149 research outputs found

    Spot Dynamics of a Reaction-Diffusion System on the Surface of a Torus

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    Quasi-stationary states consisting of localized spots in a reaction-diffusion system are considered on the surface of a torus with major radius RR and minor radius rr. Under the assumption that these localized spots persist stably, the evolution equation of the spot cores is derived analytically based on the higher-order matched asymptotic expansion with the analytic expression of the Green's function of the Laplace--Beltrami operator on the toroidal surface. Owing to the analytic representation, one can investigate the existence of equilibria with a single spot, two spots, and the ring configuration where NN localized spots are equally spaced along a latitudinal line with mathematical rigor. We show that localized spots at the innermost/outermost locations of the torus are equilibria for any aspect ratio alpha=fracRralpha=frac{R}{r}. In addition, we find that there exists a range of the aspect ratio in which localized spots stay at a special location of the torus. The theoretical results and the linear stability of these spot equilibria are confirmed by solving the nonlinear evolution of the Brusselator reaction-diffusion model by numerical means. We also compare the spot dynamics with the point vortex dynamics, which is another model of spot structures

    Stencil Computation with Vector Outer Product

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    Matrix computation units have been equipped in current architectures to accelerate AI and high performance computing applications. The matrix multiplication and vector outer product are two basic instruction types. The latter one is lighter since the inputs are vectors. Thus it provides more opportunities to develop flexible algorithms for problems other than dense linear algebra computing and more possibilities to optimize the implementation. Stencil computations represent a common class of nested loops in scientific and engineering applications. This paper proposes a novel stencil algorithm using vector outer products. Unlike previous work, the new algorithm arises from the stencil definition in the scatter mode and is initially expressed with formulas of vector outer products. The implementation incorporates a set of optimizations to improve the memory reference pattern, execution pipeline and data reuse by considering various algorithmic options and the data sharing between input vectors. Evaluation on a simulator shows that our design achieves a substantial speedup compared with vectorized stencil algorithm

    A Multi-tasking Model of Speaker-Keyword Classification for Keeping Human in the Loop of Drone-assisted Inspection

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    Audio commands are a preferred communication medium to keep inspectors in the loop of civil infrastructure inspection performed by a semi-autonomous drone. To understand job-specific commands from a group of heterogeneous and dynamic inspectors, a model must be developed cost-effectively for the group and easily adapted when the group changes. This paper is motivated to build a multi-tasking deep learning model that possesses a Share-Split-Collaborate architecture. This architecture allows the two classification tasks to share the feature extractor and then split subject-specific and keyword-specific features intertwined in the extracted features through feature projection and collaborative training. A base model for a group of five authorized subjects is trained and tested on the inspection keyword dataset collected by this study. The model achieved a 95.3% or higher mean accuracy in classifying the keywords of any authorized inspectors. Its mean accuracy in speaker classification is 99.2%. Due to the richer keyword representations that the model learns from the pooled training data, adapting the base model to a new inspector requires only a little training data from that inspector, like five utterances per keyword. Using the speaker classification scores for inspector verification can achieve a success rate of at least 93.9% in verifying authorized inspectors and 76.1% in detecting unauthorized ones. Further, the paper demonstrates the applicability of the proposed model to larger-size groups on a public dataset. This paper provides a solution to addressing challenges facing AI-assisted human-robot interaction, including worker heterogeneity, worker dynamics, and job heterogeneity.Comment: Accepted by Engineering Applications of Artificial Intelligence journal on Oct 31th. Upload the accepted clean versio

    A Review of Software Reliability Testing Techniques

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    In the era of intelligent systems, the safety and reliability of software have received more attention. Software reliability testing is a significant method to ensure reliability, safety and quality of software. The intelligent software technology has not only offered new opportunities but also posed challenges to software reliability technology. The focus of this paper is to explore the software reliability testing technology under the impact of intelligent software technology. In this study, the basic theories of traditional software and intelligent software reliability testing were investigated via related previous works, and a general software reliability testing framework was established. Then, the technologies of software reliability testing were analyzed, including reliability modeling, test case generation, reliability evaluation, testing criteria and testing methods. Finally, the challenges and opportunities of software reliability testing technology were discussed at the end of this paper

    Hidden Addressing Encoding for DNA Storage

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    DNA is a natural storage medium with the advantages of high storage density and long service life compared with traditional media. DNA storage can meet the current storage requirements for massive data. Owing to the limitations of the DNA storage technology, the data need to be converted into short DNA sequences for storage. However, in the process, a large amount of physical redundancy will be generated to index short DNA sequences. To reduce redundancy, this study proposes a DNA storage encoding scheme with hidden addressing. Using the improved fountain encoding scheme, the index replaces part of the data to realize hidden addresses, and then, a 10.1 MB file is encoded with the hidden addressing. First, the Dottup dot plot generator and the Jaccard similarity coefficient analyze the overall self-similarity of the encoding sequence index, and then the sequence fragments of GC content are used to verify the performance of this scheme. The final results show that the encoding scheme indexes with overall lower self-similarity, and the local thermodynamic properties of the sequence are better. The hidden addressing encoding scheme proposed can not only improve the utilization of bases but also ensure the correct rate of DNA storage during the sequencing and decoding processes

    A transducer positioning method for transcranial focused ultrasound treatment of brain tumors

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    PurposeAs a non-invasive method for brain diseases, transcranial focused ultrasound (tFUS) offers higher spatial precision and regulation depth. Due to the altered path and intensity of sonication penetrating the skull, the focus and intensity in the skull are difficult to determine, making the use of ultrasound therapy for cancer treatment experimental and not widely available. The deficiency can be effectively addressed by numerical simulation methods, which enable the optimization of sonication modulation parameters and the determination of precise transducer positioning.MethodsA 3D skull model was established using binarized brain CT images. The selection of the transducer matrix was performed using the radius positioning (RP) method after identifying the intracranial target region. Simulations were performed, encompassing acoustic pressure (AP), acoustic field, and temperature field, in order to provide compelling evidence of the safety of tFUS in sonication-induced thermal effects.ResultsIt was found that the angle of sonication path to the coronal plane obtained at all precision and frequency models did not exceed 10° and 15° to the transverse plane. The results of thermal effects illustrated that the peak temperatures of tFUS were 43.73°C, which did not reach the point of tissue degeneration. Once positioned, tFUS effectively delivers a Full Width at Half Maximum (FWHM) stimulation that targets tumors with diameters of up to 3.72 mm in a one-off. The original precision model showed an attenuation of 24.47 ± 6.13 mm in length and 2.40 ± 1.42 mm in width for the FWHM of sonication after penetrating the skull.ConclusionThe vector angles of the sonication path in each direction were determined based on the transducer positioning results. It has been suggested that when time is limited for precise transducer positioning, fixing the transducer on the horizontal surface of the target region can also yield positive results for stimulation. This framework used a new transducer localization method to offer a reliable basis for further research and offered new methods for the use of tFUS in brain tumor-related research
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