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Probabilistic latent semantic analysis (PLSA) has been widely used in the machine learning community. However, the original PLSAs are not capable of modeling real-valued observations and usually have severe problems with over fitting. To address both issues, we propose a novel, regularized Gaussian PLSA (RG-PLSA) model that combines Gaussian PLSAs and hierarchical Gaussian mixture models (HGMM). We...
This paper firstly provides a general introduction in the most important aspects and ideas of Visual Analytics. This multidisciplinary field focuses on the analytical reasoning of typically large and complex (often heterogeneous) data sets and combines techniques from interactive visualizations with computational analysis methods. Hereby, intuitive and efficient user interactions are a fundamental...
Large IT service providers comprise hundreds or even thousands of system administrators to handle customers' IT infrastructure. As part of the Information Systems that support the decision making of this environment, Incident Management Systems are used and usually provide human resource assignment functionalities. However, the assignment poses several challenges, such as establishing priorities to...
Managing critical infrastructures under the growing cyber-threat is becoming a matter of international urgency. The volume and frequency of cyber-related incidents on the rise yearly, and the level of sophistication is increasing. Critical infrastructures are key service providers and heavily interconnected, meaning any damaging impact would result in devastating consequences and potential cascading...
Synthesis of natural sounding speech is the greatest challenge in a Text-to-Speech Synthesis (TTS) system. In natural speech, duration, intensity and pitch are dynamically varied which is manifested as rhythm or prosody of speech. If these variations are not recreated, the synthesized speech will sound robotic. Synthesis of good quality speech depends on how well the duration and intonation patterns...
Nowadays people's life become more rich and convenient than before, but the obesity also become a problem with people. One cause of obesity is lack of exercise. Although the reason is known by people and the method of keeping health is self maintenance, but it is hard for most people, especially the elderly people. Because of this, we design a daily exercise support application, which is based on...
The concepts of wellbeing, globalization and sustainability are analyzed. The advantages and disadvantages of the present globalization situation and the measures set out in Literature to correct the disadvantages and to empower the advantages are studied. The main methods to find the best way to intervene in the world system with the purpose of improving the sustainability of the human style of life...
With the popularity of Internet of Things, the next logical step will focus on the application layer on top of network connectivity, especially Web of Things. While most of the existing efforts on Web of Things are focused on device mash up and data collection, in this paper a semantic web of things framework is proposed to leverage Semantic Web as the unified mechanism for monitoring, tasking, presentation,...
Modern robotic platforms, deployed for environmental monitoring and mapping, are able to rapidly accumulate large data sets. Whilst the data sets collected by these platforms are highly descriptive, they are often too large for human experts to analyse exhaustively. Although the large data sets could be analysed by humans in principle, the amount of labour and time required to process them is not...
Service robots that work together with humans in domestic and constantly changing environments should have a general understanding about their human partners and the tasks that are to be performed. This would enable them to verify their beliefs about the common tasks and the goals of their human partners and detect unexpected events and failures. In this paper we present a way of acquiring general,...
We are developing online interactive materials that allow students to adapt their text and homework to their own needs and interests. For example, students may specify topic areas of interest and then selected mathematics homework word problems are adapted to those areas. Using proper data management, their work can be hand-graded with feedback for the students and allowances for students to correct...
In this paper, we propose an online algorithm for multimodal categorization based on the autonomously acquired multimodal information and partial words given by human users. For multimodal concept formation, multimodal latent Dirichlet allocation (MLDA) using Gibbs sampling is extended to an online version. We introduce a particle filter, which significantly improve the performance of the online MLDA,...
Today, Virtual Reality (VR) technology has been applied in various fields, and the effects of inducing VR contents in humans have been studied. Generally, VR contents mainly consist of visual stimulation and it is considered that it influences the recognition mechanisms in the human brain, the behaviors in the human body and so on. In this research, in order to construct a methodology of VR content...
With the fast progress of mobile computing, personal lifelogging gets easier taking a little effort for automation. However data-recalling services to help a user locate or remind the event in her lifelogs still lacks supports in major aspects due to the difficulty in creating a useful environment for users. This is because a collection of lifelog streams needs high-level behavior analysis techniques...
In this paper we proposed a new method for selecting a smoothing parameter in kernel estimator to estimate a nonparametric regression function in the presence of missing values. The proposed method is based on work on the golden ratio and Surah AL-E-Imran in the Qur'an. Simulation experiments were conducted to study a small sample behavior. The results proved the superiority the proposed on the competition...
Advanced Driver Assistant Systems act, by definition in natural, often poorly structured, environments and are supposed to closely interact with human operators. Both, natural environments as well as human behaviour have no inherent metric and can not be modelled/measured in the classical way physically plausibly behaving systems are described.
Autonomous vehicles have seen great advancements in recent years, and such vehicles are now closer than ever to being commercially available. The advent of driverless cars provides opportunities for optimizing traffic in ways not possible before. This paper introduces an open source multiagent microscopic traffic simulator called AORTA, which stands for Approximately Orchestrated Routing and Transportation...
This paper investigates the applicability of a mixed effects model in predicting Quality of Experience (QoE) in World Wide Web based multi-media services. An analysis is presented on objective factors and a human factor that may impact on outcomes of observations as fixed effects, population mean, and random effects, group specific, and account for a correlation structure of variations amongst users...
For smart home researchers, it is essential to test activity recognition algorithms with various sets of sensory data. However, diverse sensory datasets are not always available due to several constraints, including limited budgets. Consequently, smart home simulators have recently grown in importance. However, there is still a need for realistic synthetic sensory data. This paper presents a simulator,...
We present a novel unsupervised learning method for human action categories from video sequences using Latent Dirichlet Markov Clustering (LDMC). Video sequences are represented by a novel "bag-of-words" representation, where each frame corresponds to a "word". The algorithm automatically learns the probability distributions of the words and the intermediate topics corresponding...
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