A Syllable-based Technique for Word Embeddings of Korean Words

Word embedding has become a fundamental component to many NLP tasks such as named entity recognition and machine translation. However, popular models that learn such embeddings are unaware of the morphology of words, so it is not directly applicable to highly agglutinative languages such as Korean. We propose a syllable-based learning model for Korean using a convolutional neural network, in which word representation is composed of trained syllable vectors. Our model successfully produces morphologically meaningful representation of Korean words compared to the original Skip-gram embeddings. The results also show that it is quite robust to the Out-of-Vocabulary problem.Comment: 5 pages, 3 figures, 1 table. Accepted for EMNLP 2017 Workshop - The 1st Workshop on Subword and Character level models in NLP (SCLeM

FedFwd: Federated Learning without Backpropagation

In federated learning (FL), clients with limited resources can disrupt the training efficiency. A potential solution to this problem is to leverage a new learning procedure that does not rely on backpropagation (BP). We present a novel approach to FL called FedFwd that employs a recent BP-free method by Hinton (2022), namely the Forward Forward algorithm, in the local training process. FedFwd can reduce a significant amount of computations for updating parameters by performing layer-wise local updates, and therefore, there is no need to store all intermediate activation values during training. We conduct various experiments to evaluate FedFwd on standard datasets including MNIST and CIFAR-10, and show that it works competitively to other BP-dependent FL methods.Comment: ICML 2023 Workshop (Federated Learning and Analytics in Practice: Algorithms, Systems, Applications, and Opportunities

Unified Modeling and Rate Coverage Analysis for Satellite-Terrestrial Integrated Networks: Coverage Extension or Data Offloading?

With the growing interest in satellite networks, satellite-terrestrial integrated networks (STINs) have gained significant attention because of their potential benefits. However, due to the lack of a tractable network model for the STIN architecture, analytical studies allowing one to investigate the performance of such networks are not yet available. In this work, we propose a unified network model that jointly captures satellite and terrestrial networks into one analytical framework. Our key idea is based on Poisson point processes distributed on concentric spheres, assigning a random height to each point as a mark. This allows one to consider each point as a source of desired signal or a source of interference while ensuring visibility to the typical user. Thanks to this model, we derive the probability of coverage of STINs as a function of major system parameters, chiefly path-loss exponent, satellites and terrestrial base stations' height distributions and density, transmit power and biasing factors. Leveraging the analysis, we concretely explore two benefits that STINs provide: i) coverage extension in remote rural areas and ii) data offloading in dense urban areas.Comment: submitted to IEEE journa

Dyadic profiles of parental disciplinary behavior and links with parenting context

Using data from couples (N ¼ 1,195) who participated in a large community-based study of families, we used maternal reports of parental discipline to examine mothers’ and fathers’ use of and patterns related to aggressive and nonviolent discipline of their 3- year-old child. First, we separately examined mothers’ and fathers’ patterns, or classes, of disciplinary behaviors. Second, we identified joint mother–father class profiles. Maternal reports indicated that the patterns among fathers and mothers were similar, but fathers were more likely to be in the low-aggression classes than mothers; and mothers were more likely to be in the highaggression classes than fathers. Dyads in which both parents employed high levels of aggressive discipline were characterized by higher parenting stress, poorer parental relationship, and lower quality community context. The majority (81.2%) of dyads used congruent disciplinary behaviors. Discordant dyads were similar to dyads in which both parents were high in aggressive discipline, in that these groups had children with the highest levels of aggressive behavior. Implications highlight the need to target both mothers and fathers with parent education efforts to reinforce positive parenting.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/120636/1/2014 Kim Lee et al Child Maltreatment.pd

An Experimental Investigation of Cavitation Bulk Nanobubbles Characteristics: Effects of pH and Surface-active Agents

Understanding the behavior of nanobubbles (NBs) in various aqueous solutions is a challenging task. The present work investigates the effects of various surfactants (i.e., anionic, cationic, and nonionic) and pH medium on bulk NBs formation, size, concentration, bubble size distribution (BSD), zeta potential, and stability. The effect of surfactant was investigated at various concentrations above and below critical micelle concentrations. NBs were created in DI water using a piezoelectric transducer. The stability of NBs was assessed by tracking the change in size and concentration over time. NBs size is small in the neutral medium compared to the other surfactant or pH mediums. The size, concentration, BSD, and stability of NBs are strongly influenced by the zeta potential rather than the solution medium. BSD curve shifts to lower bubble sizes when the magnitude of zeta potential is high in any solution. NBs were observed to exist for a long time, either in pure water, surfactant, or pH solutions. The longevity of NBs is shortened in environments with pH less than 3. Surfactant adsorption on the NBs surface increases with surfactant concentration up to a certain limit, beyond which it declines considerably. The Derjaguin-LandauVerwey-Overbeek (DLVO) theory was used to interpret the NBs stability, which resulted in a total potential energy barrier that is positive and greater than 43.90kBT for pH ranging from 6.0 to 11.0, whereas, for pH below 6, the potential energy barrier essentially vanishes. Moreover, an effort has also been made to elucidate the plausible prospect of ion distribution and its alignment surrounding NBs in cationic and anionic surfactants. The present research will extend the in-depth investigation of NBs for industrial applications involving NBs

Energy Efficiency Maximization Precoding for Quantized Massive MIMO Systems

The use of low-resolution digital-to-analog and analog-to-digital converters (DACs and ADCs) significantly benefits energy efficiency (EE) at the cost of high quantization noise for massive multiple-input multiple-output (MIMO) systems. This paper considers a precoding optimization problem for maximizing EE in quantized downlink massive MIMO systems. To this end, we jointly optimize an active antenna set, precoding vectors, and allocated power; yet acquiring such joint optimal solution is challenging. To resolve this challenge, we decompose the problem into precoding direction and power optimization problems. For precoding direction, we characterize the first-order optimality condition, which entails the effects of quantization distortion and antenna selection. We cast the derived condition as a functional eigenvalue problem, wherein finding the principal eigenvector attains the best local optimal point. To this end, we propose generalized power iteration based algorithm. To optimize precoding power for given precoding direction, we adopt a gradient descent algorithm for the EE maximization. Alternating these two methods, our algorithm identifies a joint solution of the active antenna set, the precoding direction, and allocated power. In simulations, the proposed methods provide considerable performance gains. Our results suggest that a few-bit DACs are sufficient for achieving high EE in massive MIMO systems

Turbine Bearing Housing Fire Accident Due To hydrogen inflow into nitrogen line of dry gas seal

Case StudyFire incidents occurred in the turbine bearing housing at every start-upsince the original wet type seal in the compressor was replaced with a dry gas seal(DGS). The first investigation focused on leakage of the lube oil in the turbinebearing housing. However, despite various measures, the fires continued to occur.• After repeated attempts to find a root cause, it was realized there were incorrectoperation procedures and valve passing problem in the DGS, and which causedhydrogen inflow into the nitrogen line(separation gas) of the compressor DGSand finally migration into turbine bearing housing.This case study details the root cause analysis results and the countermeasures

Sensorless Control of Surface-Mount Permanent-Magnet Synchronous Motors Based on a Nonlinear Observer

International audienceA nonlinear observer for surface-mount permanent-magnet synchronous motors (SPMSMs) was recently proposed by Ortega et al.(LSS, Gif-sur-Yvette Cedex, France, LSS Internal Rep., Jan. 2009). The nonlinear observer generates the position estimate hat(theta) via the estimates of sin theta and cos theta. In contrast to Luenberger-type observers, it does not require speed information, thus eliminating the complexity associated with speed estimation errors. Further, it is simple to implement. In this study, the nonlinear observer performance is verified experimentally. To obtain speed estimates from the position information, a proportional-integral (PI) tracking controller speed estimator was utilized. The results are good with and without loads, above 10 r/min