affects maintenance costs. Currently, such links are mainly maintained by error-prone manual efforts, which may result in missing links. To tackle this problem, automatic link recovery approaches have been proposed by building traditional classifiers with positive and negative...
For modern industrial processes, timely detection of incipient faults is of vital importance so as to ensure safe and optimal process operation. Though recently statistical process monitoring (SPM) has been extensively studied and widely applied in practice, conventional multivariate statistics are usually not sensitive to incipient faults. In this paper, a new multivariate statistical index called...
Acoustic classification of frogs has received increasing attention for its promising application in ecological studies. Various studies have been proposed for classifying frog species, but most recordings are assumed to have only a single species. In this study, a method to classify multiple frog species in an audio clip is presented. To be specific, continuous frog recordings are first cropped into...
Speech feature learning is very important for the design of classification algorithm of Parkinson's disease (PD). Existing speech feature learning method for classification of PD just pays attention to the speech feature. This paper proposed a novel hybrid feature learning algorithm which puts the features of all the speech segments of each subject together, thereby obtaining new and high efficient...
Fault detection method using k nearest neighbor rule has shown its advantages in dealing with nonlinear, multi-mode, and nonGaussian distributed data. Once a fault is detected in industrial processes, recognizing fault variables becomes the crucial task subsequently. Recently, the method of fault variables recognition using k nearest neighbor reconstruction (FVR-kNN) has been reported. However, the...
Food safety is one of the hot issues in all over the world. It is related to national economy and people's livelihood. In recent years, food safety accidents occur in China frequently, so an effective food safety network public opinion early warning model is necessary and imperative. Therefore, the model of Back Propagation neural network based on Analytic Hierarchy Process (AHP-BP) is proposed. The...
The aim of this study is to compare some classifiers' performance related to the tuples amount. The different metrics of performance has been considered, such as: Accuracy, Mean Absolute Error (MAE), and Kappa Statistic. In this research, the different numbers of tuples are considered as well. The readmission process dataset of Diabetic patients, which has been experimented, consists of 47 features...
The supervision of rehabilitation exercises is crucial for a successful therapy. Due to a lack of therapists, technical assistance systems have recently come into focus to assist patients during their exercises. Latest research proved that characteristic motion errors can be detected by using the Kinect skeleton joints in connection with Incremental Dynamic Time Warping (IDTW) and machine learning...
In 2013, Tams et al. proposed a method to determine directed reference points in fingerprints based on a mathematical model of typical orientation fields of tented arch type fingerprints. Although this Tented Arch Reference Point (TARP) method has been used successfully for pre-alignment in biometric cryptosystems, its accuracy does not yet ensure satisfactory error rates for single finger systems...
Estimating short-term power load is a fundamental issue in the power distribution system. Since short-term power load is related to many parameters such as weather conditions, and time. The aim of this study is to determine the relevant parameters in estimating short-term power load not only in order to decrease the computational cost, but also to achieve higher success rates. Furthermore, by using...
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)...
Discusses the concept of quality of education, highlights the criteria and indicators of assessing its quality in the framework of theoretical and methodological research. Highlights the main requirements to level of preparation of graduates.
In previous work we have demonstrated that Virtual Reality can be used to help train driving skills for users of a powered wheelchair. However, cybersickness was a particular problem. This work-in-progress paper presents a Mixed Reality alternative to our wheelchair training software, which overcomes this problem. The design and implementation of this application is discussed. Early results shows...
For better resolving the safety risk early warning of the apron effectively, the attribute reduction algorithm based on Rough Set is used to simplify the set as the warning index set of the apron is too large. The improved Particle Swarm Optimization (PSO) algorithm is used to optimize the parameters of Support Vector Machine. Combined with the Rough Set and SVM which is optimized by the improved...
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