Towards Fairer and More Efficient Federated Learning via Multidimensional Personalized Edge Models

Federated learning (FL) is an emerging technique that trains massive and geographically distributed edge data while maintaining privacy. However, FL has inherent challenges in terms of fairness and computational efficiency due to the rising heterogeneity of edges, and thus usually results in sub-optimal performance in recent state-of-the-art (SOTA) solutions. In this paper, we propose a Customized Federated Learning (CFL) system to eliminate FL heterogeneity from multiple dimensions. Specifically, CFL tailors personalized models from the specially designed global model for each client jointly guided by an online trained model-search helper and a novel aggregation algorithm. Extensive experiments demonstrate that CFL has full-stack advantages for both FL training and edge reasoning and significantly improves the SOTA performance w.r.t. model accuracy (up to 7.2% in the non-heterogeneous environment and up to 21.8% in the heterogeneous environment), efficiency, and FL fairness.Comment: 8 pages, 7 figure

Tile Classification Based Viewport Prediction with Multi-modal Fusion Transformer

Viewport prediction is a crucial aspect of tile-based 360 video streaming system. However, existing trajectory based methods lack of robustness, also oversimplify the process of information construction and fusion between different modality inputs, leading to the error accumulation problem. In this paper, we propose a tile classification based viewport prediction method with Multi-modal Fusion Transformer, namely MFTR. Specifically, MFTR utilizes transformer-based networks to extract the long-range dependencies within each modality, then mine intra- and inter-modality relations to capture the combined impact of user historical inputs and video contents on future viewport selection. In addition, MFTR categorizes future tiles into two categories: user interested or not, and selects future viewport as the region that contains most user interested tiles. Comparing with predicting head trajectories, choosing future viewport based on tile's binary classification results exhibits better robustness and interpretability. To evaluate our proposed MFTR, we conduct extensive experiments on two widely used PVS-HM and Xu-Gaze dataset. MFTR shows superior performance over state-of-the-art methods in terms of average prediction accuracy and overlap ratio, also presents competitive computation efficiency.Comment: This paper is accepted by ACM-MM 202

Meteor: Improved Secure 3-Party Neural Network Inference with Reducing Online Communication Costs

Secure neural network inference has been a promising solution to private Deep-Learning-as-a-Service, which enables the service provider and user to execute neural network inference without revealing their private inputs. However, the expensive overhead of current schemes is still an obstacle when applied in real applications. In this work, we present \textsc{Meteor}, an online communication-efficient and fast secure 3-party computation neural network inference system aginst semi-honest adversary in honest-majority. The main contributions of \textsc{Meteor} are two-fold: \romannumeral1) We propose a new and improved 3-party secret sharing scheme stemming from the \textit{linearity} of replicated secret sharing, and design efficient protocols for the basic cryptographic primitives, including linear operations, multiplication, most significant bit extraction, and multiplexer. \romannumeral2) Furthermore, we build efficient and secure blocks for the widely used neural network operators such as Matrix Multiplication, ReLU, and Maxpool, along with exploiting several specific optimizations for better efficiency. Our total communication with the setup phase is a little larger than SecureNN (PoPETs\u2719) and \textsc{Falcon} (PoPETs\u2721), two state-of-the-art solutions, but the gap is not significant when the online phase must be optimized as a priority. Using \textsc{Meteor}, we perform extensive evaluations on various neural networks. Compared to SecureNN and \textsc{Falcon}, we reduce the online communication costs by up to $25.6\times$ and $1.5\times$, and improve the running-time by at most $9.8\times$ (resp. $8.1\times$) and $1.5\times$ (resp. $2.1\times$) in LAN (resp. WAN) for the online inference

Gastric Lavage in Acute Organophosphorus Pesticide poisoning (GLAOP) – a randomised controlled trial of multiple vs. single gastric lavage in unselected acute organophosphorus pesticide poisoning

BACKGROUND: Organophosphorus (OP) pesticide poisoning is the most common form of pesticide poisoning in many Asian countries. Guidelines in western countries for management of poisoning indicate that gastric lavage should be performed only if two criteria are met: within one hour of poison ingestion and substantial ingested amount. But the evidence on which these guidelines are based is from medicine overdoses in developed countries and may be irrelevant to OP poisoning in Asia. Chinese clinical experience suggests that OP remains in the stomach for several hours or even days after ingestion. Thus, there may be reasons for doing single or multiple gastric lavages for OP poisoning. There have been no randomised controlled trials (RCTs) to assess this practice of multiple lavages. Since it is currently standard therapy in China, we cannot perform a RCT of no lavage vs. a single lavage vs. multiple lavages. We will compare a single gastric lavage with three gastric lavages as the first stage to assess the role of gastric lavage in OP poisoning. METHODS/DESIGN: We have designed an RCT assessing the effectiveness of multiple gastric lavages in adult OP self-poisoning patients admitted to three Chinese hospitals within 12 hrs of ingestion. Patients will be randomised to standard treatment plus either a single gastric lavage on admission or three gastric lavages at four hour intervals. The primary outcome is in-hospital mortality. Analysis will be on an intention-to-treat basis. On the basis of the historical incidence of OP at the study sites, we expect to enroll 908 patients over three years. This projected sample size provides sufficient power to evaluate the death rate; and a variety of other exposure and outcome variables, including particular OPs and ingestion time. Changes of OP level will be analyzed in order to provide some toxic kinetic data. DISCUSSION: the GLAOP study is a novel, prospective cohort study that will explore to the toxic kinetics of OP and effects of gastric lavage on it. Given the poor information about the impact of gastric lavage on clinical outcomes for OP patients, this study can provide important information to inform clinical practice

Study of Impact Characteristics of ZrO2 Ceramic Composite Projectiles on Ceramic Composite Armor

Exploring new armor-piercing materials is crucial for improving the penetrative ability of projectiles. Based on the process of in situ solidification injection molding through ceramic dispersant hydrolytic degradation, a ZrO2 ceramic material suitable for use as the tip of a 12.7 mm kinetic energy (KE) projectile was prepared. The ZrO2 ceramic tip can be matched with the metal core of a conventional projectile to form a ceramic composite projectile, increasing the damage to the Al2O3 ceramic composite armor. Specifically, the ZrO2 ceramic tip can increase the impact load on the Al2O3 ceramic panel, prolonging the pre-damage phase and reducing the stable penetration phase, shortening the mass erosion time of the metal core compared with a 12.7 mm metal KE projectile tip. The ceramic composite projectile with the ZrO2 ceramic tip has a lower critical penetration velocity than a 12.7 mm metal KE projectile for Al2O3 ceramic composite armor. Furthermore, the residual velocity, residual length, and residual mass of the metal core of the ceramic composite projectile that penetrated the Al2O3 ceramic composite armor are greater than those of a 12.7 mm metal KE projectile

Effect of CeO2 on Impact Toughness and Corrosion Resistance of WC Reinforced Al-Based Coating by Laser Cladding

WC reinforced Al-based coating with added CeO2 was prepared on the surface of S420 steel by laser cladding. The microstructure and structure of the coatings were analyzed by scanning electron microscope, X-ray diffractometer and optical profiler. The mechanical properties and corrosion properties of the coatings were studied by microhardness tester, friction and wear tester, Charpy impact tester, and electrochemical workstation. The results show that the coating is mainly composed of Al-phase, continuous-phase, and hard reinforced-phase WC, and the coating and substrate show good metallurgical bonding. When the content of CeO2 is 1%, the fine grain strengthening effect is obvious, and the impact toughness of the coating is obviously improved. Appropriate amount of rare earth CeO2 can significantly improve the hardness of the coating. When the content of CeO2 is more than 1%, the wear resistance of the coating decreases. The coating prepared with different CeO2 content has higher impedance and corrosion resistance than that of the substrate. At 1% CeO2 content, the coating has the best corrosion resistance

Predict-and-Drive: Avatar Motion Adaption in Room-Scale Augmented Reality Telepresence with Heterogeneous Spaces

International audienceAvatar-mediated symmetric Augmented Reality (AR) telepresence has emerged with the ability to empower users located in different remote spaces to interact with each other in 3D through avatars. However, different spaces have heterogeneous structures and features, which bring difficulties in synchronizing avatar motions with real user motions and adapting avatar motions to local scenes. To overcome these issues, existing methods generate mutual movable spaces or retarget the placement of avatars. However, these methods limit the telepresence experience in a small sub-area space, fix the positions of users and avatars, or adjust the beginning/ending positions of avatars without presenting smooth transitions. Moreover, the delay between the avatar retargeting and users’ real transitions can break the semantic synchronization between users’ verbal conversation and perceived avatar motion. In this paper, we first examine the impact of the aforementioned transition delay and explore the preferred transition style with the existence of such delay through user studies. With the results showing a significant negative effect of avatar transition delay and providing the design choice of the transition style, we propose a Predict-and-Drive controller to diminish the delay and present the smooth transition of the telepresence avatar. We also introduce a grouping component as an upgrade to immediately calculate a coarse virtual target once the user initiates a transition, which could further eliminate the avatar transition delay. Once having the coarse virtual target or an exactly predicted target, we find the corresponding target for the avatar according to the pre-constructed mapping of objects of interest between two spaces. The avatar control component maintains an artificial potential field of the space and drives the avatar towards the target while respecting the obstacles in the physical environment. We further conduct ablation studies to evaluate the effectiveness of our proposed components

Toward Cost-Effective Mobile Video Streaming through Environment-Aware Watching State Prediction

Mobile video applications are becoming increasingly prevalent and enriching the way people learn and are entertained. However, on mobile terminals with inherently limited resources, mobile video streaming services consume too much energy and bandwidth, which is an urgent problem to solve. At present, research on cost-effective mobile video streaming typically focuses on the management of data transmission. Among such studies, some new approaches consider the user’s behavior to further optimize data transmission. However, these studies have not adequately discussed the specific impact of the physical environment on user behavior. Therefore, this paper takes into account the environment-aware watching state and proposes a cost-effective mobile video streaming scheme to reduce power consumption and mobile data usage. First, the watching state is predicted by machine learning based on user behavior and the physical environment during a given time window. Second, based on the resulting prediction, a downloading algorithm is introduced based on the user equipment (UE) running mode in the LTE system and the VLC player. Finally, according to the corresponding experimental results obtained in a real-world environment, the proposed approach, compared to its benchmarks, effectively reduces the data usage (14.4% lower than that of energy-aware, on average) and power consumption (about 19% when there are screen touches) of mobile devices

Diagnostic procedure for idiopathic eosinophilic pleural effusion: a single-center experience

BACKGROUND: Eosinophilic pleural effusion (EPE) is attributed to several well-recognised causes. However, some patients remain idiopathic, even after thorough clinical work-up. The present study aimed to better characterize idiopathic EPE (IEPE) and to outline the diagnostic procedure for this disease. METHODS: Complete clinical data of 11 consecutive patients with IEPE were prospectively collected and analysed. Preliminary diagnostic procedure of IEPE in our hospital was performed. RESULTS: All the 11 patients had respiratory symptoms and unilateral pleural effusion (PE) occurred in 4 patients. The mean percentage of eosinophils in PE was 22.4% (range, 12.4–50.5%). Lactate dehydrogenase, adenosine deaminase, proteins and carcinoembryonic antigen in PE were 246.0 U/L (range, 89.8–421.9 U/L), 13.8 U/L (range, 1.8–24.0 U/L), 42.6 g/dl (range, 32.8–52.6 g/dl) and 2.17 mg/mL (range, 0.46–4.31 mg/mL), respectively. Parasite-specific IgG antibody in blood and parasite eggs in stool were both negative. No evidence of tuberculosis or malignancy was observed in pleural biopsy. Symptoms and abnormal pulmonary imaging were eliminated after glucocorticoid use. CONCLUSIONS: IEPE is a diagnosis of exclusion. Patients with EPE without a clear cause should be asked to provided complete medical, surgical and drug-related histories. A thorough work-up is essential. Moreover, we recommend follow-up after the use of glucocorticoid until effusion resolves. TRIAL REGISTRATION: GYFYY. Registration No: GYFYY20150901221. Registered time: 1 September 2015. Date of enrolment of the first participant to the trial: 22 January 2016