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Human User (human + user)
Selected AbstractsInvestigating the potential neurotoxicity of Ecstasy (MDMA): an imaging approachHUMAN PSYCHOPHARMACOLOGY: CLINICAL AND EXPERIMENTAL, Issue 8 2001Liesbeth Reneman Abstract Human users of 3,4-methylenedioxymethamphetamine (MDMA, ,Ecstasy') users may be at risk of developing MDMA-induced neuronal injury. Previously, no methods were available for directly evaluating the neurotoxic effects of MDMA in the living human brain. However, development of in vivo neuroimaging tools has begun to provide insights into the effects of MDMA in the human brain. In this review, contributions of brain imaging studies on the potential neurotoxic effects of MDMA and functional consequences are highlighted. An overview is given of PET, SPECT and MR spectroscopy studies, most of which show evidence of neuronal injury in MDMA users. Different neuroimaging tools are discussed that have investigated potential functional consequences of MDMA-induced 5-HT neurotoxic lesions. Finally, the contribution of brain imaging in future studies is discussed, emphasising the crucial role it will play in our understanding of MDMA's short- and long-term effects in the human brain. Copyright © 2001 John Wiley & Sons, Ltd. [source] Towards closing the analysis gap: Visual generation of decision supporting schemes from raw dataCOMPUTER GRAPHICS FORUM, Issue 3 2008T. May Abstract The derivation, manipulation and verification of analytical models from raw data is a process which requires a transformation of information across different levels of abstraction. We introduce a concept for the coupling of data classification and interactive visualization in order to make this transformation visible and steerable for the human user. Data classification techniques generate mappings that formally group data items into categories. Interactive visualization includes the user into an iterative refinement process. The user identifies and selects interesting patterns to define these categories. The following step is the transformation of a visible pattern into the formal definition of a classifier. In the last step the classifier is transformed back into a pattern that is blended with the original data in the same visual display. Our approach allows in intuitive assessment of a formal classifier and its model, the detection of outliers and the handling of noisy data using visual pattern-matching. We instantiated the concept using decision trees for classification and KVMaps as the visualization technique. The generation of a classifier from visual patterns and its verification is transformed from a cognitive to a mostly pre-cognitive task. [source] An approach to the linguistic summarization of time series using a fuzzy quantifier driven aggregationINTERNATIONAL JOURNAL OF INTELLIGENT SYSTEMS, Issue 5 2010Janusz Kacprzyk We extend our previous work on the linguistic summarization of time series data meant as the linguistic summarization of trends, i.e. consecutive parts of the time series, which may be viewed as exhibiting a uniform behavior under an assumed (degree of) granulation, and identified with straight line segments of a piecewise linear approximation of the time series. We characterize the trends by the dynamics of change, duration, and variability. A linguistic summary of a time series is then viewed to be related to a linguistic quantifier driven aggregation of trends. We primarily employ for this purpose the classic Zadeh's calculus of linguistically quantified propositions, which is presumably the most straightforward and intuitively appealing, using the classic minimum operation and mentioning other t -norms. We also outline the use of the Sugeno and Choquet integrals proposed in our previous papers. We show an application to the absolute performance type analysis of time series data on daily quotations of an investment fund over an 8-year period, by presenting first an analysis of characteristic features of quotations, under various (degrees of) granulations assumed, and then by listing some more interesting and useful summaries obtained. We propose a convenient presentation of linguistic summaries focused on some characteristic feature exemplified by what happens "almost always," "very often," "quite often," "almost never," etc. All these analyses are meant to provide means to support a human user to make decisions. © 2010 Wiley Periodicals, Inc. [source] Safe planning for human-robot interactionJOURNAL OF FIELD ROBOTICS (FORMERLY JOURNAL OF ROBOTIC SYSTEMS), Issue 7 2005Dana Kuli This paper presents a strategy for improving the safety of human-robot interaction by minimizing a danger criterion during the planning stage. This strategy is one part of the overall methodology for safe planning and control in human-robot interaction. The focus application is a hand-off task between an articulated robot and an inexpert human user. Two formulations of the danger criterion are proposed: a criterion assuming independent safety-related factors, and a criterion assuming mutually dependent factors. Simulations of the proposed planning strategy are presented for both 2D and 3D robots. The results indicate that a criterion based on scaled mutually dependent factors such as the robot inertia and the human robot distance generates safe, feasible paths for interaction. © 2005 Wiley Periodicals, Inc. [source] Design of a virtual environment aided by a model-based formal approach using DEVS,CONCURRENCY AND COMPUTATION: PRACTICE & EXPERIENCE, Issue 11 2009Azzedine Boukerche Abstract Virtual environment (VE) is a modern computer technique that aims to provide an attracting and meaningful human,computer interacting platform, which can essentially help the human users to learn, to play or to be trained in a ,like-real' situation. Recent advances in VE techniques have resulted in their being widely used in many areas, in particular, the E-learning-based training applications. Many researchers have developed the techniques for designing and implementing the 3D virtual environment; however, the existing approaches cannot fully catch up the increasing complexity of modern VE applications. In this paper, we designed and implemented a very attracting web-based 3D virtual environment application that aims to help the training practice of personnel working in the radiology department of a hospital. Furthermore, we presented a model-based formal approach using discrete event system specification (DEVS) to help us in validating the X3D components' behavior. As a step further, DEVS also helps to optimize our design through simulating the design alternatives. Copyright © 2009 John Wiley & Sons, Ltd. [source] Brand specific responses to smokeless tobacco in a rat lip canal modelJOURNAL OF ORAL PATHOLOGY & MEDICINE, Issue 6 2010Joel L. Schwartz J Oral Pathol Med (2010) 39: 453,459 Background:, Different compositions of smokeless tobacco (ST) are widely thought to cause oral carcinoma at different rates but there is little direct evidence for this hypothesis. Methods:, We used a rat lip canal model to examine the mucosal changes induced by chronic daily exposure to four different brands of ST: Skoal, Copenhagen, Ettan Swedish Snus, and Stonewall, differing in measured levels of: tobacco specific nitrosamines (TSNAs), unprotonated nicotine, moisture, and pH. Results:, Exposure to the lip canal for 12 months produced changes in the mucosa marked by increases in S phase and M phase cells for the Skoal and Copenhagen exposed rats. This correlated with the high level of TSNAs and nicotine in these products. All the tobacco products, to different degrees, induced sites of moderate to severe dysplasia some with extensive rete peg outgrowth from the oral mucosa not seen in the controls. Many of these sites showed a loss of p16 expression. Conclusions:, While all ST products caused dysplasia, the products with lower levels of TSNAs and unprotonated nicotine caused less, consistent with the model that tobacco with low levels of nitrosamines might potentially induce fewer carcinomas in human users. [source] Mining related queries from Web search engine query logs using an improved association rule mining modelJOURNAL OF THE AMERICAN SOCIETY FOR INFORMATION SCIENCE AND TECHNOLOGY, Issue 12 2007Xiaodong Shi With the overwhelming volume of information, the task of finding relevant information on a given topic on the Web is becoming increasingly difficult. Web search engines hence become one of the most popular solutions available on the Web. However, it has never been easy for novice users to organize and represent their information needs using simple queries. Users have to keep modifying their input queries until they get expected results. Therefore, it is often desirable for search engines to give suggestions on related queries to users. Besides, by identifying those related queries, search engines can potentially perform optimizations on their systems, such as query expansion and file indexing. In this work we propose a method that suggests a list of related queries given an initial input query. The related queries are based in the query log of previously submitted queries by human users, which can be identified using an enhanced model of association rules. Users can utilize the suggested related queries to tune or redirect the search process. Our method not only discovers the related queries, but also ranks them according to the degree of their relatedness. Unlike many other rival techniques, it also performs reasonably well on less frequent input queries. [source] | |||||||||||||