Due to irregular deployment of small base stations (SBSs), the interference in cognitive heterogeneous networks (CHNs) becomes even more complex; in particular, the uncertainty of spectrum mobility aggravates the interference context. In this case, how to analyze system capacity to obtain a closed-form expression becomes a crucial problem. In this paper we employ stochastic methods to formulate the capacity of CHNs and achieve a closed-form expression. By using discrete-time Markov chains (DTMCs), the spectrum mobility with respect to the arrival and departure of macro base station (MBS) users is modeled. Then an integral method is proposed to derive the interference based on stochastic geometry (SG). Also, the effect of sensing accuracy on network capacity is discussed by concerning false-alarm and miss-detection events. Simulation results are illustrated to show that the proposed capacity analysis method for CHNs can approximate the conventional sum methods without rigorous requirement for channel station information (CSI). Therefore, it turns out to be a feasible and efficient way to capture the network capacity in CHNs.
The objective of this research is the rapid reconstruction of ancient buildings of historical importance using a single image. The key idea of our approach is to reduce the infinite solutions that might otherwise arise when recovering a 3D geometry from 2D photographs. The main outcome of our research shows that the proposed methodology can be used to reconstruct ancient monuments for use as proxies for digital effects in applications such as tourism, games, and entertainment, which do not require very accurate modeling. In this article, we consider the reconstruction of ancient Mughal architecture including the Taj Mahal. We propose a modeling pipeline that makes an easy reconstruction possible using a single photograph taken from a single view, without the need to create complex point clouds from multiple images or the use of laser scanners. First, an initial model is automatically reconstructed using locally fitted planar primitives along with their boundary polygons and the adjacency relation among parts of the polygons. This approach is faster and more accurate than creating a model from scratch because the initial reconstruction phase provides a set of structural information together with the adjacency relation, which makes it possible to estimate the approximate depth of the entire structural monument. Next, we use manual extrapolation and editing techniques with modeling software to assemble and adjust different 3D components of the model. Thus, this research opens up the opportunity for the present generation to experience remote sites of architectural and cultural importance through virtual worlds and real-time mobile applications. Variations of a recreated 3D monument to represent an amalgam of various cultures are targeted for future work.
Real-time encryption and decryption of digital images stored on end-user devices is a challenging task due to the inherent features of the images. Traditional software encryption applications generally suffered from the expense of user convenience, performance efficiency, and the level of security provided. To overcome these limitations, the concept of transparent encryption has been proposed. This type of encryption mechanism can be implemented most efficiently with kernel file systems. However, this approach has some disadvantages since developing a new file system and attaching it in the kernel level requires a deep understanding of the kernel internal data structure. A filesystem in userspace (FUSE) can be used to bridge the gap. Nevertheless, current implementations of cryptographic FUSE-based file systems suffered from several weaknesses that make them less than ideal for deployment. This paper describes the design and implementation of ImgFS, a fully transparent cryptographic file system that resides on user space. ImgFS can provide a sophisticated way to access, manage, and monitor all encryption and key management operations for image files stored on the local disk without any interaction from the user. The development of ImgFS has managed to solve weaknesses that have been identified on cryptographic FUSE-based implementations. Experiments were carried out to measure the performance of ImgFS over image files’ read and write against the cryptographic service, and the results indicated that while ImgFS has managed to provide higher level of security and transparency, its performance was competitive with other established cryptographic FUSE-based schemes of high performance.
We propose a self-adaptive process (SAP) that maintains the software architecture quality using the MAPE-K standard model. The proposed process can be plugged into various software development processes and service-oriented methodologies due to its explicitly defined inputs and outputs. To this aim, the proposed SAP is integrated with the service-oriented modeling and application (SOMA) methodology in a two-layered structure to create a novel methodology, named self-adaptive service-oriented architecture methodology (SASOAM), which provides a semi-automatic self-aware method by the composition of architectural tactics. Moreover, the maintenance activity of SOMA is improved using architectural and adaptive patterns, which results in controlling the software architecture quality. The improvement in the maintainability of SOMA is demonstrated by an analytic hierarchy process (AHP) based evaluation method. Furthermore, the proposed method is applied to a case study to represent the feasibility and practicality of SASOAM.
Controller area networks (CANs) have been designed for multiplexing communication between electronic control units (ECUs) in vehicles and many high-level industrial control applications. When a CAN bus is overloaded by a large number of ECUs connected to it, both the waiting time and the error probability of the data transmission are increased. Thus, it is desirable to reduce the CAN frame length, since the duration of data transmission is proportional to the frame length. In this paper, we present a CAN message compression method to reduce the CAN frame length. Experimental results indicate that CAN transmission data can be compressed by up to 81.06% with the proposed method. By using an embedded test board, we show that 64-bit engine management system (EMS) CAN data compression can be performed within 0.16 ms; consequently, the proposed algorithm can be successfully used in automobile applications.
We present a high-definition (HD) 3D laparoscopic system including a dual channel optical system, two cameras, a camera control unit (CCU), and an HD 3D monitor. This laparoscopic system is capable of outputting dual high-definition videos and providing vivid 3D images. A modified pinhole camera model is used for camera calibration and a new method of depth measurement to improve precision. The average error of depth measurement measured by experiment (about 1.13 mm) was small in proportion to the large range in distance of the system (10−150 mm). The new method is applicable to any calibrated binocular vision system.