Contactless palmprint identification offers significantly improved hygiene and user convenience, making it highly attractive for a range of civilian applications, especially during the current pandemic. However, the accurate recognition of contactless palmprint images can be highly challenging, attributed to the significant variations in the intra-class similarity and limitations of conventional palmprint feature descriptors under involuntary or contactless imaging variations. State-of-the-art completely contactless palmprint matching algorithms in the literature cannot adequately address these challenges and are not sufficiently accurate and fast enough for such real-world applications. This paper proposes a novel approach that adaptively locates the local palmprint regions with high similarities between their corresponding feature representations or templates to address these challenges. We consider spatial localization of such highly similar feature representations from multiple local regions and consolidate them to generate a more reliable match score. This paper presents reproducible and comparative experimental results, using within-database, cross-database, and cross-sensor performance evaluation, on four publicly available contactless palmprint datasets, including a sizeable contactless palmprint database from 600 different subjects. The proposed method achieves outperforming results compared with three state-of-the-art deep learning-based methods and five widely used conventional methods. In addition, the proposed method is also significantly faster than all state-of-the-art baseline methods .

Billions of fingerprint images are acquired and matched to protect the national borders and in a range of egovernance applications. Fast and accurate minutiae detection from fingerprint images is the key to advance fingerprint matching algorithms for large-scale applications. However, currently available fingerprint minutiae extraction methods are not accurate and fast enough to support such large-scale applications. This paper proposes a new method that uses a lightweight pixelwise local dilated neural network to extract local features and a patch-wise global neural network to recover the global features. It consolidates the local and global fingerprint features to generate a full-size minutiae location map, and then accurately localizes the minutiae positions by using a recursive connected components algorithm. We design a new loss function to accurately detect minutia orientation and incorporate a dynamic end-to-end loss to provide effective supervision in learning discriminant features. It is due to the proposed design and loss function that can enable higher accuracy with significantly less computations. We present reproducible experimental results from five publicly available contact-based and contactless databases that indicate significant improvement in the minutiae detection accuracy, which also leads to enhanced fingerprint matching accuracy. Since the minutiae represent key points in the fingerprint images, the proposed end-to-end minutiae detection method also has a potential to be employed in many other key points detection tasks.

One of the major applications of wireless ad hoc networks is to extend the Internet coverage and support pervasive and efficient data dissemination and sharing. To reduce data access cost and delay, caching has been widely used as an important technique. The efficiency of data access in caching systems largely depends on the cost for maintaining cache consistency, which can be high in wireless ad hoc networks due to network dynamism. Therefore, to make better trade-off between cache consistency and the cost incurred, it would be highly desirable to provide users the flexibility in specifying consistency requirements for their applications. In this paper, we propose a general consistency model called Probabilistic Delta Consistency (PDC), which integrates the flexibility granted by existing consistency models, covering them as special cases. We also propose the Flexible Combination of Push and Pull (FCPP) algorithm which satisfies user-specified consistency requirements under the PDC model. The analytical model of FCPP is used to derive the balance of minimizing the consistency maintenance cost and ensuring the specified consistency requirement. Extensive simulations are conducted to evaluate whether FCPP can satisfy arbitrarily specified consistency requirements, and whether FCPP works cost-effectively in dynamic wireless ad hoc networks. The evaluation results show that FCPP can adaptively tune itself to satisfy various user-specified consistency requirements. Moreover, it can save the traffic cost by up to 50 percent and reduce the query delay by up to 40 percent, compared with the widely used Pull with TTR algorithm.

Caching is an important technique to support pervasive Internet access. Cache consistency measures the deviation between the cached data and the source data. In mobile computing environments, especially with ad hoc networks, users are in great need of the flexibility in tuning their consistency requirements, in order to make tradeoffs between the specified cache consistency and the cost incurred. Existing works have used delta consistency (DC) and probabilistic consistency (PC) which, to some extent, provide the users with such flexibility. In this paper, we propose a general consistency model called probabilistic delta consistency (PDC). PDC covers all existing consistency models including DC and PC, and integrates the flexibility granted by both DC and PC. Thus, PDC enables the users to flexibly specify their consistency requirements in two orthogonal dimensions, namely the deviation in time/value and the ratio of queries gaining the specified consistency. We also propose a consistency maintenance algorithm, called flexible combination of push and pull (FCPP), which can meet users' consistency requirements specified under the PDC model. An analytical model is derived to achieve the optimized combination of push and pull, so as to ensure the user-specified consistency requirements, while minimizing the consistency maintenance overhead. Extensive simulations are conducted to evaluate the performance of the FCPP algorithm. Evaluation results show that, compared with the widely used dynamic TTR algorithm, FCPP can save up to 68% of the traffic overhead and reduce the query delay by up to 84%

Context-aware mobile computing middleware is designed to automatically adapt its behavior to changing environment. To achieve this, an important issue to be addressed is how to effectively select services for adaptation according to the user's current context. Existing work does not adequately address this issue. In this paper, we propose a fuzzy-based service adaptation model (FSAM) that can be used in context-aware middleware. We formulate the service adaptation process by using fuzzy linguistic variables and membership degrees to define the context situations and the rules for adopting the policies of implementing a service. We propose three fitness functions to calculate the fitness degree for each policy based on the distance of fuzzy status between the policy and the current context situation. The decision for service adaptation is achieved by selecting the policy with the largest fitness degree. A context-aware application scenario called Campus Assistant is used to exemplify the proposed service adaptation process and demonstrate its effectiveness.

A transactional workflow is composed of traditional flat transactions, and its execution has relaxed transactional atomicity. Due to different termination characteristics of transactions, a transactional workflow may be not well-formed. Moreover, only one workflow is allowed to execute a non-compensatable transaction with the current scheduling protocol. We present a transactional workflow model and formally define the correctness criteria of transactional workflow structure (well-formedness) and execution (serializability). We then propose an efficient method for well-formedness validation through a set of computation rules. Finally a scheduling protocol based on two kinds of locking granularities is presented. The protocol is different from related research in the fine-grained locking on transaction instances and coarse-grained locking on transaction classes, multiple workflows are therefore allowed to execute non-compensatable transactions if they are not conflict in a predicated future execution.

Recent advances in wireless and mobile networks have led to the exponential growth of mobile applications. Unlike conventional computing, mobile computing has stringent constraints in network resources, such as bandwidth and connectivity. As such, data in mobile applications are often cached at clients to increase performance, data availability and reliability. Formal verification of cache coherence in data access is essential in ascertaining the validity of a cache coherence protocol. Although a number of studies have been made in this subject, few researchers focused on mobile data access. In this paper, we present an automatic approach towards formal validation of a cache validation protocol supporting mobile data access. This approach combines the flexibility of visual modeling techniques with the rigor of formal validation. As it is difficult to construct the formal model of protocol, we have developed a set of formalization and translation rules to automate the process of construction. The reliability of the protocol has been verified using model checking.

An Escher circuit description is a hierarchical structure composed of cells, wires, connectors between wires, and pins that connect wires to cells. Cells may correspond to primitive circuit elements, or they may be defined in terms of lower level subcells. Unlike other geometrical layout systems, a subcell may be an instance of the cell being defined. When such a recursive cell definition is initiated, the recursion is unwound in a manner reminiscent of the procedure call copy rule in Algol-like programming languages. Cell specifications may have parameters that are used to control the unwinding of recursive cells and to provide for cell families with varying numbers of pins and other internal components. It is shown how the Escher layout system might be used with several nontrivial examples, including a parallel sorting network and a FFT (fast Fourier transform) implementation. The unwinding algorithm is also briefly described.>

An Escher circuit description is a hierarchical structure composed of cells, wires, connectors between wires, and pins that connect wires to cells. Cells may correspond to primitive circuit elements, or they may be defined in terms of lower level subcells. Unlike other geometrical layout systems, a subcell may be instance of the cell being defined. When such a recursive cell definition is instantiated, the recursion is unwound in a manner reminiscent of the procedure call copy rule in Algol-like programming languages. Cell specifications may have parameters that are used to control the unwinding of recursive cells and to provide for cell families with varying numbers of pins and other internal components. We illustrate how the Escher layout system can be used with several nontrivial examples, including a parallel sorting network and a FFT implementation. We also briefly describe the unwinding algorithm.