Privacy-enhanced architecture for smart metering

The recent deployment of smart grids promises to bring numerous advantages in terms of energy consumption reduction in both homes and businesses. A more transparent and instantaneous measurement of electricity consumption through smart meters utilization leads to an enhancement in the ability of monitoring, controlling and predicting energy usage. Nevertheless, it also has associated drawbacks related to the privacy of customers, since such management might reveal their personal habits, which electrical appliances they are using at each moment, whether they are at home or not, etc. In this work, we present a privacy-enhanced architecture for smart metering aimed at tackling this threat by means of encrypting individual measurements while allowing the electricity supplier to access the aggregation of the corresponding decrypted values.     

Image mosaicking for polyhedral scene and in particular singly visible surfaces

Image mosaic construction is about stitching together a number of images about the same scene to construct a single image with a larger field of view. The majority of the previous work was rooted at the use of a single image-to-image mapping termed planar homography for representing the imaged scene. However, the mapping is applicable only to cases where the imaged scene is either a single planar surface, or very distant from the cameras, or imaged under a pure rotation of the camera, and that greatly limits the range of applications of the mosaicking methods. This paper presents a novel mosaicking solution for scenes that are polyhedral (thus consisting of multiple surfaces) and that are pictured possibly in closed range of the camera. The solution has two major advantages. First, it requires only a few correspondences over the entire scene, not correspondences over every surface patch in it to work. Second, it conquers a seemingly impossible task—warping image data of surfaces that are visible in only one of the input images, which we refer to as the singly visible surfaces, to another viewpoint to constitute the mosaic there. We also provide a detail analysis of what determines whether a singly visible surface could be mosaicked or not. Experimental results on real image data are presented to illustrate the performance of the method.     

On near optimal neural control of multiple-input nonlinear systems

It has been a common consensus that general techniques for stabilization of nonlinear systems are available only for some special classes of nonlinear systems. Control design for nonlinear systems with uncertain components is usually carried out on a per system basis, especially when physical control constraints, and certain control performance measures such as optimum time control are imposed. Elegant adaptive control techniques are difficult to apply to this type of problems. A new neural network based control design is proposed and presented in this paper to deal with a special class of uncertain nonlinear systems with multiple inputs. The desired system dynamics are analyzed and utilized in the process of the proposed intelligent control design. The theoretical results are provided to justify the design procedures. The simulation study is conducted on a second-order bilinear system with two inputs and uncertainties on its parameters. The simulation results indicate that the proposed design approach is effective.     

AMOLED displays with transfer‐printed integrated circuits

Abstract— Small integrated circuits of crystalline silicon (chiplets) transfer‐printed onto a flat‐panel‐display substrate provide greatly improved electrical performance and uniformity in active‐matrix organic light‐emitting‐diode (OLED) displays. The integrated circuits are formed in high‐performance crystalline silicon using conventional photolithographic processes and then transfer‐printed onto a substrate using a stamp that transfers hundreds or thousands of chiplets at once. The chiplets are connected to an external controller and to pixel elements using conventional photolithographic substrate processing methods. Active‐matrix OLED (AMOLED) displays using transfer‐printed chiplets have good yields, excellent uniformity, and electrical performance and are thermally robust.     

SimKnowledge—Analyzing impact of knowledge management measures on team organizations with multi agent-based simulation

Even though there is abundant literature on successful cases of organizations applying knowledge management (KM) measures, many KM initiatives have failed to achieve their knowledge and business goals. In order to foster decisions about the design of such initiatives, information is required on success factors and barriers when selecting KM measures. Multi agent-based simulation (MABS) is suggested as instrument to investigate potential effects of KM measures on dependent variables such as sharing of knowledge in organizations or business performance. For such a simulation, the concept of knowledge sharing, influencing factors and their impact on business and knowledge goals are modeled based on an extensive multi-disciplinary literature survey. An extensive domain model is operationalized in a simulation model which is then further simplified and implemented in a MABS tool used for a series of experiments contrasting results with/without KM measures, specifically skill and experience management. Skill management is found highly sensitive with respect to conditions of application and has no significant impact on knowledge or business goals. Experience management positively impacts knowledge and business goals. Personal documentation leads to specialist, project debriefings to generalist knowledge workers. Finally, the paper discusses the simulation’s limitations and further areas of application.     

Colonic fold detection from computed tomographic colonography images using diffusion-FCM and level sets

Colon cancer is the second major cause of cancer related deaths in industrial nations. Computed tomographic colonography (CTC) has emerged in the last decade as a new less invasive colon diagnostic alternative to the usually practiced optical colonoscopy. The overall goal is to increase the effectiveness of virtual endoscopic navigation of the existing computer-aided detection (CAD) system. The colonic/haustral folds serve as important landmarks for various associated tasks in the virtual endoscopic navigation like prone–supine registration, colonic polyp detection and tenia coli extraction. In this paper, we present two different techniques, first in isolation and then in synergism, for the detection of haustral folds. Our input is volumetric computed tomographic colonography (CTC) images. The first method, which uses a combination of heat diffusion and fuzzy c-means algorithm (FCM), has a tendency of over-segmentation. The second method, which employs level sets, suffers from under-segmentation. A synergistic combination, where the output of the first is used as an input for the second, is shown to improve the segmentation quality. Experimental results are presented on digital colon phantoms as well as real patient scans. The combined method has a total erroneous (over-segmentation plus under-segmentation) detection of (6.5 ± 2)% of the total number of folds per colon as compared to (12.5 ± 5)% for the diffusion-FCM-based method and (11.5 ± 3)% for the level set-based method. The p-values obtained from the associated ANOVA tests indicate that the performance improvements are statistically significant.