Evidence-Efficient Affinity Propagation Scheme for Virtual Machine Placement in Data Center

In cloud data center, without efficient virtual machine placement, the overload of any types of resources on physical machines (PM) can easily cause the waste of other types of resources, and frequent costly virtual machine (VM) migration, which further negatively affects quality of service (QoS). To address this problem, in this paper we propose an evidence-efficient affinity propagation scheme for VM placement (EEAP-VMP), which is capable of balancing the workload across various types of resources on the running PMs. Our approach models the problem of searching the desirable destination hosts for the liveVMmigration as the propagation of responsibility and availability. The sum of responsibility and availability represent the accumulated evidence for the selection of candidate destination hosts for the VMs to be migrated. Further, in combination with the presented selection criteria for destination hosts. Extensive experiments are conducted to compare our EEAP-VMP method with the previousVMplacement methods. The experimental results demonstrate that the EEAP-VMP method is highly effective on reducing VM migrations and energy consumption of data centers and in balancing the workload of PMs

Privacy-Preserving Community Detection for Locally Distributed Multiple Networks

Modern multi-layer networks are commonly stored and analyzed in a local and distributed fashion because of the privacy, ownership, and communication costs. The literature on the model-based statistical methods for community detection based on these data is still limited. This paper proposes a new method for consensus community detection and estimation in a multi-layer stochastic block model using locally stored and computed network data with privacy protection. A novel algorithm named privacy-preserving Distributed Spectral Clustering (ppDSC) is developed. To preserve the edges' privacy, we adopt the randomized response (RR) mechanism to perturb the network edges, which satisfies the strong notion of differential privacy. The ppDSC algorithm is performed on the squared RR-perturbed adjacency matrices to prevent possible cancellation of communities among different layers. To remove the bias incurred by RR and the squared network matrices, we develop a two-step bias-adjustment procedure. Then we perform eigen-decomposition on the debiased matrices, aggregation of the local eigenvectors using an orthogonal Procrustes transformation, and k-means clustering. We provide theoretical analysis on the statistical errors of ppDSC in terms of eigen-vector estimation. In addition, the blessings and curses of network heterogeneity are well-explained by our bounds

Gaze modulated disambiguation technique for gesture control in 3D virtual objects selection

© 2017 IEEE. Inputs with multimodal information provide more natural ways to interact with virtual 3D environment. An emerging technique that integrates gaze modulated pointing with mid-air gesture control enables fast target acquisition and rich control expressions. The performance of this technique relies on the eye tracking accuracy which is not comparable with the traditional pointing techniques (e.g., mouse) yet. This will cause troubles when fine grainy interactions are required, such as selecting in a dense virtual scene where proximity and occlusion are prone to occur. This paper proposes a coarse-to-fine solution to compensate the degradation introduced by eye tracking inaccuracy using a gaze cone to detect ambiguity and then a gaze probe for decluttering. It is tested in a comparative experiment which involves 12 participants with 3240 runs. The results show that the proposed technique enhanced the selection accuracy and user experience but it is still with a potential to be improved in efficiency. This study contributes to providing a robust multimodal interface design supported by both eye tracking and mid-air gesture control

Multimodality with Eye tracking and Haptics: A New Horizon for Serious Games?

The goal of this review is to illustrate the emerging use of multimodal virtual reality that can benefit learning-based games. The review begins with an introduction to multimodal virtual reality in serious games and we provide a brief discussion of why cognitive processes involved in learning and training are enhanced under immersive virtual environments. We initially outline studies that have used eye tracking and haptic feedback independently in serious games, and then review some innovative applications that have already combined eye tracking and haptic devices in order to provide applicable multimodal frameworks for learning-based games. Finally, some general conclusions are identified and clarified in order to advance current understanding in multimodal serious game production as well as exploring possible areas for new applications

Exploitation of Novel Multiplayer Gesture-based Interaction and Virtual Puppetry for Digital Storytelling to Develop Children’s Narrative Skills

In recent years, digital storytelling has demonstrated powerful pedagogical functions by improving creativity, collaboration and intimacy among young children. Saturated with digital media technologies in their daily lives, the young generation demands natural interactive learning environments which offer multimodalities of feedback and meaningful immersive learning experiences. Virtual puppetry assisted storytelling system for young children, which utilises depth motion sensing technology and gesture control as the Human-Computer Interaction (HCI) method, has been proved to provide natural interactive learning experience for single player. In this paper, we designed and developed a novel system that allows multiple players to narrate, and most importantly, to interact with other characters and interactive virtual items in the virtual environment. We have conducted one user experiment with four young children for pedagogical evaluation and another user experiment with five postgraduate students for system evaluation. Our user study shows this novel digital storytelling system has great potential to stimulate learning abilities of young children through collaboration tasks

Semantic framework for interactive animation generation and its application in virtual shadow play performance.

Designing and creating complex and interactive animation is still a challenge in the field of virtual reality, which has to handle various aspects of functional requirements (e.g. graphics, physics, AI, multimodal inputs and outputs, and massive data assets management). In this paper, a semantic framework is proposed to model the construction of interactive animation and promote animation assets reuse in a systematic and standardized way. As its ontological implementation, two domain specific ontologies for the hand-gesture-based interaction and animation data repository have been developed in the context of Chinese traditional shadow play art. Finally, prototype of interactive Chinese shadow play performance system using deep motion sensor device is presented as the usage example

Exploitation of multiplayer interaction and development of virtual puppetry storytelling using gesture control and stereoscopic devices

With the rapid development of human-computer interaction technologies, the new media generation demands novel learning experiences with natural interaction and immersive experience. Considering that digital storytelling is a powerful pedagogical tool for young children, in this paper, we design an immersive storytelling environment that allows multiple players to use naturally interactive hand gestures to manipulate virtual puppetry for assisting narration. A set of multimodal interaction techniques is presented for a hybrid user interface that integrates existing 3D visualization and interaction devices including head-mounted displays and depth motion sensor. In this system, the young players could intuitively use hand gestures to manipulate virtual puppets to perform a story and interact with props in a virtual stereoscopic environment. We have conducted a user experiment with four young children for pedagogical evaluation, as well as system acceptability and interactivity evaluation by postgraduate students. The results show that our framework has great potential to stimulate learning abilities of young children through collaboration tasks. The stereoscopic head-mounted display outperformed the traditional monoscopic display in a comparison between the two

Patient satisfaction with nurses' care is positively related to the nurse–patient relationship in Chinese hospitals: A multicentre study

BackgroundThe nurse–patient relationship and nursing care satisfaction are important factors that represent whether patients experience the care they expect from nurses. However, research is lacking on the relationship between nursing staff and patients, and the correlation between nursing care satisfaction and relationship care in China. Therefore, this study aimed to explore the correlation between the nurse–patient relationship and patients' satisfaction with nursing care, to form a basis for corresponding intervention measures.MethodsA total of 29,108 patients from 107 hospitals in 30 provinces/municipalities in China completed a general information questionnaire, the Nursing Care Satisfaction Scale, and Relational Care Scale.ResultsThe average nurse–patient relational care scale score was 4.38 ± 0.57, and the average patients' satisfaction with nursing care scale score was 5.40 ± 0.86. Nursing care satisfaction score was significantly related to differences among patients in different age, gender, marital status, education level, occupation, residence, family per capita monthly income, type of medical insurance, medical department, and regional patient characteristics. The correlation analysis showed that the total nurse–patient relational care score and its three dimensions of caring, trust, and professional ethics correlated positively with nursing care satisfaction scores. The multiple linear regression analysis showed that patients' age, marital status, region, department, income, type of medical insurance and the caring, trust, and professional ethics dimensions of relational care predicted nursing care satisfaction.ConclusionEnhancing nurse–patient relational care improves nursing care satisfaction, reduces nurse–patient disputes, promotes early rehabilitation of patients, and ensures patient safety

Understanding the impact of multimodal interaction using gaze informed mid-air gesture control in 3D virtual objects manipulation.

Multimodal interactions provide users with more natural ways to manipulate virtual 3D objects than using traditional input methods. An emerging approach is gaze modulated pointing, which enables users to perform object selection and manipulation in a virtual space conveniently through the use of a combination of gaze and other interaction techniques (e.g., mid-air gestures). As gaze modulated pointing uses different sensors to track and detect user behaviours, its performance relies on the user's perception on the exact spatial mapping between the virtual space and the physical space. An underexplored issue is, when the spatial mapping differs with the user's perception, manipulation errors (e.g., out of boundary errors, proximity errors) may occur. Therefore, in gaze modulated pointing, as gaze can introduce misalignment of the spatial mapping, it may lead to user's misperception of the virtual environment and consequently manipulation errors. This paper provides a clear definition of the problem through a thorough investigation on its causes and specifies the conditions when it occurs, which is further validated in the experiment. It also proposes three methods (Scaling, Magnet and Dual-gaze) to address the problem and examines them using a comparative study which involves 20 participants with 1040 runs. The results show that all three methods improved the manipulation performance with regard to the defined problem where Magnet and Dual-gaze delivered better performance than Scaling. This finding could be used to inform a more robust multimodal interface design supported by both eye tracking and mid-air gesture control without losing efficiency and stability

Dynamic Alterations in Yak Rumen Bacteria Community and Metabolome Characteristics in Response to Feed Type

Current knowledge about the relationships between ruminal bacterial communities and metabolite profiles in the yak rumen is limited. This is due to differences in the nutritional and metabolic features between yak and other ordinary cattle combined with difficulties associated with farm-based research and a lack of technical guidance. A comprehensive analysis of the composition and alterations in ruminal metabolites is required to advance the development of modern yak husbandry. In the current study, we characterized the effect of feed type on the ruminal fluid microbiota and metabolites in yak using 16S rRNA gene sequencing and liquid chromatography-mass spectrometry (LC-MS). Bacteroidetes and Firmicutes were the predominant bacterial phyla in the yak rumen. At the genus level, the relative abundance of Bacteroidales BS11 gut group, Prevotellaceae UCG-003, Ruminococcaceae UCG-011, Bacteroidales RF16 group and Ruminococcaceae UCG-010 was significantly (P < 0.01) higher in the forage group compared to that in the concentrate group, while the concentrate group harbored higher proportions of Bacteroidales S24-7 group, Ruminococcaceae NK4A214, Succiniclasticum and Ruminococcus 2. Yak rumen metabolomics analysis combined with enrichment analysis revealed that feed type altered the concentrations of ruminal metabolites as well as the metabolic pattern, and significantly (P < 0.01) affected the concentrations of ruminal metabolites involved in protein digestion and absorption (e.g., L-arginine, ornithine, L-threonine, L-proline and β-alanine), purine metabolism (e.g., xanthine, hypoxanthine, deoxyadenosine and deoxyadenosine monophosphate) and fatty acid biosynthesis (e.g., stearic acid, myristic acid and arachidonic acid). Correlation analysis of the association of microorganisms with metabolite features provides us with a comprehensive understanding of the composition and function of microbial communities. Associations between utilization or production were widely identified between affected microbiota and certain metabolites, and these findings will contribute to the direction of future research in yak