Collaborative business has been increasingly developing with the environment of globalization and advanced information technologies. In a collaboration environment with multiple organizations, participants from different organizations always have different views about modeling the overall business process due to different knowledge and cultural backgrounds. Moreover, flexible support, privacy preservation and process reuse are important issues that should be considered in business process management across organizational boundaries. This paper presents a novel approach of modeling interorganizational business process for collaboration. Our approach allows for modeling loosely coupled interorganizational business process considering different views of organizations. In the proposed model, organizations have their own local process views of modeling business process instead of sharing pre-defined global processes. During process cooperation, local process of an organization can be invisible to other organizations. Further, we propose the coordination mechanisms for different local process views to detect incompatibilities among organizations. We illustrate our proposed approach by a case study of interorganizational software development collaboration.

This letter presents a new entropy measure for electroencephalograms (EEGs), which reflects the underlying dynamics of EEG over multiple time scales. The motivation behind this study is that neurological signals such as EEG possess distinct dynamics over different spectral modes. To deal with the nonlinear and nonstationary nature of EEG, the recently developed empirical mode decomposition (EMD) is incorporated, allowing an EEG to be decomposed into its inherent spectral components, referred to as intrinsic mode functions (IMFs). By calculating Shannon entropy of IMFs in a time-dependent manner and summing them over adaptive multiple scales, the result is an adaptive subscale entropy measure of EEG. Simulation and experimental results show that the proposed entropy properly reveals the dynamical changes over multiple scales.

Developers often face difficulties while using APIs. API usage patterns can aid them in using APIs efficiently, which are extracted from source code stored in software repositories. Previous approaches have mined repositories to extract API usage patterns by simply applying data mining techniques to the collection of method invocations of API objects. In these approaches, respective functional roles of invoked methods within API objects are ignored. The functional role represents what type of purpose each method actually achieves, and a method has a specific predefined order of invocation in accordance with its role. Therefore, the simple application of conventional mining techniques fails to produce API usage patterns that are helpful for code completion. This paper proposes an improved approach that extracts API usage patterns at a higher abstraction level rather than directly mining the actual method invocations. It embraces a multilevel sequential mining technique and uses categorization of method invocations based on their functional roles. We have implemented a mining tool and an extended Eclipse's code completion facility with extracted API usage patterns. Evaluation results of this tool show that our approach improves existing code completion.

Computational fluid dynamics (CFD) is an important tool for designing aircraft components. FaSTAR (Fast Aerodynamics Routines) is one of the most recent CFD packages and has various subroutines. However, its irregular and complicated data structure makes it difficult to execute FaSTAR on parallel machines due to memory access problem. The use of a reconfigurable platform based on field programmable gate arrays (FPGAs) is a promising approach to accelerating memory-bottlenecked applications like FaSTAR. However, even with hardware execution, a large number of pipeline stalls can occur due to read-after-write (RAW) data hazards. Moreover, it is difficult to predict when such stalls will occur because of the unstructured mesh used in FaSTAR. To eliminate this problem, we developed an out-of-order mechanism for permuting the data order so as to prevent RAW hazards. It uses an execution monitor and a wait buffer. The former identifies the state of the computation units, and the latter temporarily stores data to be processed in the computation units. This out-of-order mechanism can be applied to various types of computations with data dependency by changing the number of execution monitors and wait buffers in accordance with the equations used in the target computation. An out-of-order system can be reconfigured by automatic changing of the parameters. Application of the proposed mechanism to five subroutines in FaSTAR showed that its use reduces the number of stalls to less than 1% compared to without the mechanism. In-order execution was speeded up 2.6-fold and software execution was speeded up 2.9-fold using an Intel Core 2 Duo processor with a reasonable amount of overhead.

This paper describes a method for the efficient computation of the total autocorrelation for large multiple-output Boolean functions over a Shared Binary Decision Diagram (SBDD). The existing methods for computing the total autocorrelation over decision diagrams are restricted to single output functions and in the case of multiple-output functions require repeating the procedure k times where k is the number of outputs. The proposed method permits to perform the computation in a single traversal of SBDD. In that order, compared to standard BDD packages, we modified the way of traversing sub-diagrams in SBDD and introduced an additional memory function kept in the hash table for storing results of the computation of the autocorrelation between two subdiagrams in the SBDD. Due to that, the total amount of computations is reduced which makes the method feasible in practical applications. Experimental results over standard benchmarks confirm the efficiency of the method.

High Efficiency Video Coding (HEVC) is the latest video coding standard that is supported by JCT-VC. In this letter, an encoding algorithm for early termination of Coding Unit (CU) and Prediction Unit (PU) based on the texture direction is proposed for the HEVC intra prediction. Experimental results show that the proposed algorithm provides an average 40% total encoding time reduction with the negligible loss of rate-distortion.

The delay time component (τs) of an InGaAs MOSFET caused by dynamic source resistance is discussed. On the basis of the relationship between the current density (J) and the dynamic source resistance (rs), the value of rs is proportional to 1/J with some offset at low current densities, whereas the offset becomes smaller in a region of high current density. The value of τs depends on the current in a way similar to rs. Because the offset in the high-current-density region is proportional to the square root of the effective mass, an InGaAs MOSFET with a small mass has a shorter rs than a Si MOSFET.

A new scheme based on multi-order visual comparison is proposed for full-reference image quality assessment. Inspired by the observation that various image derivatives have great but different effects on visual perception, we perform respective comparison on different orders of image derivatives. To obtain an overall image quality score, we adaptively integrate the results of different comparisons via a perception-inspired strategy. Experimental results on public databases demonstrate that the proposed method is more competitive than some state-of-the-art methods, benchmarked against subjective assessment given by human beings.

With the development of global navigation satellite systems (GNSS), the interference among global navigation satellite systems, known as the radio frequency compatibility problem, has become a matter of great concern to system providers and user communities. The acceptable compatibility threshold should be determined in the radio frequency compatibility assessment process. However, there is no common standard for the acceptable threshold in the radio frequency compatibility assessment. This paper firstly introduces the comprehensive radio frequency compatibility methodology combining the spectral separation coefficient (SSC) and code tracking spectral sensitivity coefficient (CT_SSC). Then, a method for determination of the acceptable compatibility threshold is proposed. The proposed method considers the receiver processing phase including acquisition, code and carrier tracking and data demodulation. Simulations accounting for the interference effects are carried out at each time step and every place on earth. The simulations mainly consider the signals of GPS, Galileo and BeiDou Navigation Satellite System (BDS) in the L1 band. Results show that all of the sole systems are compatible with other GNSS systems with respect to a special receiver configuration used in the simulations.

Pseudo-random sequences with high linear complexity play important roles in many domains. We give linear complexity of generalized cyclotomic quaternary sequences with period pq over Z4 via the weights of its Fourier spectral sequence. The results show that such sequences have high linear complexity.

The Euler number of a binary image is an important topological property for pattern recognition, and can be calculated by counting certain bit-quads in the image. This paper proposes an efficient strategy for improving the bit-quad-based Euler number computing algorithm. By use of the information obtained when processing the previous bit quad, the number of times that pixels must be checked in processing a bit quad decreases from 4 to 2. Experiments demonstrate that an algorithm with our strategy significantly outperforms conventional Euler number computing algorithms.

In this paper, we focus on the multi-way relaying channel where K users wish to exchange information with each other within two phases. Precoding at each user and the relay is carefully constructed to ensure that the signals from the same user pair are grouped together and cross-pair interference can be cancelled. Reliable detection is challenging at the relay since the observation constellation is no longer one of the regular ones, due to the fact that a relay observation is the superposition of the messages from one of the $rac{1}{2}K(K-1)$ user pairs. When the trellis coded modulation is used at each node, a simple constellation mapping function and a reduced-states decoding scheme can be applied at the relay, which result in much lower complexity. Furthermore, a modified version of the decoding method is also developed which is called the re-encoding-avoidance scheme at the relay. Monte-Carlo simulation results are provided to demonstrate the performance of the proposed scheme.

A number of studies have been conducted on topic modeling for various types of data, including text and image data. We focus particularly on the burstiness of the local features in modeling topics within video data in this paper. Burstiness is a phenomenon that is often discussed for text data. The idea is that if a word is used once in a document, it is more likely to be used again within the document. It is also observed in video data; for example, an object or visual word in video data is more likely to appear repeatedly within the same video data. Based on the idea mentioned above, we propose a new topic model, the Correspondence Dirichlet Compound Multinomial LDA (Corr-DCMLDA), which takes into account the burstiness of the local features in video data. The unknown parameters and latent variables in the model are estimated by conducting a collapsed Gibbs sampling and the hyperparameters are estimated by focusing on the fixed-point iterations. We demonstrate through experimentation on the genre classification of social video data that our model works more effectively than several baselines.

As data volumes explode, data storage costs become a large fraction of total IT costs. We can reduce the costs substantially by using compression. However, it is generally known that database compression is not suitable for write-intensive workloads. In this paper, we provide a comprehensive solution to improve the performance of compressed databases for write-intensive OLTP workloads. We find that storing data too densely in compressed pages incurs many future page splits, which require exclusive locks. In order to avoid lock contention, we reduce page splits by sacrificing a couple of percent of space savings. We reserve enough space in each compressed page for future updates of records and prevent page merges that are prone to incur page splits in the near future. The experimental results using TPC-C benchmark and MySQL/InnoDB show that our method gives 1.5 times higher throughput with 33% space savings compared with the uncompressed counterpart and 1.8 times higher throughput with only 1% more space compared with the state-of-the-art compression method developed by Facebook.

MapReduce is commonly used as a parallel massive data processing model. When deploying it as a service over the open systems, the computational integrity of the participants is becoming an important issue due to the untrustworthy workers. Current duplication-based solutions can effectively solve non-collusive attacks, yet most of them require a centralized worker to re-compute additional sampled tasks to defend collusive attacks, which makes the worker a bottleneck. In this paper, we try to explore a trusted worker scheduling framework, named VAWS, to detect collusive attackers and assure the integrity of data processing without extra re-computation. Based on the historical results of verification, we construct an Integrity Attestation Graph (IAG) in VAWS to identify malicious mappers and remove them from the framework. To further improve the efficiency of identification, a verification-couple selection method with the IAG guidance is introduced to detect the potential accomplices of the confirmed malicious worker. We have proven the effectiveness of our proposed method on the improvement of system performance in theoretical analysis. Intensive experiments show the accuracy of VAWS is over 97% and the overhead of computation is closed to the ideal value of 2 with the increasing of the number of map tasks in our scheme.

With the distributed data mining technique having been widely used in a variety of fields, the privacy preserving issue of sensitive data has attracted more and more attention in recent years. Our major concern over privacy preserving in distributed data mining is the accuracy of the data mining results while privacy preserving is ensured. Corresponding to the horizontally partitioned data, this paper presents a new hybrid algorithm for privacy preserving distributed data mining. The main idea of the algorithm is to combine the method of random orthogonal matrix transformation with the proposed secure multi-party protocol of matrix product to achieve zero loss of accuracy in most data mining implementations.

An LSI Chip-Package-Board integrated power noise simulation model and its validity is discussed in this paper. A unified power delivery network (PDN) of LSI chip, package, and printed circuit board (PCB) is connected with on-chip power supply current models with capacitor charging expression. The proposed modeling flow is demonstrated for the 32-bit microprocessor in a 1.0V 90nm CMOS technology. The PDN of the system that includes a chip, bonding wires and a printed circuit board is modeled in an equivalent circuit. The on-chip power supply noise monitoring technique and the magnetic probe method is applied for validating simulation results. Simulations and measurements explore power supply noise generation with the dependency on operating frequencies in the wide range from 10MHz to 300MHz, under the operation mode of dynamic frequency scaling, and in the long time operation with various operation codes. It is confirmed that the proposed power supply noise simulation model is helpful for the noise estimation throughout the design phase of the LSI system.

We determine the linear complexity of binary sequences derived from the polynomial quotient modulo p defined by $F(u)equiv rac{f(u)-f_p(u)}{p} ~(mod~ p), qquad 0 le F(u) le p-1,~uge 0,$ where fp(u)≡f(u) (mod p), for general polynomials $f(x)in mathbb{Z}[x]$. The linear complexity equals to one of the following values {p2-p,p2-p+1,p2-1,p2} if 2 is a primitive root modulo p2, depending on p≡1 or 3 modulo 4 and the number of solutions of f'(u)≡0 (mod) p, where f'(x) is the derivative of f(x). Furthermore, we extend the constructions to d-ary sequences for prime d|(p-1) and d being a primitive root modulo p2.

This paper describes a new method for lossy audio signal compression via compressive sensing (CS). In this method, a structured shrinkage operator is employed to decompose the audio signal into three layers, with two sparse layers, tonal and transient, and additive noise, and then, both the tonal and transient layers are compressed using CS. Since the shrinkage operator is able to take into account the structure information of the coefficients in the transform domain, it is able to achieve a better sparse approximation of the audio signal than traditional methods do. In addition, we propose a sparsity allocation algorithm, which adjusts the sparsity between the two layers, thus improving the performance of CS. Experimental results demonstrated that the new method provided a better compression performance than conventional methods did.

An efficient beamforming algorithm for large-scale phased arrays with lossy digital phase shifters is presented. This problem, which arises in microwave power transmission from solar power satellites, is to maximize the array gain in a desired direction with the gain loss of the phase shifters taken into account. In this paper the problem is first formulated as a discrete optimization problem, which is then decomposed into element-wise subproblems by the real rotation theorem. Based on this approach, a polynomial-time algorithm to solve the problem numerically is constructed and its effectiveness is verified by numerical simulations.