This paper describes a method based on an energy minimizing deformable model applied to the 3D biomechanical modeling of a set of organs considered as regions of interest (ROI) for radiotherapy. The initial model consists of a quadratic surface that is deformed to the exact contour of the ROI by means of the physical properties of a mass-spring system. The exact contour of each ROI is first obtained using a geodesic active contour model. The ROI is then parameterized by the vibration modes resulting from the deformation process. Once each structure has been defined, the method provides a 3D global model including the whole set of ROIs. This model allows one to describe statistically the most significant variations among its structures. Statistical ROI variations among a set of patients or through time can be analyzed. Experimental results are presented using the pelvic zone to simulate anatomical variations among structures and its application in radiotherapy treatment planning.

In this paper, we propose a fast and simple system emulator, called a system performance emulator (SPE), to evaluate long read operations. The SPE estimates how much system-wide performance is enhanced by using a faster solid state disk (SSD). By suspending a CPU for a certain time during direct memory access (DMA) transfer and subtracting this suspended time from the total DMA time, the SPE estimates the improvement in system performance expected from an enhanced SSD prior to its manufacture. We also examine the relation between storage performance and system performance using the SPE.

Multiscale classification has potential advantages for monitoring industrial processes generally driven by events in different time and frequency domains. In this study, we adopt stationary wavelet transform for multiscale analysis and propose an applicable scale selection method to obtain the most discriminative scale features. Then using the multiscale features, we construct two classifiers: (1) a supported vector machine (SVM) classifier based on classification distance, and (2) a Bayes classifier based on probability estimation. For the SVM classifier, we use 4-fold cross-validation and grid-search to obtain the optimal parameters. For the Bayes classifier, we introduce dimension reduction techniques including kernel Fisher discriminant analysis (KFDA) and principal component analysis (PCA) to investigate their influence on classification accuracy. We tested the classifiers with two simulated benchmark processes: the continuous stirred tank reactor (CSTR) process and the Tennessee Eastman (TE) process. We also tested them on a real polypropylene production process. The performance comparison among the classifiers in different scales and scale combinations showed that when datasets present typical scale features, the multiscale classifier had higher classification accuracy than conventional single scale classifiers. We also found that dimension reduction can generally contribute to a better classification in our tests.

The modeling of switching loss in semiconductor power devices is important in practice for the prediction and evaluation of thermal safety and system reliability. Both simulation-based behavioral models and data processing-based empirical models are difficult and have limited applications. Although the artificial neural network (ANN) algorithm has often been used for modeling, it has never been used for modeling insulated gate bipolar transistor (IGBT) transient loss. In this paper, we attempt to use the ANN method for this purpose, using a customized switching loss test bench. We compare its performance with two conventional curve-fitting models and verify the results by experiment. Our model is generally superior in calculation speed, accuracy, and data requirement, and is also able to be extended to loss modeling for all kinds of semiconductor power devices.

A 19 mW highly integrated GPS receiver with a ΣΔ fractional-N synthesizer is presented in this paper. Fractional-N frequency synthesizer architecture was adopted in this work, to provide more degrees of freedom in the synthesizer design. A high linearity low noise amplifier (LNA) is integrated into the chip. The radio receiver chip was fabricated in a 0.18 μm complementary metal oxide semiconductor (CMOS) process and packaged in a 48-pin 2 mm×2 mm land grid array chip scale package. The chip consumes 19 mW (LNA1 excluded) and the LNA1 6.3 mW. Measured performances are: noise figure<2 dB, channel gain=108 dB (LNA1 included), image rejection>36 dB, and ?108 dBc/Hz @ 1 MHz phase noise offset from the carrier. The carrier noise ratio (C/N) can reach 41 dB at an input power of ?130 dBm. The chip operates over a temperature range of [?40, 120] °C and ±5% tolerance over the CMOS technology process.

In the presence of multiple non-regenerative relays, we derived optimal joint power allocation, relay selection, and subchannel pairing schemes in orthogonal frequency division multiplexing (OFDM) based wireless networks. The Lagrange dual method was employed to design the optimal algorithm. First, the optimization problem was formulated for the single-relay system and the optimal centralized algorithm was presented by resolving the dual problem. Next, the optimal algorithm for a multi-relay system was proposed in a similar way. Compared with the exhaustive search method, the computational complexity of the proposed optimal algorithms was reduced from non-polynomial to polynomial time. Finally, the centralized algorithm was extended to the distributed algorithm, which was more feasible for the practical system. Simulation results verify our analysis.

Peer-to-peer (P2P) swarm technologies have been shown to be very efficient for large scale content distribution systems, such as the well-known BitTorrent and eMule applications. However, these systems have been designed for generic file sharing with little consideration of media streaming support, and the user cannot start a movie playback before it is completely downloaded. The playing-as-downloading capability would be particularly useful for a downloading peer to evaluate if a movie is valuable to be downloaded, and it could also help the P2P content distribution system to locate and eliminate the polluted contents. In this paper we address this issue by introducing a new algorithm, wish driven chunk distribution (WDCD), which enables the P2P file sharing system to support the video-on-demand (VOD) function while keeping the P2P native downloading speed. A new parameter named next-play-frequency is added to the content chunk to strike a replication balance between downloading and streaming requests. We modify the eMule as the test bed by adding the WDCD algorithm and then verify the prototype implementation by experiments. The experimental results show that the proposed algorithm can keep the high downloading throughput performance of the eMule system with a good playing-as-downloading function.

Golay codes are the most practical code in coded ultrasound imaging systems. But the trade-off for perfect range sidelobe cancellation is the requirement for two firings, thus resulting in motion-dependent decoding errors. In view of this, we propose a new scheme using the simultaneous emission of code pairs. The code pair is allocated to different elements of an aperture and transmitted simultaneously. The process of separating the code pair from the echo received is based on the orthogonality of the code pair. At last the autocorrelation functions of the individual Golay codes are added together. The simultaneous emission of code pairs instead of two firings recovers the frame rate loss, and eliminates the motion-dependent decoding error. Our theoretical analysis and simulations show that the scheme can be used to eliminate the tissue motion effects.

This paper deals with the problem of project scheduling subject to multiple execution modes with non-renewable resources, and a model that handles some of monetary issues in real world applications. The objective is to schedule the activities to maximize the expected net present value (NPV) of the project, taking into account the activity costs, the activity durations, and the cash flows generated by successfully completing an activity. Owing to the combinatorial nature of this problem, the current study develops a hybrid of branch-and-bound procedure and memetic algorithm to enhance both mode assignment and activity scheduling. Modifications for the makespan minimization problem have been made through a set of benchmark problem instances. Algorithmic performance is rated on the maximization of the project NPV and computational results show that the two-phase hybrid metaheuristic performs competitively for all instances of different problem sizes.