Domains are basic structural and functional unit of proteins, and, thus, exploring associations between protein domains and human inherited diseases will greatly improve our understanding of the pathogenesis of human complex diseases and further benefit the medical prevention, diagnosis and treatment of these diseases. Based on the assumption that deleterious nonsynonymous single nucleotide polymorphisms (nsSNPs) underlying human complex diseases may actually change structures of protein domains, affect functions of corresponding proteins, and finally result in these diseases, we compile a dataset that contains 1174 associations between 433 protein domains and 848 human disease phenotypes. With this dataset, we compare two approaches (guilt-by-association and correlation coefficient) that use a domain-domain interaction network and a phenotype similarity network to prioritize associations between candidate domains and human disease phenotypes. We implement these methods with three distance measures (direct neighbor, shortest path with Gaussian kernel, and diffusion kernel), demonstrate the effectiveness of these methods using three large-scale leave-one-out cross-validation experiments (random control, simulated linkage interval, and whole-genome scan), and evaluate the performance of these methods in terms of three criteria (mean rank ratio, precision, and AUC score). Results show that both methods can effectively prioritize domains that are associated with human diseases at the top of the candidate list, while the correlation coefficient approach can achieve slightly higher performance in most cases. Finally, taking the advantage that the correlation coefficient method does not require known disease-domain associations, we calculate a genome-wide landscape of associations between 4036 protein domains and 5080 human disease phenotypes using this method and offer a freely accessible web interface for this landscape.

A high contrast to noise ratio (CNR) is always desirable for contrast-enhanced computed tomography angiography (CTA). To ensure a high CNR of the vascular images in CTA and potentially reduce the radiation exposure and contrast usage, an adaptive bolus chasing method is proposed and evaluated compared to the existing constant-speed method. The proposed method is based on a local time and space parameter varying model of the contrast bolus. Optimal scan time for the next segment of the vasculature is estimated and predicted in real time and guides the computed tomography (CT) scanner table movement that guarantees that each segment of the vasculature is scanned with the maximum possible enhancement. Simulations and experimental results show that the proposed bolus chasing method outperforms the conventional constant-speed method substantially.

This study attempted to accurately segment the mammographic masses and distinguish malignant from benign tumors. An adaptive region growing algorithm with hybrid assessment function combined with maximum likelihood analysis and maximum gradient analysis was developed in this paper. In order to accommodate different situations of masses, the likelihood and the edge gradients of segmented masses were weighted adaptively by the use of information entropy. 106 benign and 110 malignant tumors were included in this study. We found that the proposed algorithm obtained segmentation contour more accurately and delineated the tumor body as well as tumor peripheral regions covering typical mass boundaries and some spiculation patterns. Then the segmented results were evaluated by the classification accuracy. 42 features including age, intensity, shape and texture were extracted from each segmented mass and support vector machine (SVM) was used as a classifier. The classification accuracy was evaluated using the area (A_z) under the receiver operating characteristic (ROC) curve. It was found that the maximum likelihood analysis achieved an A_z value of 0.835, the maximum gradient analysis got an A_z value of 0.932 and the hybrid assessment function performed the best classification result where the value of A_z was 0.948. In addition, compared with traditional region growing algorithm, our proposed algorithm is more adaptive and provides a better performance for future works.

Video event detection is an important research area nowadays. Modeling the video event is a key problem in video event detection. In this paper, we combine dynamic description logic with linear time temporal logic to build a logic system for video event detection. The proposed logic system is named as LTD_ALCO which can represent and inference the static, dynamic and temporal knowledge in one uniform logic system. Based on the LTD_ALCO, a framework for video event detection is proposed. The video event detection framework can automatically obtain the logic description of video content with the help of ontology-based computer vision tech-niques and detect the specified video event based on satisfiability checking on LTD_ALCO formulas.

A hardware platform using broadband antenna, oscilloscope, and spectrum analyzer is designed to receive radio frequency (RF) signals from electromagnetic radiation leakage of computers in the office environment. The process of receiving and the processing techniques have also been given. Then, the software radio-based computing models and software algorithms are proposed to demodulate and decode the RF signals. An experimental result shows that the text information can be recovered from electromagnetic (EM) leakage wave of computer by this interception system. This architecture not only reduces the cost of the system’s hardware but also makes interception more flexible. The innovation points of this paper are recovering the video information in EM leakage wave of computers in an ordinary office environment based on public equipments and proposing the process of receiving processing techniques that only use the software radio-based computing models and software algorithms.

In this paper, the ideas of universal logic is introduced into fuzzy systems. After giving the definitions of the softened fuzzy reasoning models based on Schweizer-Sklar t-norms and Schweizer-Sklar implications, i.e., α-models and β-models, we give the sufficient and necessary conditions for these models to be continuous, and discuss the continuity of some commonly used models. We also prove that when an α-model or a β-model is used as a fuzzy controller, it has universal property with respect to function approximation. The results we obtained show that α-models and β-models are more flexible than the existing models in applications.

Multi-robot mission planning is composed of assignment allocation and mobile-robot route planning in this paper. Multi-robot exploration missions adopts fuzzy c-mean (FCM) algorithm to allocate, and then, heterogeneous interactive cultural hybrid algorithm (HICHA) is devised for route planning in order to optimize mobile-robot execution path. Meanwhile, we design multi-robot mission replanning mechanism based on the rules system of greedy algorithm for dynamic stochastic increment missions. Finally, extensive simulation experiments were shown that FCM for assignment allocation and HICHA for route planning were efficacious for mobile-robot exploration mission planning. Furthermore, the improved greedy algorithm based on experience rules met dynamic stochastic increment missions replanning requirement for load balance.

A new framework has been developed to express variant and invariant properties of functions operating on a binary vector space. This framework allows for manipulation of dynamic logic using basic operations and permutations. Novel representations of binary functional spaces are presented. Current ideas of binary functional spaces are extended and additional conditions are added to describe new function representation schemes: F code and C code.
Sizes of the proposed functional space representation schemes were determined. It was found that the complete representation for any set of functions operating on a binary sequence of numbers is larger than previously thought. The complete representation can only be described using a structure having a space of size for any given space of functions acting on a binary sequence of length n. The framework, along with the proposed coding schemes provides a foundational theory of variant and invariant logic in software and electric-electronic technology and engineering, and has uses in the analysis of the stability of rule-based, dynamic binary systems such as cellular automata.

A novel classification approach called modified center-based feature line (MCFL) is proposed to reduce the computational cost of the nearest feature line (NFL) and maintain the advantages of NFL. Unlike NFL, MCFL defines a different type of feature line and utilizes both the query point’s local information and corresponding class-global information in training set. In experiments provided, the comparisons with the nearest neighbor (NN), NFL, and other NFL-refined approaches show that the computation time of MCFL can be shortened dramatically with less accuracy decreases. MCFL proposed is probably a better choice for the classification application tasks of large-scale dataset.

A novel approach for the synthesis of shaped beam patterns in time-modulated antenna arrays (TMAAs) with static uniform amplitude and phase excitations is proposed in this paper. Based on the sideband radiation in TMAAs, shaped beam patterns can be realized by only controlling the switch-on time sequences of the TMAAs. Differential evolution (DE) algorithm is adopted to optimize the time modulation parameters to obtain the desired flat-top and cosecant-squared beams and to suppress the sidelobe levels (SLLs). Simulation results of a time-modulated linear array (TMLA) and a time-modulated semicircular array (TMSA) demonstrate the effectiveness of the proposed approach for the synthesis of shaped beam patterns from TMAAs.

Genetic algorithm (GA) is utilized to design microstrip patch antenna shapes for broad bandwidth. A new project based on GA and high frequency simulation software (HFSS) is proposed to perform optimization. Reasonable agreement between simulated results and measured results of the GA-optimized design is obtained. The optimized patch design exhibits a three-fold enhancement in bandwidth when contrasted with a standard square microstrip antenna, showing the validity of this project.

With the increasing scale of information technology (IT) service system, traditional threshold-based static service level management (SLM) solution appears to be inadequate to meet current increasingly management requirement of SLM. Due to the stochastic service request rate, the random inherent failure and load surge of IT devices during service operating stage of large scaled IT system, service level objective (SLO) maintenance issue has become a realistic and important issue in dynamic SLM. This paper proposes a closed-loop feedback control mechanism to adaptively maintain SLO that service provider (SP) guaranteed at service operation stage. The mechanism can automatically tune the capacity of IT infrastructure according to service performance dispersion and reduce SLO violations. Considering that the tuning operations also affect service performance, fuzzy control is applied to alleviate the negative effect caused by tuning operations. In the dynamic SLM system that is applied with this mechanism compared with the traditional threshold-based solution, it is proved that the amount of SLO violations obviously decreases, the reliability of the service system increases relatively, and the resource utilization of IT infrastructure is optimized.

A novel adaptive cooperative medium access control (MAC) protocol, which is completely backward compatible with the legacy IEEE 802.11 distributed coordination function (DCF), is proposed in this paper. To adapt to dynamic channel variation and network topology, the sender adaptively selects transmission scheme based on the instantaneous channel measurements. Analytical and simulation results show that the proposed protocol outperforms the existing one in terms of throughput, delay, energy and mobility.

A sort of audio watermarking algorithm in discrete cosine transform (DCT) domain can embed secret information through modification of the distinction between positive and negative direct current (DC) coefficients. Such an algorithm achieves a good balance between robustness and imperceptibility. This paper points out that steganographic methods change statistical characteristics of DC coefficients. It also states that the difference between positive and negative DC coefficients can detect whether an audio has hidden information or not. Experiment results justify that the algorithm accuracy is 79%.

During the past few decades, there have been a number of new delay-dependent stability criteria based on linear matrix inequalities published in the literature. These criteria, to some extent, can reduce the conservativeness. In fact, some criteria are equivalence. In this paper, we aim to theoretically establish equivalence of two stability criteria. One was obtained by Sun et al. [Sun et al. In: Proceedings of IEEE Power & Energy Society General Meeting. 2009, 1–7] and the other was given by Xu et al. [Xu et al. IEEE Transactions on Automatic Control, 2005, 50(3): 384–387]. Also, we theoretically establish equivalence of the robust stability criterion presented by Jia et al. [Jia et al. Automation of Electric Power Systems, 2010, 34(3): 6–11] and the one given by Xu et al. (2005).

A novel measurement method of temperature model for bioreactor has been proposed. Temperature is the key parameter in monitoring the bioreactor operation. However, the system input signal of bioreactor is delayed, and model parameters are uncertain, so the output of temperature is non-steady-state. Many dynamic measurements are not steady so that it cannot be described by variables constant in time. In this paper, we adopt the monopulse signal as input so that the output of the bioreactor system is steady. This method has a powerful ability to steady the output of the bioreactor. In view of the measurement results, it can be seen that the model dynamic measurement approaches the real process. The analytical expression of the monopulse response for the temperature model of the bioreactor is obtained. The novel measurement approach is simple and can be easily adopted by industry.

In this paper, a fast algorithm is presented to compute the electromagnetic fields of a thin wire current source inside lossy ground. The modified image method is used to evaluate the Sommerfeld integrals, and the fast multipole method (FMM) is utilized for solving the governing electric field integral equation (EFIE). The validation of the proposed algorithm is performed by comparing the results with that of using method of moment (MoM). The numerical example shows the flexibility, efficiency and accuracy of this algorithm.

Triggered vacuum switches (TVSs) have fast growing applications in the field of power system and pulse power. The relation between triggering parameters of triggering system, such as triggering voltage and triggering power, between the triggering time delay and its scatter of TVS had been obtained through series of experiments. The result can be adopted as the steering for high-power controller design and application of TVS. A steepened high-voltage triggering pulse is introduced in the main high-voltage generating circuit. As a result, the triggering time delay and its scatter can be decreased remarkably. Synchronous switch technology is imported to control the triggering phase at the crest of applied voltage on TVS. The Triggering characteristic of TVS under alternating current (AC) and direct current (DC) load has been investigated emphatically. Given the identical triggering parameter of triggering system, DC condition is prior to AC on the triggering probability and stability markedly. Such conclusion can be drawn, for AC condition, TVS would require much for the triggering system.