3,444 research outputs found
A Development of Motivation Scale of Sport Website Users: A Perspective of Motivation Factors on Attitude and Behavioral Intention
Efficient and Privacy Preserving Group Signature for Federated Learning
Federated Learning (FL) is a Machine Learning (ML) technique that aims to
reduce the threats to user data privacy. Training is done using the raw data on
the users' device, called clients, and only the training results, called
gradients, are sent to the server to be aggregated and generate an updated
model. However, we cannot assume that the server can be trusted with private
information, such as metadata related to the owner or source of the data. So,
hiding the client information from the server helps reduce privacy-related
attacks. Therefore, the privacy of the client's identity, along with the
privacy of the client's data, is necessary to make such attacks more difficult.
This paper proposes an efficient and privacy-preserving protocol for FL based
on group signature. A new group signature for federated learning, called GSFL,
is designed to not only protect the privacy of the client's data and identity
but also significantly reduce the computation and communication costs
considering the iterative process of federated learning. We show that GSFL
outperforms existing approaches in terms of computation, communication, and
signaling costs. Also, we show that the proposed protocol can handle various
security attacks in the federated learning environment
Improving Multi-lingual Alignment Through Soft Contrastive Learning
Making decent multi-lingual sentence representations is critical to achieve
high performances in cross-lingual downstream tasks. In this work, we propose a
novel method to align multi-lingual embeddings based on the similarity of
sentences measured by a pre-trained mono-lingual embedding model. Given
translation sentence pairs, we train a multi-lingual model in a way that the
similarity between cross-lingual embeddings follows the similarity of sentences
measured at the mono-lingual teacher model. Our method can be considered as
contrastive learning with soft labels defined as the similarity between
sentences. Our experimental results on five languages show that our contrastive
loss with soft labels far outperforms conventional contrastive loss with hard
labels in various benchmarks for bitext mining tasks and STS tasks. In
addition, our method outperforms existing multi-lingual embeddings including
LaBSE, for Tatoeba dataset. The code is available at
https://github.com/YAI12xLinq-B/IMASCLComment: 8 pages, 1 figures, Accepted at NAACL SRW 202
Changes in bone mineral density and trabecular bone score in Graves' disease patients after anti-thyroid therapy
AbstractObjectiveThe purpose of this study was to evaluate changes in bone quantity based on bone mineral density (BMD) and bone quality based on trabecular bone score (TBS) in Graves' disease patients after anti-thyroid therapy.Research design and methodThis retrospective study included premenopausal female and male patients with Graves' disease who received BMD measurement more than two times during treatment. BMD and thyroid function tests with free thyroxine (FT4), total triiodothyronine (T3), thyroid stimulating hormone (TSH), and TSH receptor antibody (TRAb) levels were collected two times during follow-up. TBS was calculated using TBS insight® software (version 2.1) from dual-energy X-ray absorptiometry images.ResultsThirty Graves' disease patients (17 males, 56%; 13 premenopausal females, 44%) with a mean age of 35.3 ± 9.9 years were included. The mean follow-up period was 20.7 ± 8.5 months. The median levels of FT4, TSH and TRAb improved at follow-up [2.55 ng/dL (Interquartile range (IQR) 2.07–3.78) to 1.28 ng/dL (IQR 1.23–1.39), 0.015 mIU/L (IQR 0.01–0.04) to 0.89 mIU/L (IQR 0.35–1.55), 17.0 IU/L (IQR 5.0–40.3) to 5.0 IU/L (5.0–6.0), respectively; p < 0.001]. Median BMD (lumbar spine) values also improved from 1.118 g/cm2 (IQR 1.000–1.119) to 1.167 g/cm2 (IQR 1.050–1.219) (p = 0.001) at follow-up. TBS increased from 1.377 (IQR 1.299–1.422) to 1.390 (IQR 1.327–1.430) after treatment (p = 0.038).ConclusionBoth bone quality and density improved after anti-thyroid treatment in premenopausal female and male Graves' disease patients
Sarcopenia in Outcome in Chronic Obstructive Pulmonary Disease: Is the Tip of the Iceberg? - Authors’ Reply
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