Communication-Efficient Federated Learning over Capacity-Limited Wireless Networks

In this paper, a communication-efficient federated learning (FL) framework is proposed for improving the convergence rate of FL under a limited uplink capacity. The central idea of the proposed framework is to transmit the values and positions of the top-$S$ entries of a local model update for uplink transmission. A lossless encoding technique is considered for transmitting the positions of these entries, while a linear transformation followed by the Lloyd-Max scalar quantization is considered for transmitting their values. For an accurate reconstruction of the top-$S$ values, a linear minimum mean squared error method is developed based on the Bussgang decomposition. Moreover, an error feedback strategy is introduced to compensate for both compression and reconstruction errors. The convergence rate of the proposed framework is analyzed for a non-convex loss function with consideration of the compression and reconstruction errors. From the analytical result, the key parameters of the proposed framework are optimized for maximizing the convergence rate for the given capacity. Simulation results on the MNIST and CIFAR-10 datasets demonstrate that the proposed framework outperforms state-of-the-art FL frameworks in terms of classification accuracy under the limited uplink capacity

A Neural Pre-Conditioning Active Learning Algorithm to Reduce Label Complexity

Deep learning (DL) algorithms rely on massive amounts of labeled data. Semi-supervised learning (SSL) and active learning (AL) aim to reduce this label complexity by leveraging unlabeled data or carefully acquiring labels, respectively. In this work, we primarily focus on designing an AL algorithm but first argue for a change in how AL algorithms should be evaluated. Although unlabeled data is readily available in pool-based AL, AL algorithms are usually evaluated by measuring the increase in supervised learning (SL) performance at consecutive acquisition steps. Because this measures performance gains from both newly acquired instances and newly acquired labels, we propose to instead evaluate the label efficiency of AL algorithms by measuring the increase in SSL performance at consecutive acquisition steps. After surveying tools that can be used to this end, we propose our neural pre-conditioning (NPC) algorithm inspired by a Neural Tangent Kernel (NTK) analysis. Our algorithm incorporates the classifier's uncertainty on unlabeled data and penalizes redundant samples within candidate batches to efficiently acquire a diverse set of informative labels. Furthermore, we prove that NPC improves downstream training in the large-width regime in a manner previously observed to correlate with generalization. Comparisons with other AL algorithms show that a state-of-the-art SSL algorithm coupled with NPC can achieve high performance using very few labeled data.Comment: NeurIPS 202

Image display apparatus and method for operating the same

An image display apparatus and a method for operating the same are disclosed. The method for operating an image display apparatus includes receiving a 3-dimensional (3D) image, detecting the depth of the 3D image, performing 3D processing on an audio signal received in synchronization with the 3D image in correspondence with the detected depth, and outputting the audio signal subjected to 3D processing. Thus, it is possible to output the audio signal in correspondence with the depth of the 3D image during 3D image displa

Design of Single-modal Take-over Request in SAE Level 2 & 3 Automated Vehicle

Recently, cutting-edge technology has led to the development of automated vehicles, but the limitations of the related technology may lead to hazardous situations. This resulted in the remarkable significance of the interaction between automated vehicles and drivers. In particular, the transition between the driver and the automated vehicle in accordance with Level 3 of SAE J3016 is inevitable, and guidelines or standards regarding the takeover should be provided. Therefore, we aim to prepare the safety guidelines for the takeover and to conduct a comparative test. First, guidelines for visual, auditory, and haptic displays in existing vehicles were examined. Second, preliminary research was conducted on the modality of automated vehicles. Third, we carried out a modality investigation regarding the partially automated vehicle. Based on this, we proposed visual, auditory, and haptic signals for each modality. This will serve as a significant starting point for future research based on multimodal methods

SALM5 trans-synaptically interacts with LAR-RPTPs in a splicing-dependent manner to regulate synapse development

Synaptogenic adhesion molecules play critical roles in synapse formation. SALM5/Lrfn5, a SALM/Lrfn family adhesion molecule implicated in autism spectrum disorders (ASDs) and schizophrenia, induces presynaptic differentiation in contacting axons, but its presynaptic ligand remains unknown. We found that SALM5 interacts with the Ig domains of LAR family receptor protein tyrosine phosphatases (LAR-RPTPs; LAR, PTPδ, and PTPσ). These interactions are strongly inhibited by the splice insert B in the Ig domain region of LAR-RPTPs, and mediate SALM5-dependent presynaptic differentiation in contacting axons. In addition, SALM5 regulates AMPA receptor-mediated synaptic transmission through mechanisms involving the interaction of postsynaptic SALM5 with presynaptic LAR-RPTPs. These results suggest that postsynaptic SALM5 promotes synapse development by trans-synaptically interacting with presynaptic LAR-RPTPs and is important for the regulation of excitatory synaptic strength

Npas4 regulates IQSEC3 expression in hippocampal somatostatin interneurons to mediate anxiety-like behavior

Activity-dependent GABAergic synapse plasticity is important for normal brain functions, but the underlying molecular mechanisms remain incompletely understood. Here, we show that Npas4 (neuronal PAS-domain protein 4) transcriptionally regulates the expression of IQSEC3, a GABAergic synapse-specific guanine nucleotide-exchange factor for ADP-ribosylation factor (ARF-GEF) that directly interacts with gephyrin. Neuronal activation by an enriched environment induces Npas4-mediated upregulation of IQSEC3 protein specifically in CA1 stratum oriens layer somatostatin (SST)-expressing GABAergic interneurons. SST+ interneuron-specific knockout (KO) of Npas4 compromises synaptic transmission in these GABAergic interneurons, increases neuronal activity in CA1 pyramidal neurons, and reduces anxiety behavior, all of which are normalized by the expression of wild-type IQSEC3, but not a dominant-negative ARF-GEF-inactive mutant, in SST+ interneurons of Npas4-KO mice. Our results suggest that IQSEC3 is a key GABAergic synapse component that is directed by Npas4 and ARF activity, specifically in SST+ interneurons, to orchestrate excitation-to-inhibition balance and control anxiety-like behavior.1

LRRTM3 Regulates Excitatory Synapse Development through Alternative Splicing and Neurexin Binding

The four members of the LRRTM family (LRRTM1-4) are postsynaptic adhesion molecules essential for excitatory synapse development. They have also been implicated in neuropsychiatric diseases. Here, we focus on LRRTM3, showing that two distinct LRRTM3 variants generated by alternative splicing regulate LRRTM3 interaction with PSD-95, but not its excitatory synapse-promoting activity. Overexpression of either LRRTM3 variant increased excitatory synapse density in dentate gyrus (DG) granule neurons, whereas LRRTM3 knockdown decreased it. LRRTM3 also controlled activity-regulated AMPA receptor surface expression in an alternative splicing-dependent manner. Furthermore, Lrrtm3-knockout mice displayed specific alterations in excitatory synapse density, excitatory synaptic transmission and excitability in DG granule neurons but not in CA1 pyramidal neurons. Lastly, LRRTM3 required only specific splice variants of presynaptic neurexins for their synaptogenic activity. Collectively, our data highlight alternative splicing and differential presynaptic ligand utilization in the regulation of LRRTMs, revealing key regulatory mechanisms for excitatory synapse development.Peer reviewe

The time course of the analgesic effect of acupuncture in the treatment of lateral epicondylalgia : a randomized controlled feasibility trial comparing standard acupuncture and electroacupuncture

Background: Resistance exercise is effective in relieving pain and improving grip strength in patients with lateral epicondylalgia (LE). However, patients’ activity-related pain can hinder their active participation in an exercise program. Acupuncture, particularly electro-acupuncture (EA), may be an effective complementary modality for pain control in order to promote patients’ participation in an exercise program and further to enhance therapeutic effects. Objectives: 1) assess the feasibility of a study designed to compare the effect size of analgesia induced by EA vs. standard acupuncture (SA); 2) estimate the time course of the analgesic effect of EA and SA for patients with LE; and 3) investigate if the analgesic effect of either intervention is associated with a change in pain-free grip strength. Methods: A double-blind, parallel-group randomized controlled feasibility trial was conducted at a research centre located in Vancouver, Canada. Twenty-one participants with unilateral LE lasting more than 6 weeks duration were enrolled in the study. The participants were randomly allocated to receive a single treatment of either EA (10-30 Hz) or SA. The primary outcome measure was pain-free grip strength, and the secondary outcome measures included the severity of lateral elbow pain (numeric rating scale), and patients’ global rating of change. Outcomes were measured over a 72-hour period. Results: No significant differences in outcome measures were found between the two treatment groups at any time point. A pattern of gradual improvement of pain-free grip strength (approximately 12N /day) over the 72-hour monitoring period in both treatment groups was observed, and this improvement was statistically significant compared to baseline at the 72-hour time point (38 ± 13N). In contrast, there was a statistically significant reduction in patients’ perceived pain level immediately after either treatment, and this improvement was maintained throughout the 72-hour follow-up period (-0.99~-1.59 ± 0.35). After 24 hours, 5% of patients reported themselves as feeling ‘much better’, 55% ‘slightly better’, 15% ‘unchanged’, 10% ‘slightly worse’, 10% ‘moderately worse’ and 5% ‘much worse’. Conclusion: Acupuncture may complement the therapeutic effect of rehabilitation exercise program as it provides immediate pain relief for patients with chronic LE. Trial registration: ISRCTN14667535 Funding: noneMedicine, Faculty ofGraduat

Distributed Blockchain-Based Message Authentication Scheme for Connected Vehicles

Vehicular ad-hoc networks (VANETs) have several security issues such as privacy preservation, secure authentication, and system reliability. In the VANET, a vehicle communicates with other vehicles or infrastructures using broadcasting messages. These messages contain not only normal traffic information, but also identification information of sender. In general, the identification information remains encrypted to ensure privacy. However, the conventional centralized system can decrypt the identification information using private information of the sender vehicle. As a result, the central server can often be targeted by adversaries. We propose a message authentication scheme for anonymity and decentralization of information using blockchain technology. Here, we introduce public-private key and message authentication code (MAC) for secure authentication. In this paper, we adopt consensus algorithms for composing blockchain system such as the proof of work (PoW) and Practical Byzantine Fault Tolerance (PBFT) into the proposed authentication process. Finally, we demonstrate that the proposed method is secure from the attacks which include impersonation from internal attacker as well as typical attacks