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9th International Conference on Advanced computing and Communication Technologies (ICACCT)

作者： Malviya, Shrikant Singh, Vivek Kr. Umrao, Jigyasa Indian Inst Informat Technol Allahabad Dept Informat Technol Allahabad Uttar Pradesh India

ISBN: (纸本)9789811010231;9789811010217

Nowadays affective computing is one of the most interesting and challenging research areas among the human computer interaction (HCI) researchers. One of the potential applications of emotion detection is to analyze confidence level of a speaker. In human-computer or human-human interaction systems, speech based confidence level check can provide users with improved services. Confidence level checking would be useful in various applications e.g. job recruitment process. In this paper a solution to similar kind of applications is proposed to differentiate between a confident person and non-confident person. A set of speech features have been selected empirically to support the concept that speech conveys not only the linguistic messages, but also emotional content. A protruding result has been sought on using SVM and KNN classifiers in determining confidence level of a human. The accuracy and efficiency of result is found good and reliable.

关键词： human-centered computing Speech analysis Feature extraction Feature analysis Affective computing

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Externalization of Data Analytics Models: Toward human-centered Visual Analytics 18th

Externalization of Data Analytics Models: Toward Human-Cente...

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18th International Conference on human-Computer Interaction (HCI International)

作者： Didandeh, Arman Sedig, Kamran Univ Western Ontario Dept Comp Sci London ON Canada Univ Western Ontario Fac Informat & Media Studies London ON Canada

ISBN: (纸本)9783319403496;9783319403489

Visual analytics tools (VATs) can support the execution of complex cognitive activities. Most VATs make use of analytics models in the execution of data-intensive activities. However, due to their non-transparent and black box nature, analytics models are hard to use. This leads to a lower degree of understandability of the models, which then results in a lack of trust and applicability. To overcome this problem and to help bring VATs closer in line with users' mental models, we introduce a framework for the externalization of analytics models in VATs. In doing so, we propose the use of scaffolding to provide the users with visual support in the execution of their cognitive activities. The aim is to make VATs more human-centered. To demonstrate the application of the externalization framework, we present two components of a visual analytics tool named VARSITY.

关键词： Visual analytics Cognitive activity Scaffolding Externalization human-centered computing

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Personality differences predict decision-making in an accident situation in virtual driving 18

Personality differences predict decision-making in an accide...

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IEEE Virtual Reality Conference (IEEE VR)

作者： Ju, Uijong Kang, June Wallraven, Christian Korea Univ Dept Brain & Cognit Engn Seoul South Korea Korea Univ Dept Biomed Sci Seoul South Korea Empathy Res Inst Seoul South Korea

ISBN: (纸本)9781509008360

Understanding how humans make decisions in challenging situations - such as trying to save peoples' lives even though this endangers one's own life - is crucial in optimizing rescue operations and dealing with natural disasters and other crises. The experimental study of these decisions, however, has often been done using text-based surveys, which is known to emphasize rational and reflective judgments. Here, we used virtual reality to investigate decision-making in a real-world context, in which a decision needs to be made intuitively under time pressure - for this we simulated an accident situation in an immersive virtual driving scenario. In the scenario, participants were told to race a course as fast as possible. After training, participants were confronted with the sudden appearance of pedestrians on the race course. We observed three different behaviors: group one ignored the pedestrians and/or hit the accelerator, group two hit the brake, and group three tried to steer the car to avoid pedestrians. We found that most Avoid-group participants had more real and virtual driving experience compared to the other two groups and they also felt more competent during the game as measured by subjective game experience questionnaires. Importantly, results from established personality questionnaires showed that participants who did not brake (therefore potentially harming the pedestrians) had significantly lower scores in perspective-taking and higher scores in psychopathy compared to participants who tried to avoid the accident situation. Our results demonstrate that personality differences to some degree are able to predict intuitive decision-making and that such processes can be studied in a controlled, immersive VR simulation.

关键词： Virtual reality decision-making driving Simulation moral judgments personality differences computing methodologies Virtual reality Applied computing Psychology Software and its engineering Interactive games human-centered computing Laboratory experiments

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Power-Aware computing in Wearable Sensor Networks: An Optimal Feature Selection

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IEEE TRANSACTIONS ON MOBILE computing 2015年第4期14卷 800-812页

作者： Ghasemzadeh, Hassan Amini, Navid Saeedi, Ramyar Sarrafzadeh, Majid Washington State Univ Sch Elect Engn & Comp Sci Pullman WA 99164 USA Univ Calif Los Angeles Jules Stein Eye Inst Los Angeles CA 90095 USA Univ Calif Los Angeles Wireless Hlth Inst Los Angeles CA 90095 USA Univ Calif Los Angeles Dept Comp Sci Los Angeles CA 90095 USA

Wearable sensory devices are becoming the enabling technology for many applications in healthcare and well-being, where computational elements are tightly coupled with the human body to monitor specific events about their subjects. Classification algorithms are the most commonly used machine learning modules that detect events of interest in these systems. The use of accurate and resource-efficient classification algorithms is of key importance because wearable nodes operate on limited resources on one hand and intend to recognize critical events (e.g., falls) on the other hand. These algorithms are used to map statistical features extracted from physiological signals onto different states such as health status of a patient or type of activity performed by a subject. Conventionally selected features may lead to rapid battery depletion, mainly due to the absence of computing complexity criterion while selecting prominent features. In this paper, we introduce the notion of power-aware feature selection, which aims at minimizing energy consumption of the data processing for classification applications such as action recognition. Our approach takes into consideration the energy cost of individual features that are calculated in real-time. A graph model is introduced to represent correlation and computing complexity of the features. The problem is formulated using integer programming and a greedy approximation is presented to select the features in a power-efficient manner. Experimental results on thirty channels of activity data collected from real subjects demonstrate that our approach can significantly reduce energy consumption of the computing module, resulting in more than 30 percent energy savings while achieving 96.7 percent classification accuracy.

关键词： Real-time systems and embedded systems emerging technologies wearable computers healthcare human-centered computing signal processing ubiquitous computing low-power design optimization

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Person-centered accessible technologies and computing solutions through interdisciplinary and integrated perspectives from disability research

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UNIVERSAL ACCESS IN THE INFORMATION SOCIETY 2015年第3期14卷 415-426页

作者： Panchanathan, Sethuraman McDaniel, Troy Arizona State Univ Ctr Cognit Ubiquitous Comp Tempe AZ 85281 USA

human-centered computing and human-centered multimedia computing (HCMC) have emerged as important subfields of computational science which leverage the social and behavioral sciences toward improving the usability of technologies and multimedia systems. While technological solutions have made significant strides for the broader population, individuals with disabilities have been largely ignored, often having to force-fit or adapt themselves to available solutions. The authors first introduced a methodology to enrich HCMC by considering perspectives from individuals with disabilities. They subsequently introduced a person-centered approach to HCMC known as person-centered multimedia computing (PCMC). In the proposed work, they seek to further enrich the PCMC methodology by incorporating interdisciplinary inspirations that take into account the diverse challenges associated with assistive technology design and deployment. Several applications are presented, highlighting how considerations of technology, adaptation and policy from a disability perspective can enrich the design of person-centered accessible technologies. This approach has been implemented through ongoing work on a NSF IGERT project, "Alliance for Person-centered Accessible Technologies," details of which are also provided in this paper.

关键词： Assistive technology human-centered computing Person-centered computing Disability research

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MM4DM: How Multimedia Enrolls Decision-Making Processes in the Era of Cognitive computing 16

MM4DM: How Multimedia Enrolls Decision-Making Processes in t...

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Proceedings of the 22nd Brazilian Symposium on Multimedia and the Web

作者： Marcio Ferreira Moreno Rafael Rossi de Mello Brandao Renato Cerqueira IBM Research | Brazil Rio de Janeiro Brazil

ISBN: (纸本)9781450345125

The increasing momentum towards cognitive computing unlocks a diverse set of opportunities and challenges for the multimedia research area. In fact, with a different approach from the one present in the traditional artificial intelligence systems, cognitive computing glimpses a human-machine collaboration, where a more symbiotic interaction is required. The main goal of the Multimedia for Decision-Making (MM4DM) tutorial is to discuss how the multimedia research area enrolls decision-making processes in the era of cognitive computing. In this context, this tutorial discusses topics of multidisciplinary interest, always from a multimedia perspective, aiming to inspire heterogeneous participation of researchers from industry and academia.

关键词： decision-making processes hypermedia conceptual models mulsemedia hypermedia and multimedia systems cognitive computing systems media synchronism human-centered computing

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Connecting Brains and Bodies: Applying Physiological computing to Support Social Interaction

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INTERACTING WITH COMPUTERS 2015年第5期27卷 534-550页

作者： Chanel, Guillaume Muehl, Christian Univ Geneva Swiss Ctr Affect Sci CH-1202 Geneva Switzerland Aerosp Med Flight Physiol German Aerosp Ctr D-51147 Cologne Germany

Physiological and affective computing propose methods to improve human-machine interactions by adapting machines to the users' states. Recently, social signal processing (SSP) has proposed to apply similar methods to human-human interactions with the hope of better understanding and modeling social interactions. Most of the social signals employed are facial expressions, body movements and speech, but studies using physiological signals remain scarce. In this paper, we motivate the use of physiological signals in the context of social interactions. Specifically, we review studies which have investigated the relationship between various physiological indices and social interactions. We then propose two main directions to apply physiological SSP: using physiological signals of individual users as new social cues displayed in the group and using inter-user physiology to measure properties of the interactions such as conflict and social presence. We conclude that physiological measures have the potential to enhance social interactions and to connect people.

关键词： Collaborative interaction Collaborative and social computing human-centered computing Law social en behavioral sciences Affective computing Physiological computing

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Lower rates of receiving model for end-stage liver disease exception and longer time to transplant among nonalcoholic steatohepatitis hepatocellular carcinoma

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LIVER TRANSPLANTATION 2016年第10期22卷 1356-1366页

作者： Young, Kellie Aguilar, Maria Gish, Robert Younossi, Zobair Saab, Sammy Bhuket, Taft Liu, Benny Ahmed, Aijaz Wong, Robert J. Univ Calif San Francisco Sch Med San Francisco CA USA Alameda Hlth Syst Highland Hosp Div Gastroenterol & Hepatol Oakland CA USA Santa Clara Valley Med Ctr Dept Med San Jose CA 95128 USA Stanford Univ Sch Med Div Gastroenterol & Hepatol Palo Alto CA 94304 USA Ctr Liver Dis Dept Med Falls Church VA USA Inova Hlth Syst Betty & Guy Beatty Ctr Integrated Res Falls Church VA USA Univ Calif Los Angeles David Geffen Sch Med Dept Med Los Angeles CA 90095 USA Univ Calif Los Angeles David Geffen Sch Med Dept Surg Los Angeles CA 90095 USA

Receiving Model for End-Stage Liver Disease (MELD) exception status for hepatocellular carcinoma (HCC) improves wait-list survival and probability of liver transplantation (LT). We aim to evaluate etiology-specific disparities in MELD exception, LT wait-list times, and post-LT outcomes among patients with HCC listed for LT. Using United Network for Organ Sharing 2004-2013 data, we evaluated adults (age>18 years) with HCC secondary to hepatitis C virus (HCV), nonalcoholic steatohepatitis (NASH), alcoholic cirrhosis (EtOH), hepatitis B virus (HBV), combined EtOH/HCV, and combined HBV/HCV. Multivariate regression models evaluated etiology-specific odds of active exception, probability of receiving LT, and post-LT survival. In total, 10,887 HCC patients were listed for LT from 2004 to 2013. Compared with HCV-HCC patients (86.8%), patients with NASH-HCC (67.7%), and EtOH-HCC (64.4%) had a lower proportion with active MELD exception (P<0.001). On multivariate regression, NASH-HCC and EtOH-HCC patients had significantly lower odds of active MELD exception compared with HCV-HCC (NASH-HCCodds ratio [OR], 0.73;95% confidence interval [CI], 0.58-0.93;P=0.01;EtOH-HCCOR, 0.72;95% CI, 0.59-0.89;P=0.002). Compared with HCV-HCC patients, NASH-HCC (HR, 0.83;95% CI 0.76-0.90;P<0.001), EtOH-HCC (HR, 0.88;95% CI 0.81-0.96;P=0.002), and EtOH/HCV-HCC (HR, 0.92;95% CI 0.85-0.99;P=0.03) were less likely to receive LT if they had active exception. Without active exception, these discrepancies were more significant (NASH-HCCHR, 0.22;95% CI, 0.18-0.27;P<0.001;EtOH-HCCHR, 0.22;95% CI, 0.18-0.26;P<0.001;EtOH/HCV-HCCHR, 0.26;95% CI, 0.22-0.32;P<0.001). In conclusion, among US adults with HCC listed for LT, patients with NASH-HCC, EtOH-HCC, and EtOH/HCV-HCC were significantly less likely to have active MELD exception compared with HCV-HCC, and those without active exception had a lower likelihood of receiving LT. More research is needed to explore why NASH-HCC patients were less likely to have ac

关键词： Level Trigger Exception End Stage Liver Disease Nonalcoholic Steatohepatitis time of transplanting human-centered computing

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human Endogenous Retroviruses-K (HML-2) Expression Is Correlated with Prognosis and Progress of Hepatocellular Carcinoma

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BIOMED RESEARCH INTERNATIONAL 2016年第0期2016卷 8201642-8201642页

作者： Ma, Weijie Hong, Zhenfei Liu, Hailing Chen, Xi Ding, Lu Liu, Zhisu Zhou, Fuling Yuan, Yufeng Wuhan Univ Dept Hepatobiliary & Pancreat Surg Zhongnan Hosp Wuhan 430071 Peoples R China Xi An Jiao Tong Univ Sch Med Affiliated Hosp 2 Dept Clin Hematol Xian 710004 Peoples R China Wuhan Univ Zhongnan Hosp Dept Clin Hematol Wuhan Peoples R China

Background. The association between human endogenous retroviruses-K (HERV-K) (HML-2) and human disease, including a variety of cancers, has been indicated. However, the function of HERV-K (HML-2) in the progression of hepatocellular carcinoma (HCC) still remains largely unclear. Methods. We detected the expression of HERV-K (HML-2) in 84 HCC tissues and adjacent nontumor tissues by quantitative real-time PCR (qRT-PCR) and analyzed its correlation with the clinical parameters. Result. The HEVR-K level was significantly increased in HCC compared with adjacent normal tissues (P < 0.01) which was proved to be significantly associated with cirrhosis (P < 0.05), tumor differentiation (P < 0.05), and TNM stage (P < 0.05). Moreover, the high expression of HERV-K (HML-2) had a poorer overall survival than patients with lower expression by a Kaplan-Meier survival analysis (P < 0.01). The multivariate Cox regression analysis indicated that the level of HERV-K (HML-2) was an independent prognostic factor for the overall survival rate of HCC patients. Receiver operating characteristic (ROC) curves demonstrated the diagnostic accuracy of HERV-K (HML-2) expression in HCC (AUC = 0.729, 74.7% sensitivity, and 67.8% specificity). Conclusions. Our results suggested that upregulation of HERV-K (HML-2) in HCC patients was significantly related to cancer progression and poor outcome, indicating that HERV-K (HML-2) might be a novel candidate prognostic biomarker for HCC.

关键词： Prognostic Factors diagnosis quality/standard Tumor Progression regression analysis ROC Curve human-centered computing

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A User-Independent and Sensor-Tolerant Wearable Activity Classifier

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COMPUTER 2015年第10期48卷 64-+页

作者： Blake, Madison Younes, Rabih Dennis, Jacob Martin, Thomas L. Jones, Mark Heron Syst Lexington Pk MD USA Virginia Tech Comp Engn Blacksburg VA USA Virginia Tech Blacksburg VA USA Virginia Tech Bradley Dept Elect & Comp Engn Blacksburg VA USA

An activity classifier based on an abstract model of the human body is suitable for use in an e-textile monitoring system without the need to retrain the recognition model to accommodate different users, sensor types,... 详细信息

关键词： pattern classification pose estimation sensors textiles wearable computers abstract model e-textile monitoring system human body recognition model user-independent sensor-tolerant wearable activity classifier Biological system modeling Biomedical monitoring Clothing Data models Monitoring Quaternions Training HCI activity classification activity monitoring e-textiles human-centered computing human-computer interaction medical computing pattern recognition sensors wearable computers wearable computing

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