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This contribution presents a new approach to the prediction of cloud attenuation A on Earth-space links operating in the EHF (Extremely High Frequency) range. The methodology relies on SMOC (Stochastic MOdel of Clouds), which synthesizes high-resolution three-dimensional distributions of the liquid water content w (extent: 200 km×200 km horizontal, 10 km vertical), starting from coarse integral information...
A joint indoor to outdoor ray launching algorithm is proposed in this paper. Different resolutions are considered for indoor and outdoor simulations. Instead of using conventional sampling technique to extract rays from a finer resolution, a novel method, named Ray Aggregation, is applied to minimise the loss of accuracy while benefiting from the computational cost of a coarse resolution. Furthermore,...
Recommender systems are an integral part of today's internet landscape. Recently the enhancement of recommendation services through Linked Open Data (LOD) became a new research area. The ever growing amount of structured data on the web can be used as additional background information for recommender systems. But current approaches in Linked Data recommender systems (LDRS) miss out on an adequate...
A multivariate discrete grey forecasting model is proposed to solve the problem that the qualitative relative factors can't be employed in traditional models. Firstly, a new model is constructed though introducing dummy drivers. Then, the parameters estimation method and recursive function of the model are discussed. Furthermore, dummy driver setting, pre and posttest methods of dummy drivers are...
Tens of thousands of pictures are taken at different locations throughout the year. People often visit places and take pictures to remember their visits. We believe that the seasonal travel patterns of people to specific locations will create a correlation between a location and the season of the images taken in that location. For example, fewer people visit Bear Valley, California during the summer...
The main cause of errors in the navigation of the Global Positioning System (GPS) satellite is the ionospheric delay. Therefore, ionospheric delay forecasting studies play an important role in the reduction of the positioning error. This paper focuses on forecasting of ionospheric delay using the statistical Holt-Winter method during the quiet and disturbed days in October 2011, using GPS Ionospheric...
Previous studies never uses Gompertz model integrated with genetic algorithms to express the evolutions of capital flows although Gompertz model is suitable in the field of statistics, management science, information technology, product innovation, technological forecasting and finance to express the growth diffusions. This work utilizes Gompertz diffusion model integrated with genetic algorithm to...
In this paper, we develop a model of braincontrolled vehicles. This model includes an extended driver model based on the Queuing-network cognitive architecture, a brain-computer interface (BCI) model representing the performance of the BCI system that can issue three classes of direction control commands, an interface model converting the actual steering command from the BCI system to the steering...
Change in a software is crucial to incorporate defect correction and continuous evolution of requirements and technology. Thus, development of quality models to predict the change proneness attribute of a software is important to effectively utilize and plan the finite resources during maintenance and testing phase of a software. In the current scenario, a variety of techniques like the statistical...
The field of network and computer security is a never-ending race with attackers, trying to identify and patch software vulnerabilities before they can be exploited. In this ongoing conflict, it would be quite useful to be able to predict when and where the next software vulnerability would appear. The research presented in this paper is the first step towards a capability for forecasting vulnerability...
Robotic technologies provide accurate, objective, and highly reliable tools for assessment of brain function following stroke. KINARM is an exoskeleton device that uses a number of behavioral tasks to objectively quantify sensorimotor, proprioceptive and cognitive brain function using a battery of behavioral tasks. With a growing number of tasks deployed to more broadly assess different aspects of...
Rainfall prediction is an important part of weather prediction. Compared to conventional methods predicting rainfall rate, the approach applying historical records and data mining technology shows obviously advantage in computing cost. Many excellent works have been done attempting to build predicting model with data mining methods, however, most of them just test the predicting accuracy on data set...
The location of a mobile user is used to deliver context sensitive information like advertisements and deals. Predicting the future possible locations of a mobile user can help target specific services. Nokia provided researchers with data collected from around 200 mobile users over a period of about 2 years for the purpose of research. Previous efforts have attempted either to predict the location...
In continuous casting, it is very important to predict the center segregation of billet in time for ensuring continuous production, improving product quality and reducing production costs. The data in the process of production is used to establish the quality prediction model of center segregation in continuous casting billet, which is based on the improved combination method and ladder parameter...
Occurrence of multiple seizures is a common phenomenon observed in patients with epilepsy: a neurological malfunction that affects approximately 50 million people in the world. Seizure prediction is widely acknowledged as an important problem in the neurological domain, as it holds promise to improve the quality of life for patients with epilepsy. A noticeable number of clinical studies showed evidence...
Routability is one of the primary objectives in placement. There have been many researches on forecasting routing problems and improving routability in placement but no perfect solution is found. Most traditional routability-driven placers aim to improve global routing result, but true routability lies in detailed routing. Predicting detailed routing routability in placement is extremely difficult...
In this case study we investigate software reliability models and their applicability to process improvement at an IT help desk. We propose a model selection framework and demonstrate its success using real help desk incident data from a portfolio of 156 desktop software applications. Incidents are predicted at five intervals and measured against actual numbers of submitted incidents. We analyze incident...
Prediction of protein special structural plays a significant role to better recognize the protein folding patterns. Multiple prediction methods may be used to predict the structures based on the information of sequences and biostatistics. The accuracy, nevertheless, is strongly affected by the efficiency of classification, the robustness of model and other factors. In our research, flexible neutral...
Properly addressing the performance issues presented in database systems is and has been a significant technological challenge, this due to the uncontrolled fluctuation of user requests. Being able to predict the behaviour of such systems can greatly improve their performance. Several prediction methods, such as linear regression and autoregressive moving average, among others, have extensively been...
This paper introduces an enhancement to linguistic forecast representation using Triangular Fuzzy Numbers (TFNs) called Enhanced Linguistic Generation and Representation Approach (ElinGRA). Since there is always an error margin in the predictions, there is a need to define error bounds in the forecast. The interval of the proposed presentation is generated from a Fuzzy logic based Lower and Upper...
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