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SVM (Support Vector Machine), a state of the art classifier model is implemented on a computational mobile platform and its performances are evaluated against a low complexity classifier such as SFSVC (Super Fast Vector Support Classifier) on the same platform. For a better comparison, similar implementation for the two architectures are considered, such as using the same basic linear algebra library...
The paper shows historical aspects of the application of computer-based information systems, providing the process of cosmonaut training for a space flight at the Gagarin Cosmonaut Training Center. These systems include: systems ensuring the operation of simulation complexes for cosmonaut training, computer-assisted instruction systems (computer-assisted simulators), databases for storing the results...
This paper presents a case study based on the experience of implementing a blended learning (BL) approach by SPOC to a Computer General course for all the first year undergraduates in China University of Geosciences (Beijing). It introduces ubiquitous learning environment (ULE), teaching preparation for student-centered learning, and teaching practice of the BL. The study shows that BL approach has...
In mobile interactive web applications, energy-efficient quality-of-service (QoS) scheduling involves setting a deadline for the best user experience and providing just enough performance to minimize energy. Such performance-slacking approaches require precise performance adjustment using execution time prediction. However, prior prediction approaches suffer from prohibitive training due to extensive...
Mobile devices are gaining impact in last few years due to their versatility of platform to run various types of applications. Over the years, the storage of mobile devices is increased but still it cannot fulfill all users requirements. Most of the times, users faced limited memory issues on mobile devices, therefore to free up space users often delete files abruptly without considering the usage...
Many telecommunication companies today have actively started to transform the way they do business, going beyond communication infrastructure providers are repositioning themselves as data-driven service providers to create new revenue streams. In this paper, we present a novel industrial application where a scalable Big data approach combined with deep learning is used successfully to classify massive...
Past studies have shown that there are communication and coordination delays that can disrupt delivery of care to the patient on the day of surgery. Hospitals have introduced information technology to improve the ability of staff to react in a timely fashion, but with mixed success. The research team is developing a mobile application that tracks patient progress, allowing staff to retrieve/send status...
Customer churn analysis is getting immense attention from the business community, especially in the telecommunication sector, to help in generating more revenue. This raises the need for modeling a churn prediction system that is not only accurate but also encompasses comprehensibility and justifiability. Also the judgment ability of the domain expert to identify the drivers of churn and determine...
We design a way to model apps as vectors, inspired by the recent deep learning approach to vectorization of words called word2vec. Our method relies on how users use apps. In particular, we visualize the time series of how each user uses mobile apps as a “document”, and apply the recent word2vec modeling on these documents, but the novelty is that the training context is carefully weighted by the...
Considering rescue operations, natural disasters, military missions, or similar situations, it is vital for a successful mission and for the safety of all action forces to obtain a realistic and up-to-date overview of the operational area. Easy-to-understand three-dimensional visualizations and attached applications for 3D simulation, training, planning, and assistance provide massive additional benefit...
In Human Activity Recognition (HAR) supervised and semi-supervised training are important tools for devising parametric activity models. For the best modelling performance, typically large amounts of annotated sample data are required. Annotating often represents the bottleneck in the overall modelling process as it usually involves retrospective analysis of experimental ground truth, like video footage...
The fundamental goal of education and training is to provide capabilities that can help humans improve performance and accelerate decision-making. Advances in mobile computing (e.g., sensor technology, context aware computing, and cloud computing) allow for the design of systems that goes beyond the traditional methods of simulation training to support adaptive learning. The focus of this paper will...
Skill level estimation is very important since it allows an instructor, a human or an artificial instructor through an intelligent tutoring system, to predict the level of a student and adjust the learning materials accordingly. In this paper, a new approach based on 1-NN (First Nearest Neighbor) is introduced to determine the skill level of a student based on the pattern of skill levels learned over...
Many state-of-the-art emotion classification systems are computationally complex. In this paper we present an emotion distillation framework that decreases the need for computational complex algorithms while maintaining rich, and interpretable, emotional descriptors. These representations are important for emotionally-aware interfaces, which we will increasingly see in technologies such as mobile...
VAMOS (Voice services over Adaptive Multi-user channels on One Slot) technique is the next step in the evolution of GSM voice services. The new method is based on the Adaptive QPSK scheme and VAMOS subchannel power control feature, which ensure that VAMOS is fully compatible with legacy mobiles. In this paper we propose a model for VAMOS network traffic. FR (full rate) and HR (half rate) users associated...
The distributed Tactical Internet (TI) simulative training has been the developing trend nowadays, and its network simulation needed dynamic and real-time requirement. Therefore, the paper proposed a TI simulative training architecture based on High Level Architecture (HLA) firstly, it resolved the distributed simulative training problem of TI. Secondly, the paper proposed a design scheme of TI network...
Mobility is one of the most challenging issues in mobile ad-hoc networks which has a significant impact on performance of network protocols. To cope with this issue, the protocol designers should be able to analyze the movement of mobile nodes in a particular wireless network. In this paper, a new framework called mobility analyzer has been introduced for analysis and recognition of mobility traces...
The two-level synthetical evaluating model is presented in this paper based on the factors of substance and people which affect the industrial product model design and the fuzzy feature existed in the mobile phone model evaluation. And a synthetical evaluation system is formed as to mobile phone by the way of the radial basis function neural network. And it gained a good result from evaluating. Experimental...
We review some recent techniques for 3D tracking and occlusion handling for computer vision-based augmented reality. We discuss what their limits for real applications are, and why object recognition techniques are certainly the key to further improvements.
Recently, the attentions of communication societies are paid to MIMO-OFDM systems. In this paper we propose a new beamforming method to the receive end of MIMO-OFDM systems. To make the method work with fewer known OFDM symbols, oversampling samples are employed and multistage decomposition based on orthogonality of sub-carriers of OFDM signal is used to formulate the beamforming weight vector for...
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