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The state and the fault prediction for the measure & control equipment in the test range plays an important role in the test and evaluation for the large-scale weapon system. It is also a research development in the state or fault process region. The objective of this paper is to address a state or fault prediction method for the equipment in the test range, which is combined with the physical...
The emergence of computing power and the abundance of data have made it possible to assist human decisions, especially in the stock markets, in which the ability to predict future values would lower the risk of investing. In this paper, we present a new approach for identifying the predictive power of public emotions extracted from various sections of daily news articles on the movements of stock...
Question and Answering (Q&A) platforms are an important source for information and a first place to go when searching for help. Q&A sites, like StackOverflow (SO), use reward systems to incentivize users to answer fast and accurately. In this paper we study and predict the response time for those questions on StackOverflow, that benefit from an additional incentive through so called bounties...
This paper puts forward a testability modeling method for analog circuit fault prediction. It firstly gets the grey correlation entropy of each test point in the analog circuit. Then it treats each grey correlation entropy as a correlation coefficient to form the dependency matrix of testability. After that, according to the dependency matrix we get, the paper uses the method of PSO (Particle Swarm...
The intent of our study, conducted on a sample of 98 psychiatric outpatients, was to explore the correlations between executive functions and traits of temperament and character. Executive functions were assessed through Frontal Assessment Battery and the traits of temperament and character using the Temperament and Character Inventory. From our sample, a significant link between certain traits of...
A cloud platform website, offering a catalog of services, operates under a freemium business model or a free trial business model, aggressively marketing to customers who have previously visited. In such a cloud platform or service business, accurate identification of high profile customers is central to the success for the business. However, there are several limitations of existing approaches because...
Good Quality of Experience is critical to the success of IPTV business development and promotion. To this end, the paper combines status data from the set-top box with the data of user's complaints and then selects the appropriate model to predict user's QoE. Firstly, we clean and conduct some statistical analysis for the dataset. Then, random under-sampling and synthetic over-sampling are applied...
The man-hour costing is the largest cost in the chemical plant design companies because the design processes are undertaken by the staff. The accurate man-hour forecasting can facilitate the design process control and the human resources scheduling optimization so as to cut the costs. This paper presents a framework, combining the Back Propagation (BP) Artificial Neural Network (ANN) and Genetic Algorithm...
Forecasting volatility in the stock market is an important research topic that has been immensely reviewed over the years. However, in Sri Lankan context this research topic is studied by only few researchers and they did not incorporate the day of the week effect in their studies. Therefore, this study examines the impact of the day of the week effect on All Share Price Index (ASPI) of Colombo Stock...
Social networks are known to form on the basis of homophily, where nodes with some type of similar characteristics are more likely to be connected. Some of the most fundamental human characteristics are reflected by an individual's personality, which represents a persistent disposition governing a human's outlook and approach to diverse situations. While taking into account demographics of age and...
The onset of fetal pathologies can be screened during pregnancy by means of Fetal Heart Rate (FHR) monitoring and analysis. Noticeable advances in understanding FHR variations were obtained in the last twenty years, thanks to the introduction of quantitative indices extracted from the FHR signal. This study searches for discriminating Normal and Intra Uterine Growth Restricted (IUGR) fetuses by applying...
Stroke is a major cause of mortality and long-term disability in the world. Predictive outcome models in stroke are valuable for personalized treatment, rehabilitation planning and in controlled clinical trials. We design a new multi-class classification model to predict outcome in the short-term, the putative therapeutic window for several treatments. Our model addresses the challenges of class imbalance,...
The lack of the historical data of new rail line makes the passenger flow distribution prediction be a challenge. Traditional methods always use simple factors, which can not reflect the complexity of OD distribution. This paper proposes a novel passenger flow distribution prediction method based on multi-factor model. This method obtains quantitative impact factors of OD distribution by analyzing...
This preliminary study investigates feasibility of a running speed based heart rate (HR) prediction. It is basically motivated from the assumption that there is a significant relationship between HR and the running speed. In order to verify the assumption, HR and running speed data from 217 subjects of varying aerobic capabilities were simultaneously collected during an incremental treadmill exercise...
Trust model has been suggested as an effective security mechanism in distributed network environment. Considerable researches have been done on trust evaluation and trust prediction. Traditional methods take the historical behavior data into consideration to predict the trust value of the network entity. However, the context of the network entity is seldom taken into account. It is obvious that the...
Social network is a hot topic of interest for the researchers in the field of computer science in recent years. The vast amount of data generated by these social networks play a very important role in information diffusion. Social network data are generated by its users. So, user's behavior and activities are being investigated by the researchers to get a logical view of social network platform. This...
To improve the prediction precision of residential property, the paper brings up a mixed optimizing model based on IPSO-BPNN. The model has adopted gray correlation theory to optimized the the index that influences price and use IPSO to optimize the definition of original weights and threshold value. We take the real estate market in Changsha as an example. The result shows that the speed of convergence...
The accuracy of network traffic prediction has received significant interest in various domains, such as capacity planning, anomaly detection, admission control, and traffic engineering. For large-time scale traffic variation, it shows both a daily pattern and an hour pattern, which means the model based on single trend has not met the needs of prediction. Therefore, by dealing with the internal relationship...
In this article, we apply different machine learning (ML) techniques for building objective models, that permit to automatically assess the image quality in agreement with human visual perception. The six ML methods proposed are discriminant analysis, k-nearest neighbors, artificial neural network, non-linear regression, decision tree and fuzzy logic. Both the stability and the robustness of designed...
Vegetation index derived from remote sensing measurement servers as the significant reference for crop growing monitor and agricultural disaster forecasting. Vegetation index forecasting at long lead time and appropriate spatial scale is critical for decision making to mitigate the impacts from agricultural disaster. In previous studies, vegetation index forecasting has been studied and implemented...
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