Detecting approximate clones in process model repositories with Apromore

Approximate clone detection is the process of identifying similar process fragments in business process model collections. The tool presented in this paper can efficiently cluster approximate clones in large process model repositories. Once a repository is clustered, users can filter and browse the clusters using different filtering parameters. Our tool can also visualize clusters in the 2D space, allowing a better understanding of clusters and their member fragments. This demonstration will be useful for researchers and practitioners working on large process model repositories, where process standardization is a critical task for increasing the consistency and reducing the complexity of the repository.

An investigation into factors affecting electron density calibration for a megavoltage cone-beam CT system

There is a growing interest in the use of megavoltage cone-beam computed tomography (MV CBCT) data for radiotherapy treatment planning. To calculate accurate dose distributions, knowledge of the electron density (ED) of the tissues being irradiated is required. In the case of MV CBCT, it is necessary to determine a calibration-relating CT number to ED, utilizing the photon beam produced for MV CBCT. A number of different parameters can affect this calibration. This study was undertaken on the Siemens MV CBCT system, MVision, to evaluate the effect of the following parameters on the reconstructed CT pixel value to ED calibration: the number of monitor units (MUs) used (5, 8, 15 and 60 MUs), the image reconstruction filter (head and neck, and pelvis), reconstruction matrix size (256 by 256 and 512 by 512), and the addition of extra solid water surrounding the ED phantom. A Gammex electron density CT phantom containing EDs from 0.292 to 1.707 was imaged under each of these conditions. The linear relationship between MV CBCT pixel value and ED was demonstrated for all MU settings and over the range of EDs. Changes in MU number did not dramatically alter the MV CBCT ED calibration. The use of different reconstruction filters was found to affect the MV CBCT ED calibration, as was the addition of solid water surrounding the phantom. Dose distributions from treatment plans calculated with simulated image data from a 15 MU head and neck reconstruction filter MV CBCT image and a MV CBCT ED calibration curve from the image data parameters and a 15 MU pelvis reconstruction filter showed small and clinically insignificant differences. Thus, the use of a single MV CBCT ED calibration curve is unlikely to result in any clinical differences. However, to ensure minimal uncertainties in dose reporting, MV CBCT ED calibration measurements could be carried out using parameter-specific calibration measurements.

A general model for MAC generation using direct injection

This paper presents a model for generating a MAC tag by injecting the input message directly into the internal state of a nonlinear filter generator. This model generalises a similar model for unkeyed hash functions proposed by Nakano et al. We develop a matrix representation for the accumulation phase of our model and use it to analyse the security of the model against man-in-the-middle forgery attacks based on collisions in the final register contents. The results of this analysis show that some conclusions of Nakano et al regarding the security of their model are incorrect. We also use our results to comment on several recent MAC proposals which can be considered as instances of our model and specify choices of options within the model which should prevent the type of forgery discussed here. In particular, suitable initialisation of the register and active use of a secure nonlinear filter will prevent an attacker from finding a collision in the final register contents which could result in a forged MAC.

Prevalence of papillary changes and folliculosis of the palpebral conjunctiva in asymptomatic Chinese children

Purpose To determine the prevalence of papillary changes of the upper palpebral conjunctiva and folliculosis of the lower palpebral conjunctiva in Chinese children with no history of contact lens wear. Method Ninety-nine subjects (aged 6–15 years old) who were interested in a myopia control study were screened for papillary changes and folliculosis of the palpebral conjunctiva. Photodocumentation was performed under white and blue light (after the application of fluorescein) with a yellow filter and the photographs were graded by a group of practitioners according to a pre-set grading scale. Analysis was performed with the subjects divided into groups according to gender and age. Results More than 48% of the subjects had clinically significant (≥Grade 3) papillary changes in the upper palpebral conjunctiva. The prevalence of significant folliculosis in the lower lid was about 33%. The prevalence of significant papillary changes and folliculosis were similar between genders. No differences were observed between younger (age ≤ 10 years old) and older (age > 10 years old) in papillary changes but younger subjects showed a higher prevalence of folliculosis. Conclusions The prevalences of clinically significant papillary changes and folliculosis of unknown aetiology are high in Chinese children.

Adaptive stepsize based on control theory for stochastic differential equations

The numerical solution of stochastic differential equations (SDEs) has been focused recently on the development of numerical methods with good stability and order properties. These numerical implementations have been made with fixed stepsize, but there are many situations when a fixed stepsize is not appropriate. In the numerical solution of ordinary differential equations, much work has been carried out on developing robust implementation techniques using variable stepsize. It has been necessary, in the deterministic case, to consider the "best" choice for an initial stepsize, as well as developing effective strategies for stepsize control-the same, of course, must be carried out in the stochastic case. In this paper, proportional integral (PI) control is applied to a variable stepsize implementation of an embedded pair of stochastic Runge-Kutta methods used to obtain numerical solutions of nonstiff SDEs. For stiff SDEs, the embedded pair of the balanced Milstein and balanced implicit method is implemented in variable stepsize mode using a predictive controller for the stepsize change. The extension of these stepsize controllers from a digital filter theory point of view via PI with derivative (PID) control will also be implemented. The implementations show the improvement in efficiency that can be attained when using these control theory approaches compared with the regular stepsize change strategy.

Image Region Salience for Improving Appearance-Based Place Recognition using a Supervised Classifier System

Many state of the art vision-based Simultaneous Localisation And Mapping (SLAM) and place recognition systems compute the salience of visual features in their environment. As computing salience can be problematic in radically changing environments new low resolution feature-less systems have been introduced, such as SeqSLAM, all of which consider the whole image. In this paper, we implement a supervised classifier system (UCS) to learn the salience of image regions for place recognition by feature-less systems. SeqSLAM only slightly benefits from the results of training, on the challenging real world Eynsham dataset, as it already appears to filter less useful regions of a panoramic image. However, when recognition is limited to specific image regions performance improves by more than an order of magnitude by utilising the learnt image region saliency. We then investigate whether the region salience generated from the Eynsham dataset generalizes to another car-based dataset using a perspective camera. The results suggest the general applicability of an image region salience mask for optimizing route-based navigation applications.

Fourier Lucas-Kanade Algorithm

In this paper we propose a framework for both gradient descent image and object alignment in the Fourier domain. Our method centers upon the classical Lucas & Kanade (LK) algorithm where we represent the source and template/model in the complex 2D Fourier domain rather than in the spatial 2D domain. We refer to our approach as the Fourier LK (FLK) algorithm. The FLK formulation is advantageous when one pre-processes the source image and template/model with a bank of filters (e.g. oriented edges, Gabor, etc.) as: (i) it can handle substantial illumination variations, (ii) the inefficient pre-processing filter bank step can be subsumed within the FLK algorithm as a sparse diagonal weighting matrix, (iii) unlike traditional LK the computational cost is invariant to the number of filters and as a result far more efficient, and (iv) this approach can be extended to the inverse compositional form of the LK algorithm where nearly all steps (including Fourier transform and filter bank pre-processing) can be pre-computed leading to an extremely efficient and robust approach to gradient descent image matching. Further, these computational savings translate to non-rigid object alignment tasks that are considered extensions of the LK algorithm such as those found in Active Appearance Models (AAMs).

A high frequency current source converter with adjustable magnitude to drive high power piezoelectric transducers

A general electrical model of a piezoelectric transducer for ultrasound applications consists of a capacitor in parallel with RLC legs. A high power voltage source converter can however generate significant voltage stress across the transducer that creates high leakage currents. One solution is to reduce the voltage stress across the piezoelectric transducer by using an LC filter, however a main drawback is changing the piezoelectric resonant frequency and its characteristics. Thereby it reduces the efficiency of energy conversion through the transducer. This paper proposes that a high frequency current source converter is a suitable topology to drive high power piezoelectric transducers efficiently.

Power electronic converters for high power ultrasound transducers

Piezoelectric transducers convert electrical energy to mechanical energy and play a great role in ultrasound systems. Ultrasound power transducer performance is strongly related to the applied electrical excitation. To have a suitable excitation for maximum energy conversion, it is required to analyze the effects of input signal waveform, medium and input signal distortion on the characteristic of a high power ultrasound system (including ultrasound transducer). In this research, different input voltage signals are generated using a single-phase power inverter and a linear power amplifier to excite a high power ultrasound transducer in different medium (water and oil) in order to study the characteristic of the system. We have also considered and analyzed the effect of power converter output voltage distortions on the performance of the high power ultrasound transducer using a passive filter.

Designing a new robust on-line secondary path modeling technique for feedforward active noise control systems

Several approaches have been introduced in the literature for active noise control (ANC) systems. Since the filtered-x least-mean-square (FxLMS) algorithm appears to be the best choice as a controller filter, researchers tend to improve performance of ANC systems by enhancing and modifying this algorithm. This paper proposes a new version of the FxLMS algorithm, as a first novelty. In many ANC applications, an on-line secondary path modeling method using white noise as a training signal is required to ensure convergence of the system. As a second novelty, this paper proposes a new approach for on-line secondary path modeling on the basis of a new variable-step-size (VSS) LMS algorithm in feed forward ANC systems. The proposed algorithm is designed so that the noise injection is stopped at the optimum point when the modeling accuracy is sufficient. In this approach, a sudden change in the secondary path during operation makes the algorithm reactivate injection of the white noise to re-adjust the secondary path estimate. Comparative simulation results shown in this paper indicate the effectiveness of the proposed approach in reducing both narrow-band and broad-band noise. In addition, the proposed ANC system is robust against sudden changes of the secondary path model.

An efficient online secondary path estimation for feedback active noise control systems

In practical cases for active noise control (ANC), the secondary path has usually a time varying behavior. For these cases, an online secondary path modeling method that uses a white noise as a training signal is required to ensure convergence of the system. The modeling accuracy and the convergence rate are increased when a white noise with a larger variance is used. However, the larger variance increases the residual noise, which decreases performance of the system and additionally causes instability problem to feedback structures. A sudden change in the secondary path leads to divergence of the online secondary path modeling filter. To overcome these problems, this paper proposes a new approach for online secondary path modeling in feedback ANC systems. The proposed algorithm uses the advantages of white noise with larger variance to model the secondary path, but the injection is stopped at the optimum point to increase performance of the algorithm and to prevent the instability effect of the white noise. In this approach, instead of continuous injection of the white noise, a sudden change in secondary path during the operation makes the algorithm to reactivate injection of the white noise to correct the secondary path estimation. In addition, the proposed method models the secondary path without the need of using off-line estimation of the secondary path. Considering the above features increases the convergence rate and modeling accuracy, which results in a high system performance. Computer simulation results shown in this paper indicate effectiveness of the proposed method.

A framework for a dense matching algorithm : Results using matching metrics and order statistic filters

An algorithm for computing dense correspondences between images of a stereo pair or image sequence is presented. The algorithm can make use of both standard matching metrics and the rank and census filters, two filters based on order statistics which have been applied to the image matching problem. Their advantages include robustness to radiometric distortion and amenability to hardware implementation. Results obtained using both real stereo pairs and a synthetic stereo pair with ground truth were compared. The rank and census filters were shown to significantly improve performance in the case of radiometric distortion. In all cases, the results obtained were comparable to, if not better than, those obtained using standard matching metrics. Furthermore, the rank and census have the additional advantage that their computational overhead is less than these metrics. For all techniques tested, the difference between the results obtained for the synthetic stereo pair, and the ground truth results was small.

Adsorption of p-nitrophenol on organoclays

In this study, organoclays were prepared through ion exchange of a single cationic surfactant, hexadecyltrimethylammonium bromide and characterised by a range of methods including X-ray diffraction (XRD) and thermogravimetric analysis. Changes in the surface properties of montmorillonite and the organoclays were observed and the basal spacings of organoclays with and without p-nitrophenol were determined using XRD. The thermal stability of both organoclays were measured using thermogravimetry. As the surfactant loading increased, the expanded basal spacings were observed, and different molecular configurations of surfactant were identified. When the surfactant loading exceeded 1.0 CEC, surfactant molecules tend to adsorb strongly on the clay surface and this resulted in increased affinity to organic compounds. The adsorbed p-nitrophenol and the surfactant decomposed simultaneously. Hence, the surfactant molecules and adsorbed p-nitrophenol are important in determining the thermal stabilities of organoclays. This study enhances the understanding of the structure and adsorption properties of organoclays and has further implications for the application of organoclays as filter materials for the removal of organic pollutants in aqueous solutions.

Exit humidity of wet scrubbers for underground coal mines

A wet scrubber is a device used in underground coal mines for the exhaust treatment system of various internal combustion engines (generally diesel) primarily as a spark arrestor with a secondary function to remove pollutants from the exhaust gas. A pool of scrubbing liquid (generally water based) is used in conjunction with a Diesel Particulate Filter (DPF). Scrubbers are widely used in underground applications of diesel engines as their exhaust contains high concentration of harmful diesel particulate matter (DPM) and other pollutant gases. Currently the DPFs have to be replaced frequently because moisture output from the wet scrubber blocks the filter media and causes reduced capacity. This paper presents experimental and theoretical studies on the heat and mass transfer mechanisms of the exhaust flow both under and above the water surface, aiming at finding the cause and effects of the moisture reaching the filters and employing a solution to reduce the humidity and DPM output, and to prolong the change-out period of the DPF. By assuming a steady flow condition, heat transfer from the inlet exhaust gas balances energy required for the water evaporation. Hence the exit humidity will decrease with the increase of exit temperature. Experiments on a real scrubber are underway.

General trajectory prior for non-rigid reconstruction

Trajectory basis Non-Rigid Structure From Motion (NRSFM) currently faces two problems: the limit of reconstructability and the need to tune the basis size for different sequences. This paper provides a novel theoretical bound on 3D reconstruction error, arguing that the existing definition of reconstructability is fundamentally flawed in that it fails to consider system condition. This insight motivates a novel strategy whereby the trajectory's response to a set of high-pass filters is minimised. The new approach eliminates the need to tune the basis size and is more efficient for long sequences. Additionally, the truncated DCT basis is shown to have a dual interpretation as a high-pass filter. The success of trajectory filter reconstruction is demonstrated quantitatively on synthetic projections of real motion capture sequences and qualitatively on real image sequences.