Image enhancement in embedded devices for internet of things

This paper proposes a new color interpolation method which can be used in embedded devices for IoT system. In this work, we use regression approach for generating and designing filters to restore color image. The filters are designed with four sizes, 5x5 training filter, 7x7 training filter, 9x9 training filter, and 11x11 training filter. The obtained filters are tested in 25 LC dataset to assess the performance. Experimental results inform that the proposed filters provide outstanding performance when they are compared with conventional methods. As compared with the other methods, the proposed filters produce the best average interpolation performance both objectively and visually

Rectification of Random Walkers Induced by Energy Flow at Boundaries

We explore rectification phenomena in a system where two-dimensional random walkers interact with a funnel-shaped ratchet under two distinct classes of reflection rules. The two classes include the angle of reflection exceeding the angle of incidence ($\theta_{reflect} > \theta_{incident}$), or vice versa ($\theta_{reflect} < \theta_{incident}$). These generalized boundary reflection rules are indicative of non-equilibrium conditions due to the introduction of energy flows at the boundary. Our findings reveal that the nature of such particle-wall interactions dictates the system's behavior: the funnel either acts as a pump, directing flow, or as a collector, demonstrating a ratchet reversal. Importantly, we provide a geometric proof elucidating the underlying mechanism of rectification, thereby offering insights into why certain interactions lead to directed motion, while others do not.Comment: 5 pages, 6 figure

Emergent learning in physical systems as feedback-based aging in a glassy landscape

By training linear physical networks to learn linear transformations, we discern how their physical properties evolve due to weight update rules. Our findings highlight a striking similarity between the learning behaviors of such networks and the processes of aging and memory formation in disordered and glassy systems. We show that the learning dynamics resembles an aging process, where the system relaxes in response to repeated application of the feedback boundary forces in presence of an input force, thus encoding a memory of the input-output relationship. With this relaxation comes an increase in the correlation length, which is indicated by the two-point correlation function for the components of the network. We also observe that the square root of the mean-squared error as a function of epoch takes on a non-exponential form, which is a typical feature of glassy systems. This physical interpretation suggests that by encoding more detailed information into input and feedback boundary forces, the process of emergent learning can be rather ubiquitous and, thus, serve as a very early physical mechanism, from an evolutionary standpoint, for learning in biological systems.Comment: 11 pages, 7 figure

Reliability and capability based computation offloading strategy for vehicular ad hoc clouds

In the Internet of Vehicles (IoV), with the increasing demand for intelligent technologies such as driverless driving, more and more in-vehicle applications have been put into autonomous driving. For the computationally intensive task, the vehicle self-organizing network uses other high-performance nodes in the vehicle driving environment to hand over tasks to these nodes for execution. In this way, the computational load of the cloud alleviated. However, due to the unreliability of the communication link and the dynamic changes of the vehicle environment, lengthy task completion time may lead to the increase of task failure rate. Although the flooding algorithm can improve the success rate of task completion, the offloading expend will be large. Aiming at this problem, we design the partial flooding algorithm, which is a comprehensive evaluation method based on system reliability in the vehicle computing environment without infrastructure. Using V2V link to select some nodes with better performance for partial flooding offloading to reduce the task complete time, improve system reliability and cut down the impact of vehicle mobility on offloading. The results show that the proposed offloading strategy can not only improve the utilization of computing resources, but also promote the offloading performance of the system

Towards Transparent and Trustworthy Cloud

Despite its immense benefits in terms of flexibility, resource consumption, and simplified management, cloud computing raises several concerns due to lack of trust and transparency. Like all computing paradigms based on outsourcing, the use of cloud computing is largely a matter of trust. There is an increasing pressure by cloud customers for solutions that would increase their confidence that a cloud service/application is behaving in a secure and correct manner. Cloud assurance techniques, developed to assess the trustworthiness of cloud services, can play a major role in building trust. In this paper, we start from the assumption that an opaque cloud does not fit security, and present a reliable evidence collection process and infrastructure extending existing assurance techniques towards the definition of a trustworthy cloud. The proposed process and infrastructure are applied to a case study on cloud certification showing their utility

Defining and matching test-based certificates in Open SOA

Following the Service-Oriented Architecture (SOA) and the Cloud paradigms, an increasing number of organizations implement their business processes and applications via runtime composition of services made available on the cloud by single suppliers. This scenario however introduces new security risks and threats, as the service providers may not provide the level of assurance required by their customers. There is therefore the need of a new certification scheme for services that provides trusted evidence that a service has some security properties, and a matching infrastructure to compare service certificates with users' certification preferences. In this paper, we propose a first solution to the definition of a test-based certification process for SOA

Machine-Readable Privacy Certificates for Services

Privacy-aware processing of personal data on the web of services requires managing a number of issues arising both from the technical and the legal domain. Several approaches have been proposed to matching privacy requirements (on the clients side) and privacy guarantees (on the service provider side). Still, the assurance of effective data protection (when possible) relies on substantial human effort and exposes organizations to significant (non-)compliance risks. In this paper we put forward the idea that a privacy certification scheme producing and managing machine-readable artifacts in the form of privacy certificates can play an important role towards the solution of this problem. Digital privacy certificates represent the reasons why a privacy property holds for a service and describe the privacy measures supporting it. Also, privacy certificates can be used to automatically select services whose certificates match the client policies (privacy requirements). Our proposal relies on an evolution of the conceptual model developed in the Assert4Soa project and on a certificate format specifically tailored to represent privacy properties. To validate our approach, we present a worked-out instance showing how privacy property Retention-based unlinkability can be certified for a banking financial service.Comment: 20 pages, 6 figure

Facial identification problem : a tracking based approach

This paper presents a method for face identification using a query by example approach. Our technique is suitable for use within Ambient Security Environments and is robust across variations in pose, expression and illuminations conditions. To account for these variations, we use a face template matching algorithm based on a 3D head model created from a single frontal face image. Thanks to our tracking-based approach our algorithm is able to extract simultaneously all parameters related to the face expression and to the 3D posture. With these estimates, we are able to reconstruct a frontal, neutral and normalized image on which dissimilarity analysis for identification and anomalies detection is performed. Our tracking process combined with dissimilarity analysis was tested on Kanade-Cohn database for expression independent identification and several other experimental databases for robustness

Effects of avatar character performances in virtual reality dramas used for teachers&#8217; education

Virtual reality drama has the benefit of enhancing immersion, which was lacking in original e-Learning systems. Moreover, dangerous and expensive educational content can be replaced by stimulating users\u2019 interest. In this study, we investigate the effects of avatar performance in virtual reality drama. The hypothesis that the psychical distance between virtual characters and their viewers changes according to the size of video shots is tested with an autonomic nervous system function test. Eighty-four college students were randomly assigned to three groups. Virtual reality drama is used to train teachers concerning school bullying prevention, and deals with the dialogue between teachers and students. Group 1 was provided with full-shot video clips, Group 2 was shown various clips from full shots to extreme close-ups, and Group 3 was provided with close-up shots. We found that the virtual reality drama viewers\u2019 levels of stimulation changed in relation to the size of the shots. The R-R (between P wave and P wave) intervals of the electrocardiograms (ECGs, bio-signal feedback) became significantly narrower as the shot size became smaller

Image enlargement using multiple sensors

Image sensing is generally performed with multiple spectral sensors. For example, combination of three sensors (red, green, and blue) is used for color image reproduction, and electrooptical and infrared sensors are used for surveillance and satellite imaging, respectively. The resolution of each sensor can be intensified by taking the other sensors into account and applying correlations between different sensors. There are various successful applications of image enlargement using multiple sensors and even multimodal sensors. However, there still are several open issues in sensor processing which can be explained by signal processing-based image enlargement using redundancy among the sensors