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Existing Ml-reference image quality assessment models first compute a full image quality-predictive feature map followed by a spatial pooling scheme, thereby producing a single quality score. Here we study spatial sampling strategies that can be used to more efficiently compute reliable picture quality scores. We develop a random sampling scheme on single scale full-reference image quality assessment...
Providing high quality recommendations is significant for e-commerce systems to assist users in making effective selection decisions from a plethora of choices. Collaborative filtering (CF) is one of the most well-known and successful techniques to generate recommendations. However, CF suffers from an inherent issue that does not think over the auxiliary information such as item content information...
A kriging based optimization approach is proposed for problems with large datasets and high dimensionality. Memory usage is maintained via model centering aided by minimizing the impact of information loss on accuracy of new point prediction.
Trying to PM2.s as the independent variable to establish the “beam-diffuse radiation separated” model, factor analysis showed that, PM2.5 and diffuse ratio have positive correlation. Based on the clearness index Kt and sunshine hours n/N as variables, the polynomial model and the BP neural network algorithm model containing PM2.5 as the independent variable is proposed, the polynomial model is fitted...
Error forecasting for electric energy measurement equipment is the foundation of its operation condition forecasting and fault early warning. This paper proposes a kind of forecasting model and algorithm for electric energy metering error based on intrinsic time-scale decomposition (ITD) and time series analysis. Error is decomposed into a steady baseline component and multiple rotation components...
This study examines the degree to which engineering and science students' personality and demographic characteristics are associated with their leadership practices, an area that few studies have explored. The data was from a sample of 70 students attending two institutions (Massachusetts Institute of Technology [MIT] and the Singapore University of Technology and Design [SUTD]) who participated in...
The paper describes a heuristic method for the ultra-short-term computation of prediction intervals (PIs) for photovoltaic (PV) power generation. The method allows for directly forecasting the AC active power output of a PV system by simply extracting information from past time series. Two main approaches are investigated. The former relies on experimentally observed correlations between the time...
Currently, the requirements of service quality in the electric power data network are getting higher and higher, and traffic prediction is an important premise to promote service quality. In order to accurately predict the total traffic of communication channels, a Multi-Applications Comprehensive Traffic Prediction (MACTP) model is proposed in this paper. Differing from F-ARIMA and S-ARIMA models...
Today, the use of learning analytics is becoming more crucial in the learning environment for the purpose of understanding and optimizing students' learning situations. The purpose of this paper is to examine the impacts of Teacher Interventions (TIs) on students' attitudes and achievements involved with the lesson by analyzing their freestyle comment data after every lesson. The current study proposes...
A study is presented aimed at discovering the prime factors that affect the number of suicides in certain regions of India in the year 2011 and subsequently using them to predict the number of suicides in the future. This prediction of suicides can help in making governing decisions in the affected regions such as promoting education and reworking existing facilities. The features in the study refer...
Capillary images obtained from the finger nailfolds are very useful for diagnosis of the health condition of a person. Specific capillaroscopic patterns have been identified for healthy controls as well diseases such as Systemic Sclerosis and Raynaud's phenomenon. Here, six capillary morphological abnormalities act as inputs to response surface regression, generating an output whose range will indicate...
An application of Adaptive Filters (AF) in Desired Signal Extraction (DSE) embedded in Unknown Dynamic System (UDS) is explored in the current research. Least Mean Square Algorithm (LmSA) is utilized in proposed DSE. The UDS is synthesized by adopting Pseudo Random Binary Sequence (PrBS) excitation. To start with the LMSA is educated to converge and adapt its coefficients to the prevailing PRBS signal...
As one of the most correlative impact factors of photovoltaic (PV) power output, the PV module temperature plays very important role in PV power forecasting, but often be confused with ambient temperature. In this paper, the research on impacts of ambient temperature and PV module temperature on power output of PV modules is analyzed to explore the differences and similarities of the two kinds of...
The stability of SRAM cells in high density ICs during read cycle is an extremely critical performance metric for data retention. A frame work to identify the tradeoff between Yield and Static Noise Margin (SNM) in the region of high sigma tail end distributions is presented in this paper. For developing the framework, the sensitivity of SNM is observed for different device variations using Design...
Correctly predicting the passenger flow of an air route is crucial for the airline company to make sales policy. Because of the uncertainties and data inadequacy in the passenger flow prediction of the civil aviation, regression analysis and a grey prediction method are used for predicting and analyzing the passenger flow of the air route in 2016 based on the data of to-and-fro air route of an airline...
While both spectral and prosody transformation are important for voice conversion (VC), traditional methods have focused on the conversion of spectral features with less emphasis on prosody transformation. This paper presents a novel pitch transformation method for VC. As the correlation of spectral features and fundamental frequency in pitch perceptions has been proved, well-converted spectrum should...
The accurate price forecasting of electricity market is crucial for profit maximizing producers and consumers in liberalized power markets. In all market places (day-ahead, intra-day and real-time) accurate price prediction is needed to generate optimal bids and maximize the profit. This paper first presents three methods for forecasting day-ahead market prices, namely Generalized Autoregressive Conditional...
Nowadays flood water level predictions have become one of the most popular subject matter among researcher because this natural disaster damages people's life and property. In addition, flood is also one of the natural disasters that occur frequently around the world. However, since the dynamic of the flood itself is highly nonlinear, it is a very difficult task to predict the flood water level ahead...
This paper presents a novel methodology of objective image quality assessment (IQA) based on Fuzzy Logic (FL) method. The main purpose is to automatically assess the quality of image in agreement with human visual perception. The used attributes (quality metrics) and evaluation criteria (human rating mean opinion score MOS) are extracted from image quality database TID2013. The fuzzy model design...
Early detection of depression is important to improve human well-being. This paper proposes a new method to detect depression through time-frequency analysis of Internet behaviors. We recruited 728 postgraduate students and obtained their scores on a depression questionnaire (Zung Self-rating Depression Scale, SDS) and digital records of Internet behaviors. By time-frequency analysis, we built classification...
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