ShadowTutor: Distributed Partial Distillation for Mobile Video DNN Inference

Following the recent success of deep neural networks (DNN) on video computer vision tasks, performing DNN inferences on videos that originate from mobile devices has gained practical significance. As such, previous approaches developed methods to offload DNN inference computations for images to cloud servers to manage the resource constraints of mobile devices. However, when it comes to video data, communicating information of every frame consumes excessive network bandwidth and renders the entire system susceptible to adverse network conditions such as congestion. Thus, in this work, we seek to exploit the temporal coherence between nearby frames of a video stream to mitigate network pressure. That is, we propose ShadowTutor, a distributed video DNN inference framework that reduces the number of network transmissions through intermittent knowledge distillation to a student model. Moreover, we update only a subset of the student's parameters, which we call partial distillation, to reduce the data size of each network transmission. Specifically, the server runs a large and general teacher model, and the mobile device only runs an extremely small but specialized student model. On sparsely selected key frames, the server partially trains the student model by targeting the teacher's response and sends the updated part to the mobile device. We investigate the effectiveness of ShadowTutor with HD video semantic segmentation. Evaluations show that network data transfer is reduced by 95% on average. Moreover, the throughput of the system is improved by over three times and shows robustness to changes in network bandwidth.Comment: Accepted at ICPP 202

Closed-Loop Recycling of Copper from Waste Printed Circuit Boards Using Bioleaching and Electrowinning Processes

International audienceIn the present study, a model of closed-loop recycling of copper from PCBs is demonstrated, which involves the sequential application of bioleaching and electrowinning to selectively extract copper. This approach is proposed as part of the solution to resolve the challenging ever-increasing accumulation of electronic waste, e-waste, in the environment. This work is targeting copper, the most abundant metal in e-waste that represents up to 20% by weight of printed circuit boards (PCBs). In the first stage, bioleaching was tested for different pulp densities (0.25–1.00% w/v) and successfully used to extract multiple metals from PCBs using the acidophilic bacterium, Acidithiobacillus ferrooxidans. In the second stage, the method focused on the recovery of copper from the bioleachate by electrowinning. Metallic copper foils were formed, and the results demonstrated that 75.8% of copper available in PCBs had been recovered as a high quality copper foil, with 99 + % purity, as determined by energy dispersive X-ray analysis and Inductively-Coupled Plasma Optical Emission Spectrometry. This model of copper extraction, combining bioleaching and electrowinning, demonstrates a closed-loop method of recycling that illustrates the application of bioleaching in the circular economy. The copper foils have the potential to be reused, to form new, high value copper clad laminate for the production of complex printed circuit boards for the electronics manufacturing industry. Graphic Abstract: [Figure not available: see fulltext.] © 2020, The Author(s)

Quality of Published medical articles in approved Medical Journals by Islamic Republic of Iran Committee of Medical Journal (1983-2005)

Background and Objective: Quality of medical articles is effective at improvement of medical science. This study was done for determining of published medical articles quality in approved Medical Journals. Materials and Methods: This cross- sectional study was done on 690 medial articles, which published between 1983-2005 in scientific journals, approved by special Medical Journal committee of Ministry of health and medical Education (MOHME) in Iran, during 2007. Source of data was indexed medical journal in the Iranmedex database. Results: Type of study in 52% of articles was descriptive, 21.2% was interventional and 5.8% of them were analytical. In recent years the number of analytic and interventional articles have been increased significantly in comparison to other types (P<0.05). There was no qualitative type article in published papers. The percentages of original, case report and review articles were 44.9%, 36.9% and 14.1%, respectively. In recent years the rate of original articles has increased in comparison to case report and review articles (P<0.05). In 80% of articles, at least one statistical test was applied. 60% of articles were clinical and 82% of them have been written in Persian language. Conclusion: Findings showed an increasing trend in quality indexes of published articles. It seems in recent years, the changes of MOHME policies in evaluation of the research deputy of medical science universities implementation of research and scientific writing workshops ratting protocol of approved medical journals and academic members promotion guidelines, resulted in improvement qualitative index of articles