MEMO: Coverage-guided Model Generation For Deep Learning Library Testing

Recent deep learning (DL) applications are mostly built on top of DL libraries. The quality assurance of these libraries is critical to the dependable deployment of DL applications. A few techniques have thereby been proposed to test DL libraries by generating DL models as test inputs. Then these techniques feed those DL models to DL libraries for making inferences, in order to exercise DL libraries modules related to a DL model's execution. However, the test effectiveness of these techniques is constrained by the diversity of generated DL models. Our investigation finds that these techniques can cover at most 11.7% of layer pairs (i.e., call sequence between two layer APIs) and 55.8% of layer parameters (e.g., "padding" in Conv2D). As a result, we find that many bugs arising from specific layer pairs and parameters can be missed by existing techniques. In view of the limitations of existing DL library testing techniques, we propose MEMO to efficiently generate diverse DL models by exploring layer types, layer pairs, and layer parameters. MEMO: (1) designs an initial model reduction technique to boost test efficiency without compromising model diversity; and (2) designs a set of mutation operators for a customized Markov Chain Monte Carlo (MCMC) algorithm to explore new layer types, layer pairs, and layer parameters. We evaluate MEMO on seven popular DL libraries, including four for model execution (TensorFlow, PyTorch and MXNet, and ONNX) and three for model conversions (Keras-MXNet, TF2ONNX, ONNX2PyTorch). The evaluation result shows that MEMO outperforms recent works by covering 10.3% more layer pairs, 15.3% more layer parameters, and 2.3% library branches. Moreover, MEMO detects 29 new bugs in the latest version of DL libraries, with 17 of them confirmed by DL library developers, and 5 of those confirmed bugs have been fixed.Comment: 11 pages, 8 figure

A novel WebVR-Based lightweight framework for virtual visualization of blood vasculum

With the arrival of the Web 2.0 era and the rapid development of virtual reality (VR) technology in recent years, WebVR technology has emerged as the combination of Web 2.0 and VR. Moreover, the concept of “WebVR + medical science”is also proposed to advance medical applications. However, due to the limited storage space and low computing capability of Web browsers, it is difficult to achieve real-time rendering of large-scale medical vascular models on the Web, let alone large-scale vascular animation simulations. The framework proposed in this paper can achieve virtual display of the medical blood vasculum, including lightweight processing of the vasculum and virtual realization of blood flow. This innovative framework presents a simulation algorithm for the virtual blood path based on the Catmull-Rom spline. The mechanisms of progressive compression and online recovery of the lightweight vascular structure are further proposed. The experimental results show that our framework has a shorter browser-side response time than existing methods and achieves efficient real-time simulation

A multi-directional motion interacting fusion model for diver tracking

According to the diver motion characteristics, which are low speed and rapid change of direction, a multi-directional motion model is presented. Then the motion model is introduced into an interacting multiple model method, while the timevarying motion model transition probability was corrected according to current measurements. Firstly, the predictive state was obtained by a multi-directional motion model. Secondly, the parallel Kalman filters were applied to estimate multi-directional state. Finally, the interactive fusion processing for estimations from multidirectional motion model was conducted to implement diver state estimation. The method was verified by both simulation and experiment. The results show that the proposed method has higher tracking accuracy and superior adaptability than conventional interactive multiple model algorithm based on single direction motion model. The proposed method is effective for diver tracking

`Maser-in-a-Shoebox': a portable plug-and-play maser device at room-temperature and zero magnetic-field

Masers, the microwave analogues of lasers, have seen a renaissance owing to the discovery of gain media that mase at room-temperature and zero-applied magnetic field. However, despite the ease with which the devices can be demonstrated under ambient conditions, achieving the ubiquity and portability which lasers enjoy has to date remained challenging. We present a maser device with a miniaturized maser cavity, gain material and laser pump source that fits within the size of a shoebox. The gain medium used is pentacene-doped in para-terphenyl and it is shown to give a strong masing signal with a peak power of -5 dBm even within a smaller form factor. The device is also shown to mase at different frequencies within a small range of 1.5 MHz away from the resonant frequency. The portability and simplicity of the device, which weighs under 5 kg, paves the way for demonstrators particularly in the areas of low-noise amplifiers, quantum sensors, cavity quantum electrodynamics and long-range communications

A New Dynamic Path Planning Approach for Unmanned Aerial Vehicles

Dynamic path planning is one of the key procedures for unmanned aerial vehicles (UAV) to successfully fulfill the diversified missions. In this paper, we propose a new algorithm for path planning based on ant colony optimization (ACO) and artificial potential field. In the proposed algorithm, both dynamic threats and static obstacles are taken into account to generate an artificial field representing the environment for collision free path planning. To enhance the path searching efficiency, a coordinate transformation is applied to move the origin of the map to the starting point of the path and in line with the source-destination direction. Cost functions are established to represent the dynamically changing threats, and the cost value is considered as a scalar value of mobile threats which are vectors actually. In the process of searching for an optimal moving direction for UAV, the cost values of path, mobile threats, and total cost are optimized using ant optimization algorithm. The experimental results demonstrated the performance of the new proposed algorithm, which showed that a smoother planning path with the lowest cost for UAVs can be obtained through our algorithm. (PDF) A New Dynamic Path Planning Approach for Unmanned Aerial Vehicles. Available from: https://www.researchgate.net/publication/328765418_A_New_Dynamic_Path_Planning_Approach_for_Unmanned_Aerial_Vehicles [accessed Nov 20 2018]

A Multimode Responsive Aptasensor for Adenosine Detection

We report a novel multimode detection aptasensor with three signal responses (i.e., fluorescence recovery, enhanced Raman signal, and color change). The presence of adenosine induces the conformational switch of the adenosine aptamer (Apt), forming adenosine-aptamer complex and releasing quantum dots (QDs) from AuNPs, resulting in the recovered fluorescence, the enhanced Raman signal, and color change of the solution. The multimode signal recognition is potentially advantageous in improving the precision and reliability of the detection in complex environments compared to the conventional single-mode sensing system. The multimode detection strategy opens up a new possibility in sensing and quantifying more other target molecules

An IoT-Based Framework of Webvr Visualization for Medical Big Data in Connected Health

Recently, telemedicine has been widely applied in remote diagnosis, treatment and counseling, where the Internet of Things (IoT) technology plays an important role. In the process of telemedicine, data are collected from remote medical equipment, such as CT machine and MRI machine, and then transmitted and reconstructed locally in three-dimensions. Due to the large amount of data to be transmitted in the reconstructed model and the small storage capacity, data need to be compressed progressively before transmission. On this basis, we proposed a lightweight progressive transmission algorithm based on large data visualization in telemedicine to improve transmission efficiency and achieve lossless transmission of original data. Moreover, a novel four-layer system architecture based on IoT has been introduced, including the sensing layer, analysis layer, network layer and application layer. In this way, the three-dimensional reconstructed data at the local end is compressed and transmitted to the remote end, and then visualized at the remote end to show reconstructed 3D models. Thus, it is conducive to doctors in remote real-time diagnosis and treatment, and then realize the data processing and transmission between doctors, patients and medical equipment

Genome-wide identification, expression analysis, and potential roles under low-temperature stress of bHLH gene family in Prunus sibirica

The basic helix-loop-helix (bHLH) family is one of the most well-known transcription factor families in plants, and it regulates growth, development, and abiotic stress responses. However, systematic analyses of the bHLH gene family in Prunus sibirica have not been reported to date. In this study, 104 PsbHLHs were identified and classified into 23 subfamilies that were unevenly distributed on eight chromosomes. Nineteen pairs of segmental replication genes and ten pairs of tandem replication genes were identified, and all duplicated gene pairs were under purifying selection. PsbHLHs of the same subfamily usually share similar motif compositions and exon-intron structures. PsbHLHs contain multiple stress-responsive elements. PsbHLHs exhibit functional diversity by interacting and coordinating with other members. Twenty PsbHLHs showed varying degrees of expression. Eleven genes up-regulated and nine genes down-regulated in −4°C. The majority of PsbHLHs were highly expressed in the roots and pistils. Transient transfection experiments demonstrated that transgenic plants with overexpressed PsbHLH42 have better cold tolerance. In conclusion, the results of this study have significant implications for future research on the involvement of bHLH genes in the development and stress responses of Prunus sibirica