Machine Vision Using Cellphone Camera: A Comparison of deep networks for classifying three challenging denominations of Indian Coins

Indian currency coins come in a variety of denominations. Off all the varieties Rs.1, RS.2, and Rs.5 have similar diameters. Majority of the coin styles in market circulation for denominations of Rs.1 and Rs.2 coins are nearly the same except for numerals on its reverse side. If a coin is resting on its obverse side, the correct denomination is not distinguishable by humans. Therefore, it was hypothesized that a digital image of a coin resting on its either size could be classified into its correct denomination by training a deep neural network model. The digital images were generated by using cheap cell phone cameras. To find the most suitable deep neural network architecture, four were selected based on the preliminary analysis carried out for comparison. The results confirm that two of the four deep neural network models can classify the correct denomination from either side of a coin with an accuracy of 97%.Comment: 6 Pages, 4 Figures, 6 Tables, Conference pape

Neural Approximate Dynamic Programming for On-Demand Ride-Pooling

On-demand ride-pooling (e.g., UberPool) has recently become popular because of its ability to lower costs for passengers while simultaneously increasing revenue for drivers and aggregation companies. Unlike in Taxi on Demand (ToD) services -- where a vehicle is only assigned one passenger at a time -- in on-demand ride-pooling, each (possibly partially filled) vehicle can be assigned a group of passenger requests with multiple different origin and destination pairs. To ensure near real-time response, existing solutions to the real-time ride-pooling problem are myopic in that they optimise the objective (e.g., maximise the number of passengers served) for the current time step without considering its effect on future assignments. This is because even a myopic assignment in ride-pooling involves considering what combinations of passenger requests that can be assigned to vehicles, which adds a layer of combinatorial complexity to the ToD problem. A popular approach that addresses the limitations of myopic assignments in ToD problems is Approximate Dynamic Programming (ADP). Existing ADP methods for ToD can only handle Linear Program (LP) based assignments, however, while the assignment problem in ride-pooling requires an Integer Linear Program (ILP) with bad LP relaxations. To this end, our key technical contribution is in providing a general ADP method that can learn from ILP-based assignments. Additionally, we handle the extra combinatorial complexity from combinations of passenger requests by using a Neural Network based approximate value function and show a connection to Deep Reinforcement Learning that allows us to learn this value-function with increased stability and sample-efficiency. We show that our approach outperforms past approaches on a real-world dataset by up to 16%, a significant improvement in city-scale transportation problems.Comment: Accepted for publication to the Thirty-Fourth AAAI Conference on Artificial Intelligence (AAAI-20

Similar prevalence of anxiety and depression symptoms in any ICU survivor patient relative

Background: Iwashyna et al defined a chronic critically ill (CCI) patient as any patient requiring care in ICU for more than or equal to 10 days. Physicians often assume that the prevalence of anxiety and depression symptoms in relatives of CCI patients would be higher than in those patients who are not CCI. We hypothesized that there would be no difference in the prevalence of anxiety and depression symptoms of relatives of a CCI and those whose patients are not CCI. We aimed to establish that the prevalence of anxiety and depression symptoms are similar in relatives of any ICU survivor patient. Methods: The study was a non-interventional, observational, cross-sectional study. Relatives were evaluated as early as possible after day ten following ICU admission for CCI patients and non-CCI patients on or a day before discharge from ICU. During this evaluation, anonymous demographic data of relatives were captured, and PHQ-9 and GAD-7 scales were administered and completed by the relative. Results: A total of 418 relatives consented and were included in the study [104 in CCI patient group and 314 in non-CCI group]. Overall, the prevalence of anxiety and depression symptoms in the entire study cohort was 23.2% (95% CI, 19.4-27.5) and 16.5% (95% CI, 13.2-20.4), respectively. There was no statistical difference between the two groups in the proportion of PHQ-9 total score >9 (p value: 0.577) as well as the GAD-7 total score (p value: 0.816). Conclusions: There was no difference in the prevalence of anxiety and depression symptoms in relatives of a CCI versus those whose patients are not CCI

Prospective randomized subject-masked study of intravitreal bevacizumab monotherapy versus dexamethasone implant monotherapy in the treatment of persistent diabetic macular edema

Purpose: To compare intravitreal bevacizumab monotherapy with intravitreal dexamethasone delayed delivery system monotherapy for persistent diabetic macular edema. Methods: Single-center, randomized, subject-masked study of eyes with persistent diabetic macular edema, defined as central subfield thickness (CST) >340 μm despite ≥3 anti–vascular endothelial growth factors injections within 5 months. The intravitreal bevacizumab monotherapy (n = 23 eyes) and delayed delivery system monotherapy (n = 27 eyes) groups received treatments q1month and q3months, respectively. Results: Baseline best-corrected visual acuity and CST were similar in the two groups. At Month 7, the mean final best-corrected visual acuity (mean ± SD) was 65 ± 16 letters (mean Snellen visual acuity 20/50) and 64 ± 11 letters (20/50) (P = 0.619), the mean change in best-corrected visual acuity was +5.6 ± 6.1 and +5.8 ± 7.6 letters (P = 0.785), the mean final CST was 471 ± 157 and 336 ± 89 μm (P = 0.001), and the mean change in CST was −13 ± 105 and −122 ± 120 μm (P = 0.005) in the intravitreal bevacizumab monotherapy and delayed delivery system monotherapy groups, respectively. The number of injections was 7.0 ± 0.2 and 2.7 ± 0.5 (P < 0.001) in the 2 groups. Conclusion: The two groups had similar best-corrected visual acuity gains. The delayed delivery system monotherapy group achieved a significantly greater reduction of CST compared with the intravitreal bevacizumab monotherapy group, with a q3month interval of treatment, and had no recurrent edema at any visit

An experimental investigation of tool nose radius and machining parameters on TI-6AL-4V (ELI) using grey relational analysis, regression and ANN models

Ti-6Al-4V Extra Low Interstitial (ELI) exhibits superior properties because of controlled interstitial element of iron and oxygen. The effects of four cutting parameters namely cutting speed, feed, depth of cut and tool nose radius on responses like cutting force, average cutting temperature and surface roughness have been investigated for turning of Ti-6Al-4V (ELI). Total 81 experiments have been performed in dry environment. Grey Relational Analysis has been used for multi-objective optimization. Analysis of Variance test has been carried out to investigate contribution of input parameters. The model was found fit with R-Square value of 88.74%. Regression and ANN models are developed for prediction and compared. From the Grey relational analysis, it is clear that optimum parameters to minimize cutting force, cutting temperature and surface roughness while turning Ti-6Al-4V (ELI), are cutting speed as 140 rpm, Nose radius 1.2mm, Feed 0.051mm/rev and depth of cut is 0.5mm. In comparison of regression model, the ANN model is found to be more accurate with average error of 3.57%

Subnanometer-resolution structures of the grass carp reovirus core and virion.

Grass carp reovirus (GCRV) is a member of the Aquareovirus genus of the family Reoviridae, a large family of double-stranded RNA (dsRNA) viruses infecting plants, insects, fishes and mammals. We report the first subnanometer-resolution three-dimensional structures of both GCRV core and virion by cryoelectron microscopy. These structures have allowed the delineation of interactions among the over 1000 molecules in this enormous macromolecular machine and a detailed comparison with other dsRNA viruses at the secondary-structure level. The GCRV core structure shows that the inner proteins have strong structural similarities with those of orthoreoviruses even at the level of secondary-structure elements, indicating that the structures involved in viral dsRNA interaction and transcription are highly conserved. In contrast, the level of similarity in structures decreases in the proteins situated in the outer layers of the virion. The proteins involved in host recognition and attachment exhibit the least similarities to other members of Reoviridae. Furthermore, in GCRV, the RNA-translocating turrets are in an open state and lack a counterpart for the sigma1 protein situated on top of the close turrets observed in mammalian orthoreovirus. Interestingly, the distribution and the organization of GCRV core proteins resemble those of the cytoplasmic polyhedrosis virus, a cypovirus and the structurally simplest member of the Reoviridae family. Our results suggest that GCRV occupies a unique structure niche between the simpler cypoviruses and the considerably more complex mammalian orthoreovirus, thus providing an important model for understanding the structural and functional conservation and diversity of this enormous family of dsRNA viruses

Optical Coherence Tomography of Retinal and Choroidal Tumors

Optical coherence tomography (OCT) has revolutionized the field of ophthalmology since its introduction 20 years ago. Originally intended primarily for retina specialists to image the macula, it has found its role in other subspecialties that include glaucoma, cornea, and ocular oncology. In ocular oncology, OCT provides axial resolution to approximately 7 microns with cross-sectional images of the retina, delivering valuable information on the effects of intraocular tumors on the retinal architecture. Some effects include retinal edema, subretinal fluid, retinal atrophy, photoreceptor loss, outer retinal thinning, and retinal pigment epithelial detachment. With more advanced technology, OCT now provides imaging deeper into the choroid using a technique called enhanced depth imaging. This allows characterization of the thickness and reflective quality of small (<3 mm thick) choroidal lesions including choroidal nevus and melanoma. Future improvements in image resolution and depth will allow better understanding of the mechanisms of visual loss, tumor growth, and tumor management