This paper presents an algorithm for identifying desirable multiple targets in an intracellular regulation network. The algorithm is based on constrained state feedback and Monte-Carlo simulations. The computational complexity of the algorithm increases linearly with increasing the number of species in a gene regulation system. An estimate is derived for the confidence level of the predicted minimum required perturbation strength when targets are prescribed a priori. The algorithm has been used to analyze the cell cycle of Xenopus frog eggs. The results agree well with available results for single target perturbations, and multi-target interference is usually not equal to the summation of the single-target interferences.

This paper describes a semi-supervised regularized method for additive logistic regression. The graph regularization term of the combined functions is added to the original cost functional used in AdaBoost. This term constrains the learned function to be smooth on a graph. Then the gradient solution is computed with the advantage that the regularization parameter can be adaptively selected. Finally, the function step-size of each iteration can be computed using Newton-Raphson iteration. Experiments on benchmark data sets show that the algorithm gives better results than existing methods.

Dynamic airspace management plans and assigns airspace resources to airspace users on demand to increase airspace capacity. Although many studies of air traffic flow management (ATFM) have sought to optimally allocate air traffic to get the best use of given airspace resources, few studies have focused on how to build an efficient air traffic network or how to adjust the current network in real time. This paper presents an integer program model named the dynamic air route open-close problem (DROP). DROP has a cost-based objective function which takes into account constraints such as the shortest occupancy time of routes, which are not considered in ATFM models. The aim of DROP is to determine which routes will be opened to a certain user during a given time period. Simulation results show that DROP can facilitate utilization of air routes. DROP, a simplified version of an air traffic network constructing problem, is the first step towards realizing dynamic airspace management. The combination of ATFM and DROP can facilitate decisions toward more reasonable, efficient use of limited airspace resources.

The paper analyzes the problem of blind source separation (BSS) based on the nonlinear principal component analysis (NPCA) criterion. An adaptive strong tracking filter (STF) based algorithm was developed, which is immune to system model mismatches. Simulations demonstrate that the algorithm converges quickly and has satisfactory steady-state accuracy. The Kalman filtering algorithm and the recursive least-squares type algorithm are shown to be special cases of the STF algorithm. Since the forgetting factor is adaptively updated by adjustment of the Kalman gain, the STF scheme provides more powerful tracking capability than the Kalman filtering algorithm and recursive least-squares algorithm.

This paper describes a channel estimation and equalization algorithm using three-layer artificial neural networks (ANNs) with feedback for multiple input multiple output wireless communication systems. An ANN structure with feedback was designed to use different learning algorithms in the different ANN layers. This actually forms a Turbo iteration process between the different algorithms which effectively improves the estimation performance of the channel equalizer. Simulation results show that this channel equalization algorithm has better computational efficiency and faster convergence than higher order statistics based algorithms.

A multiuser detector was developed for fast fading code-division multiple-access systems by representing the channels as a system with the multiplicative noise (SMN) model and then using the known optimal filtering algorithm for the SMN for multiuser detection (MUD). This multiuser detector allows the channel response to be stochastic in one symbol duration, which can be regarded as an effective method of MUD for fast fading CDMA systems. Performance analyses show that the multiuser detector is theoretically valid for CDMA systems over fast fading channels. Simulations show that the multiuser detector performs better than the Kalman filter-based multiuser detector with a faster convergence rate and lower bit error rate.

The problem of approximate joint diagonalization of a set of matrices is instrumental in numerous statistical signal processing applications. This paper describes a relative gradient non-orthogonal approximate joint diagonalization (AJD) algorithm based on a non-least squares AJD criterion and a special AJD using a non-square diagonalizing matrix and an AJD method for ill-conditioned matrices. Simulation results demonstrate the better performance of the relative gradient AJD algorithm compared with the conventional least squares (LS) criteria based gradient-type AJD algorithms. The algorithm is attractive for practical applications since it is simple and efficient.

In orthogonal frequency-division multiplexing (OFDM) systems, the carrier frequency offset (CFO) destroys the orthogonality among subcarriers which degrades system performance. Various CFO estimation methods have been developed to compensate for the CFO at the receiver. This paper describes a novel minimum output variance method for OFDM systems with CFO in additive white Gaussian noise channels. This method utilizes the phase and the amplitude of the received signal and reduces the mean square error of the CFO by about 3 dB compared with the original minimum output variance method.

Orthogonal frequency-division multiplexing (OFDM) systems are sensitive to carrier frequency offset (CFO) which introduces intercarrier interference and significantly degrades system performance. This paper describes an iterative blind receiver consisting of a sequential Monte Carlo detector, a CFO estimator, and a compensator to reduce intercarrier interference. The framework is of low complexity due to the separation of tasks in a joint detection problem. In addition, the CFO estimator utilizes soft output of the sequential Monte Carlo detector, which reduces the information loss caused by hard decisions and can obtain the CFO estimate in only one OFDM symbol. Simulation results demonstrate the effectiveness of the algorithm.

Concurrent programs written in a machine level language are being used in many areas but verification of such programs brings new challenges to the programming language community. Most of the studies in the literature on verifying the safety properties of concurrent programs are for high-level languages, specifications, or calculi. Therefore, more studies are needed on concurrency verification for machine level language programs. This paper describes a framework of a Petri net based safety policy for the verification of concurrent assembly programs, to exploit the capability of Petri nets in concurrency modeling. The concurrency safety properties can be considered separately using the net structure and by mixing Hoare logic and computational tree logic. Therefore, more useful higher-level safety properties can be specified and verified.

Token protocol provides a new coherence framework for shared-memory multiprocessor systems. It avoids indirections of directory protocols for common cache-to-cache transfer misses, and achieves higher interconnect bandwidth and lower interconnect latency compared with snooping protocols. However, the broadcasting increases network traffic, limiting the scalability of token protocol. This paper describes an efficient technique to reduce the token protocol network traffic, called sharing relation cache. This cache provides destination set information for cache-to-cache miss requests by caching directory information for recent shared data. This paper introduces how to implement the technique in a token protocol. Simulations using SPLASH-2 benchmarks show that in a 16-core chip multiprocessor system, the cache reduced the network traffic by 15% on average.

Context-awareness enhances human-centric, intelligent behavior in a smart environment; however, context-awareness is not widely used due to the lack of effective infrastructure to support context-aware applications. This paper presents an agent-based middleware for providing context-aware services for smart spaces to afford effective support for context acquisition, representation, interpretation, and utilization to applications. The middleware uses a formal context model, which combines first order probabilistic logic (FOPL) and web ontology language (OWL) ontologies, to provide a common understanding of contextual information to facilitate context modeling and reasoning about imperfect and ambiguous contextual information and to enable context knowledge sharing and reuse. A context inference mechanism based on an extended Bayesian network approach is used to enable automated reactive and deductive reasoning. The middleware is used in a case study in a smart classroom, and performance evaluation result shows that the context reasoning algorithm is good for non-time-critical applications and that the complexity is highly sensitive to the size of the context dataset.

Video structure analysis is a basic requirement for most content-based video editing and processing systems. This paper presents a fast video structure analysis method based on image segmentation in each frame, with region matching between frames. The structure analysis decomposes the video into several moving objects, including information about their colors, positions, shapes, movements, and lifetimes. The method also supports user interactions to improve the results. The result shows that this method is fast and stable and can complete video analyzing interactively.

Parallel frequent pattern discovery algorithms exploit parallel and distributed computing resources to relieve the sequential bottlenecks of current frequent pattern mining (FPM) algorithms. Thus, parallel FPM algorithms achieve better scalability and performance, so they are attracting much attention in the data mining research community. This paper presents a comprehensive survey of the state-of-the-art parallel and distributed frequent pattern mining algorithms with more emphasis on pattern discovery from complex data (e.g., sequences and graphs) on various platforms. A review of typical parallel FPM algorithms uncovers the major challenges, methodologies, and research problems in the field of parallel frequent pattern discovery, such as work-load balancing, finding good data layouts, and data decomposition. This survey also indicates a dramatic shift of the research interest in the field from the simple parallel frequent itemset mining on traditional parallel and distributed platforms to parallel pattern mining of more complex data on emerging architectures, such as multi-core systems and the increasingly mature grid infrastructure.

One of the difficulties that goal-oriented requirements analyses encounters is that the efficiency of the goal refinement is based on the analysts’ subjective knowledge and experience. To improve the efficiency of the requirements elicitation process, engineers need approaches with more systemized analysis techniques. This paper integrates the goal-oriented requirements language i* with concepts from a structured problem analysis notation, problem frames (PF). The PF approach analyzes software design as a contextualized problem which has to respond to constraints imposed by the environment. The proposed approach is illustrated using the meeting scheduler exemplar. Results show that integration of the goal and the problem analysis enables simultaneous consideration of the designer's subjective intentions and the physical environmental constraints.

A 4 Mb embedded silicon-oxide-nitride-oxide-silicon (SONOS) memory was developed with a 0.18 μm CMOS logic compatible technology. A reverse programming array architecture was proposed to reduce the chip area, enhance the operating window, and increase the read speed. The charge distribution was analyzed to optimize the programming and erase conditions considering both the operating speed and the endurance performance. The final test chip has a good endurance of 10⁵ cycles and a data retention time of at least 10 years.

The paper describes the growth of a germanium (Ge) film on a thin relaxed Ge-rich SiGe buffer. The thin Ge-rich SiGe buffer layer was achieved through a combination of ultrahigh vacuum chemical vapor deposition (UHVCVD) SiGe epitaxial growth and SiGe oxidation. A lower Ge content strained SiGe layer was first grown on the Si (001) substrate and then the Ge mole fraction was increased by oxidation. After removal of the surface oxide, a higher Ge content SiGe layer was grown and oxidized again. The Ge mole fraction was increased to 0.8 in the 50 nm thick SiGe layer. Finally a 150 nm thick pure Ge film was grown on the SiGe buffer layer using the UHVCVD system. This technique produces a much thinner buffer than the conventional compositionally graded relaxed SiGe method with the same order of magnitude threading dislocation density.

Transmission lines (T-Lines) are widely used in millimeter wave applications on silicon-based complementary metal-oxide semiconductor (CMOS) technology. Accurate modeling of T-lines to capture the related electrical effects has, therefore, become increasingly important. This paper describes a method to model the capacitance and conductance of T-Lines on CMOS multilayer, lossy substrates based on conformal mapping, and region subdivision. Tests show that the line parameters (per unit length) obtained by the method are frequency dependent and very accurate. The method is also suitable for parallel multiconductor interconnect modeling for high frequency circuits.

An ultrashort 10-GHz pulse generation scheme was successfully demonstrated using a bulk material InGaAsP electroabsorption modulator to generate the seed pulse. A self-phase modulation-based reshaper was used after the adiabatic soliton compression in a comb-like dispersion profiled fiber. Experiments and simulations confirm that the reshaper effectively removes the pulse pedestal and improves the pulse extinction ratio. As a result, the 10-GHz pulse had no pedestal, a high extinction ratio, and a pulse width of only 1.4 ps.