Virtual interaction algorithm of cultural heritage based on multi feature fusion

During the traditional cultural heritage virtual interaction algorithm in the interaction action recognition, the database is too single, resulting in low recognition accuracy, recognition time-consumer and other issues. Therefore, this paper introduces the multi feature fusion method to optimize the cultural heritage virtual interaction algorithm. Kinect bone tracking technology is applied to identify the movement of the tracking object, 20 joints of the human body are tracked, and interactive action recognition is realized according to the fingertip candidate points. In order to carry out the judgment virtual interactive operation of subsequent recognition actions, a multi feature fusion database is established. The mean shift is used to derive the moving mean of the target’s action position and to track the interactive object. The Euclidean distance formula is used to train samples of multi feature fusion database data to realize the judgment of recognition action and virtual interaction. In order to verify the feasibility of the research algorithm, the virtual interactive script of ink painting in a cultural heritage museum is used to simulate the research algorithm, and a comparative experiment is designed. The experimental results show that the proposed algorithm is superior to the traditional virtual interactive algorithm in recognition accuracy and efficiency, which proves the feasibility of this method.

Stackelberg game based co-firing biomass with coal under carbon cap-and-trade regulation

Coal-fired power industry is under enormous pressure to accomplish carbon emission reduction targets. This paper proposes a bi-level multi-objective model for co-firing biomass with coal under carbon cap-and-trade regulation which considers a leader-follower Stackelberg game between the authority and the coal-fired power plants. The upper level regards social welfare maximization and allocation satisfaction maximization as its multiple objectives, while the lower level attempts to maximize the profits of each coal-fired power plant. The inherent uncertainty prompts the motivation for employing fuzzy set theory to characterize the uncertain parameters and determine their exact values. A case study from Shandong Province, China is provided to demonstrate the practicality and efficiency of the optimization model. [Formula: see text]-constraint method and interactive algorithm are used to solve the model, and furthermore the solutions associated with different free carbon emission quota levels and minimal allocation satisfactions have been generated to examine the influences. Based on the analysis and discussion, the methodology can meet the carbon emission reduction goals and transit to a lower-carbon power generation. It also assists the decision makers to develop desired quota allocation strategy in accordance with their attitudes and actual conditions.

Image Localized Style Transfer to Design Clothes Based on CNN and Interactive Segmentation

In recent years, image style transfer has been greatly improved by using deep learning technology. However, when directly applied to clothing style transfer, the current methods cannot allow the users to self-control the local transfer position of an image, such as separating specific T-shirt or trousers from a figure, and cannot achieve the perfect preservation of clothing shape. Therefore, this paper proposes an interactive image localized style transfer method especially for clothes. We introduce additional image called outline image, which is extracted from content image by interactive algorithm. The interaction consists simply of dragging a rectangle around the desired clothing. Then, we introduce an outline loss function based on distance transform of the outline image, which can achieve the perfect preservation of clothing shape. In order to smooth and denoise the boundary region, total variation regularization is employed. The proposed method constrains that the new style is generated only in the desired clothing part rather than the whole image including background. Therefore, in our new generated images, the original clothing shape can be reserved perfectly. Experiment results show impressive generated clothing images and demonstrate that this is a good approach to design clothes.

Cost-effectiveness analysis of a telemonitoring program on patients with heart failure in Normandy: an 8-year retrospective analysis (2009–2017)

Background SCAD is a 3-month telemonitoring program for HF patients, associated with therapeutic education, proposed after an acute HF episode. SCAD is based on an interactive algorithm allowing to generate educative messages and alarms based on patients' responses registered on a digital tablet. It is funded by the French Health Insurance through a pilot program: ETAPES (470€/patient). Purpose To describe the profile of patients using SCAD & assess the medico-economic impact of the SCAD system. Methods Multicenter retrospective cohort study using SCAD data matched with French Health Insurance data. All patients telemonitored by SCAD in 7 centers have been included, since 01/01/2010 to 12/31/2016. Only direct costs were considered, estimated from a societal perspective limited to reimbursements. Analyses were performed to assess the difference in healthcare consumptions and costs between the year before and the year after inclusion in the SCAD program. Patients who died in the 12 months after SCAD initiation were excluded. Results 627 patients benefited from SCAD program between 01/01/2010 and 12/31/2016 and were retrieved in French Health Insurance data through probabilistic matching. Out of the 627 patients, 99 died in the 12 months after SCAD initiation. Analyses were performed on 528 patients.72.2% were male, mean age was 66.0 years old and mean BMI 28.2. HFrEF represented 51.9% of patients, HFmrEF 25.9% and HFpEF 22.2%. 58.0% were in NYHA class 2 at baseline, 29.2% in class 3, 8.5% in class 1 and 4.3% in class 4. Mean Charlson Comorbidity Index score was 2.6 at baseline. Patients reported their level of fatigue (10 representing significant fatigue) and morale (10 = good morale) at baseline: mean fatigue=4.0/10 & mean morale=7.4/10. Medico economic results are presented in table 1 and show an important & significant decrease of hospitalizations costs and some transfer of cost toward ambulatory care. Conclusion On the year following remote monitoring, total health expenditure has been reduced by 18% on average (mean=3 210€/patient) and 42% in median (5 500€/patient) vs 12 months before. Funding Acknowledgement Type of funding source: Private company. Main funding source(s): This analysis has been funded through an institutional grant from Amgen