G-CAME: Gaussian-Class Activation Mapping Explainer for Object Detectors

Nowadays, deep neural networks for object detection in images are very prevalent. However, due to the complexity of these networks, users find it hard to understand why these objects are detected by models. We proposed Gaussian Class Activation Mapping Explainer (G-CAME), which generates a saliency map as the explanation for object detection models. G-CAME can be considered a CAM-based method that uses the activation maps of selected layers combined with the Gaussian kernel to highlight the important regions in the image for the predicted box. Compared with other Region-based methods, G-CAME can transcend time constraints as it takes a very short time to explain an object. We also evaluated our method qualitatively and quantitatively with YOLOX on the MS-COCO 2017 dataset and guided to apply G-CAME into the two-stage Faster-RCNN model.Comment: 10 figure

Transport Properties of a GaAs/InGaAs/GaAs Quantum Well: Temperature, Magnetic Field and Many-body Effects

We investigate the zero and finite temperature transport properties of a quasi-two-dimensional electron gas in a GaAs/InGaAs/GaAs quantum well under a magnetic field, taking into account many-body effects via a local-field correction. We consider the surface roughness, roughness-induced piezoelectric, remote charged impurity and homogenous background charged impurity scattering. The effects of the quantum well width, carrier density, temperature and local-field correction on resistance ratio are investigated. We also consider the dependence of the total mobility on the multiple scattering effect

A Novel Explainable Artificial Intelligence Model in Image Classification problem

In recent years, artificial intelligence is increasingly being applied widely in many different fields and has a profound and direct impact on human life. Following this is the need to understand the principles of the model making predictions. Since most of the current high-precision models are black boxes, neither the AI scientist nor the end-user deeply understands what's going on inside these models. Therefore, many algorithms are studied for the purpose of explaining AI models, especially those in the problem of image classification in the field of computer vision such as LIME, CAM, GradCAM. However, these algorithms still have limitations such as LIME's long execution time and CAM's confusing interpretation of concreteness and clarity. Therefore, in this paper, we propose a new method called Segmentation - Class Activation Mapping (SeCAM) that combines the advantages of these algorithms above, while at the same time overcoming their disadvantages. We tested this algorithm with various models, including ResNet50, Inception-v3, VGG16 from ImageNet Large Scale Visual Recognition Challenge (ILSVRC) data set. Outstanding results when the algorithm has met all the requirements for a specific explanation in a remarkably concise time.Comment: Published in the Proceedings of FAIC 202

Trajectory Tracking Control Design for Dual-Arm Robots Using Dynamic Surface Controller

This paper presents a dynamic surface controller (DSC) for dual-arm robots (DAR) tracking desired trajectories. The DSC algorithm is based on backstepping technique and multiple sliding surface control principle, but with an important addition. In the design of DSC, low-pass filters are included which prevent the complexity in computing due to the “explosion of terms”, i.e. the number of terms in the control law rapidly gets out of hand. Therefore, a controller constructed from this algorithm is simulated on a four degrees of freedom (DOF) dual-arm robot with a complex kinetic dynamic model. Moreover, the stability of the control system is proved by using Lyapunov theory. The simulation results show the effectiveness of the controller which provide precise tracking performance of the manipulator

Chemical profile and antibacterial activity of acetone extract of Homalomena cochinchinensis Engl. (Araceae)

Homalomena cochinchinensis Engl. is a rare species which is found in Southern China, Cambodia, Laos and Vietnam and its chemical constituents and bioactivity have not been determined yet. In this study, we identified 32 and 38 compounds in acetone extracts of H. cochinchinensis aerial part and rhizome, respectively via gas chromatography mass spectrometry (GC/MS). The main constituents of acetone extract of the aerial part were 3-((4Z,7Z)-Heptadeca-4,7-dien-1-yl)phenol (18.73%); cis-9,cis-12-Octadecadienoic acid (12.04%); linolenic acid (11.08%); n-Hexadecanoic acid (10.13%); (Z)-3-(Heptadec-10-en-1-yl)phenol (7.09%); ?-Sitosterol (5.58%) and linalool (5.56%). On the other hand, acetone extract of rhizome contained linalool (28.42%); 1,2,3-Propanetriol, 1-acetate (10.13%); 3-((4Z,7Z)-Heptadeca-4,7-dien-1-yl)phenol (5.28%); 3-Buten-2-one, 3-methyl-4-(1,3,3-trimethyl-7-oxabicyclo[4.1.0]heptan-1-yl)- (5.28%) and 4-(2,6,6-Trimethyl-cyclohex-1-enyl)-butyric acid (4.54%). Furthermore, this study has also proved the antibacterial activity of acetone extracts from the aerial part and the rhizome of this species for the first time using disk diffusion method. The results showed that the extract of the aerial part could inhibit the growth of 5 out of a total 6 bacterial strains, including Bacillus cereus, Escherichia coli, Pseudomonas aeruginosa, Salmonella enteritidis and Staphylococcus aureus; while the susceptible strains to the rhizome extract were 5 strains, such as B. cereus, E. coli, P. aeruginosa, Salmonella typhimurium and S. aureus. The findings suggest the further application of this species in pharmacology and medicine

Disinfection performance of an ultraviolet lamp: a CFD investigation

Ultraviolet (UV)-based devices have shown their effectiveness on various germicidal purposes. To serve their design optimisation, the disinfection effectiveness of a vertically cylindrical UV lamp, whose wattage ranges from P = 30 − 100 W, is numerically investigated in this work. The UV radiation is solved by the Finite Volume Method together with the Discrete Ordinates model. Various results for the UV intensity and its bactericidal effects against several popular virus types, i.e., Corona-SARS, Herpes (type 2), and HIV, are reported and analysed in detail. Results show that the UV irradiance is greatly dependent on the lamp power. Additionally, it is indicated that the higher the lamp wattage employed, the larger the bactericidal rate is observed, resulting in the greater effectiveness of the UV disinfection process. Nevertheless, the wattage of P ≤ 100W is determined to be insufficient for an effective disinfection performance in a whole room; higher values of power must hence be considered in case intensive sterilization is required. Furthermore, the germicidal effect gets reduced with the viruses less sensitive to UV rays, e.g, the bactericidal rate against the HIV virus is only ∼8.98% at the surrounding walls

Safety and efficacy of fluoxetine on functional outcome after acute stroke (AFFINITY): a randomised, double-blind, placebo-controlled trial

Background Trials of fluoxetine for recovery after stroke report conflicting results. The Assessment oF FluoxetINe In sTroke recoverY (AFFINITY) trial aimed to show if daily oral fluoxetine for 6 months after stroke improves functional outcome in an ethnically diverse population. Methods AFFINITY was a randomised, parallel-group, double-blind, placebo-controlled trial done in 43 hospital stroke units in Australia (n=29), New Zealand (four), and Vietnam (ten). Eligible patients were adults (aged ≥18 years) with a clinical diagnosis of acute stroke in the previous 2–15 days, brain imaging consistent with ischaemic or haemorrhagic stroke, and a persisting neurological deficit that produced a modified Rankin Scale (mRS) score of 1 or more. Patients were randomly assigned 1:1 via a web-based system using a minimisation algorithm to once daily, oral fluoxetine 20 mg capsules or matching placebo for 6 months. Patients, carers, investigators, and outcome assessors were masked to the treatment allocation. The primary outcome was functional status, measured by the mRS, at 6 months. The primary analysis was an ordinal logistic regression of the mRS at 6 months, adjusted for minimisation variables. Primary and safety analyses were done according to the patient's treatment allocation. The trial is registered with the Australian New Zealand Clinical Trials Registry, ACTRN12611000774921. Findings Between Jan 11, 2013, and June 30, 2019, 1280 patients were recruited in Australia (n=532), New Zealand (n=42), and Vietnam (n=706), of whom 642 were randomly assigned to fluoxetine and 638 were randomly assigned to placebo. Mean duration of trial treatment was 167 days (SD 48·1). At 6 months, mRS data were available in 624 (97%) patients in the fluoxetine group and 632 (99%) in the placebo group. The distribution of mRS categories was similar in the fluoxetine and placebo groups (adjusted common odds ratio 0·94, 95% CI 0·76–1·15; p=0·53). Compared with patients in the placebo group, patients in the fluoxetine group had more falls (20 [3%] vs seven [1%]; p=0·018), bone fractures (19 [3%] vs six [1%]; p=0·014), and epileptic seizures (ten [2%] vs two [<1%]; p=0·038) at 6 months. Interpretation Oral fluoxetine 20 mg daily for 6 months after acute stroke did not improve functional outcome and increased the risk of falls, bone fractures, and epileptic seizures. These results do not support the use of fluoxetine to improve functional outcome after stroke

A molecular dynamics study on cooling rate effect on atomic structure of solidified silver nanoparticles

The atomic structures and solidification point of silver nanoparticles (SNPs) are studied in a series of molecular dynamics simulations based on the empirical embedded atom methods (EAM). The solidification point is calculated from the extracted potential energy during the cooling process, whereas the atomic structures are analyzed using the common neighbor (CN) method. The results indicate that the structures of the solidified SNPs are very sensitive to both the applied cooling rate and the particle size. We find the critical cooling rate where a glassy structure is observed. Below the critical rate, polycrystalline nanoparticles are formed, where the percentage of the close-packed structures, i.e., FCC and HCP, decreases with increasing cooling rate. Moreover, the proportion of those structures is always larger with a bigger particle size for an identical applied cooling rate. The findings in this study provide useful information for many practical applications where the nanostructure strongly affects thermal management and operational efficiency