Byzantine-Resilient Federated Learning with Heterogeneous Data Distribution

For mitigating Byzantine behaviors in federated learning (FL), most state-of-the-art approaches, such as Bulyan, tend to leverage the similarity of updates from the benign clients. However, in many practical FL scenarios, data is non-IID across clients, thus the updates received from even the benign clients are quite dissimilar. Hence, using similarity based methods result in wasted opportunities to train a model from interesting non-IID data, and also slower model convergence. We propose DiverseFL to overcome this challenge in heterogeneous data distribution settings. Rather than comparing each client's update with other client updates to detect Byzantine clients, DiverseFL compares each client's update with a guiding update of that client. Any client whose update diverges from its associated guiding update is then tagged as a Byzantine node. The FL server in DiverseFL computes the guiding update in every round for each client over a small sample of the client's local data that is received only once before start of the training. However, sharing even a small sample of client's data with the FL server can compromise client's data privacy needs. To tackle this challenge, DiverseFL creates a Trusted Execution Environment (TEE)-based enclave to receive each client's sample and to compute its guiding updates. TEE provides a hardware assisted verification and attestation to each client that its data is not leaked outside of TEE. Through experiments involving neural networks, benchmark datasets and popular Byzantine attacks, we demonstrate that DiverseFL not only performs Byzantine mitigation quite effectively, it also almost matches the performance of OracleSGD, where the server only aggregates the updates from the benign clients

A Young Man with Myocardial Infarction due to Trenbolone Acetate; a Case Report

Over the four decades, a significant decrease has been observed in age-related mortality caused by cardiovascular disease. People in developing countries suffer from CAD at a relatively younger age and about half of MI occurs under the age of fifty years. Abuse of anabolic steroids is one of the less common causes of atherosclerosis. In this report, a 23-year-old body builder male referred to emergency department (ED) with myocardial infarction (MI) following chronic Trenbolone acetate consumption. It seems that a comprehensive history of steroid consumption in young patients referred to ED with the chief complaint of chest pain or its equivalents is necessary in adjunct to other cardiac risk factors

Differentially Private Heavy Hitter Detection using Federated Analytics

In this work, we study practical heuristics to improve the performance of prefix-tree based algorithms for differentially private heavy hitter detection. Our model assumes each user has multiple data points and the goal is to learn as many of the most frequent data points as possible across all users' data with aggregate and local differential privacy. We propose an adaptive hyperparameter tuning algorithm that improves the performance of the algorithm while satisfying computational, communication and privacy constraints. We explore the impact of different data-selection schemes as well as the impact of introducing deny lists during multiple runs of the algorithm. We test these improvements using extensive experimentation on the Reddit dataset~\cite{caldas2018leaf} on the task of learning the most frequent words

Data Leakage via Access Patterns of Sparse Features in Deep Learning-based Recommendation Systems

Online personalized recommendation services are generally hosted in the cloud where users query the cloud-based model to receive recommended input such as merchandise of interest or news feed. State-of-the-art recommendation models rely on sparse and dense features to represent users' profile information and the items they interact with. Although sparse features account for 99% of the total model size, there was not enough attention paid to the potential information leakage through sparse features. These sparse features are employed to track users' behavior, e.g., their click history, object interactions, etc., potentially carrying each user's private information. Sparse features are represented as learned embedding vectors that are stored in large tables, and personalized recommendation is performed by using a specific user's sparse feature to index through the tables. Even with recently-proposed methods that hides the computation happening in the cloud, an attacker in the cloud may be able to still track the access patterns to the embedding tables. This paper explores the private information that may be learned by tracking a recommendation model's sparse feature access patterns. We first characterize the types of attacks that can be carried out on sparse features in recommendation models in an untrusted cloud, followed by a demonstration of how each of these attacks leads to extracting users' private information or tracking users by their behavior over time

Wiki, a New Wave of Innovation for Teaching and Collaborative Learning

Abstract Educational technology is a dynamic major which is ever developing. In the past, educational technology was one dimensional, but nowadays it has become multi-dimensional, flexible and learner-centered. A revolution has happened in teaching methods from the perspective of web. Novel technologies in web and new role of users' have led to the appearance of application programs on the basis of collaborative and social intelligence. Users have active participation, exploit their own beliefs, make the target concept, edit it and participate there. The most important feature of this kind of media is users' ability to participate in its content production. Users can exploit wikis in the process of educational technology. A wiki is a social medium which enables users to produce and edit constantly in an HTML environment. The aim of this article is to introduce wikis as educational and training tools. The degree to which these obstacles affect ICT users and institutes can support decision-making on how to equip them is discussed

The clinical and genetic spectrum of autosomal-recessive TOR1A-related disorders.

In the field of rare diseases, progress in molecular diagnostics led to the recognition that variants linked to autosomal-dominant neurodegenerative diseases of later onset can, in the context of biallelic inheritance, cause devastating neurodevelopmental disorders and infantile or childhood-onset neurodegeneration. TOR1A-associated arthrogryposis multiplex congenita 5 (AMC5) is a rare neurodevelopmental disorder arising from biallelic variants in TOR1A, a gene that in the heterozygous state is associated to torsion dystonia-1 (DYT1 or DYT-TOR1A), an early-onset dystonia with reduced penetrance. While 15 individuals with TOR1A-AMC5 have been reported (less than 10 in detail), a systematic investigation of the full disease-associated spectrum has not been conducted. Here, we assess the clinical, radiological and molecular characteristics of 57 individuals from 40 families with biallelic variants in TOR1A. Median age at last follow-up was 3 years (0-24 years). Most individuals presented with severe congenital flexion contractures (95%) and variable developmental delay (79%). Motor symptoms were reported in 79% and included lower limb spasticity and pyramidal signs, as well as gait disturbances. Facial dysmorphism was an integral part of the phenotype, with key features being a broad/full nasal tip, narrowing of the forehead and full cheeks. Analysis of disease-associated manifestations delineated a phenotypic spectrum ranging from normal cognition and mild gait disturbance to congenital arthrogryposis, global developmental delay, intellectual disability, absent speech and inability to walk. In a subset, the presentation was consistent with fetal akinesia deformation sequence with severe intrauterine abnormalities. Survival was 71% with higher mortality in males. Death occurred at a median age of 1.2 months (1 week - 9 years) due to respiratory failure, cardiac arrest, or sepsis. Analysis of brain MRI studies identified non-specific neuroimaging features, including a hypoplastic corpus callosum (72%), foci of signal abnormality in the subcortical and periventricular white matter (55%), diffuse white matter volume loss (45%), mega cisterna magna (36%) and arachnoid cysts (27%). The molecular spectrum included 22 distinct variants, defining a mutational hotspot in the C-terminal domain of the Torsin-1A protein. Genotype-phenotype analysis revealed an association of missense variants in the 3-helix bundle domain to an attenuated phenotype, while missense variants near the Walker A/B motif as well as biallelic truncating variants were linked to early death. In summary, this systematic cross-sectional analysis of a large cohort of individuals with biallelic TOR1A variants across a wide age-range delineates the clinical and genetic spectrum of TOR1A-related autosomal-recessive disease and highlights potential predictors for disease severity and survival

Wiki, a New Wave of Innovation for Teaching and Collaborative Learning

Educational technology is a dynamic major which is ever developing. In the past, educational technology was one dimensional, but nowadays it has become multi-dimensional, flexible and learner-centered. A revolution has happened in teaching methods from the perspective of web. Novel technologies in web and new role of users’ have led to the appearance of application programs on the basis of collaborative and social intelligence. Users have active participation, exploit their own beliefs, make the target concept, edit it and participate there. The most important feature of this kind of media is users’ ability to participate in its content production. Users can exploit wikis in the process of educational technology. A wiki is a social medium which enables users to produce and edit constantly in an HTML environment. The aim of this article is to introduce wikis as educational and training tools. The degree to which these obstacles affect ICT users and institutes can support decision-making on how to equip them is discussed

A comparative study of physical education curriculum in Iranian high schools with selected countries (USA, Germany, Australia, Japan)

The purpose of this study was to compare the physical education curriculum of Iranian high schools with some selected countries. The study adopted comparative research design, one of the qualitative methods. The countries of comparison were Japan, USA, Germany and Australia, which were selected via purposive sampling method. The data were collected from libraries, dissertations, databases, educational sites, books and publications. In the data analysis process, upon describing, interpreting and classifying the information, the curricula were compared and contrasted. The results showed that the most important goals of physical education course included promoting health, growth and development of motor skills, creating an active lifestyle. The most important contents of the physical education course were individual and social skills training, knowledge topics and sports training. Also, physical fitness tests, sports skills tests, written and oral tests and research projects were the most common evaluation methods. The sports equipment of the selected countries was standard and differed from that of Iran in terms of the number and the quality