Hardware Accelerated Scalable Parallel Random Number Generation

The Scalable Parallel Random Number Generators library (SPRNG) is widely used due to its speed, quality, and scalability. Monte Carlo (MC) simulations often employ SPRNG to generate large quantities of random numbers. Thanks to fast Field-Programmable Gate Array (FPGA) technology development, this thesis presents Hardware Accelerated SPRNG (HASPRNG) for the Virtex-II Pro XC2VP30 FPGAs. HASPRNG includes the full set of SPRNG generators and provides programming interfaces which hide detailed internal behavior from users. HASPRNG produces identical results with SPRNG, and it is verified with over 1 million consecutive random numbers for each type of generator. The programming interface allows a developer to use HASPRNG the same way as SPRNG. HASPRNG introduces 4-70 times faster execution than the original SPRNG. This thesis describes the implementation of HASPRNG, the verification platform, the programming interface, and its performance

A case study on latency, bandwidth and energy efficiency of mobile 5G and YouTube Edge service in London. Why the 5G ecosystem and energy efficiency matter?

The advancements in 5G mobile networks and Edge computing offer great potential for services like augmented reality and Cloud gaming, thanks to their low latency and high bandwidth capabilities. However, the practical limitations of achieving optimal latency on real applications remain uncertain. This paper aims to investigate the actual latency and bandwidth provided by 5G Networks and YouTube Edge service in London, UK. We analyze how latency and bandwidth differ between 4G LTE and 5G networks and how the location of YouTube Edge servers impacts these metrics. Our research reveals over 10 significant observations and implications, indicating that the primary constraints on 4G LTE and 5G capabilities are the ecosystem and energy efficiency of mobile devices down-streaming data. Our study demonstrates that to fully unlock the potential of 5G and it's applications, it is crucial to prioritize efforts aimed at improving the ecosystem and enhancing the energy efficiency

Learning Styles and L2 Vocabulary Learning: Do Referential Preference Learners Gain More Vocabulary Than Expressive Preference Learners?

This study investigates the relationship between learning styles and second language vocabulary learning among young learners. The learning styles were operationalized in accordance with Nelson (1973), in which referential learning occurs when learners prefer to acquire a language through learning single words, whereas expressive learning happens when learners learn a language with entire phrases. After classifying students learning styles, the present study explored the relationship between learning style (referential vs. expressive) and task types (word vs. idiom) of vocabulary learning. Results indicated that while no interaction between single items was found, there was a significant interaction between referential learning and multi-word expressions (idioms) on vocabulary learning. The results suggest that the Korean students learning style was related to learning environments, including word-based lessons by school or institute in Korea.This work was supported by Hankuk University of Foreign Studies Research Fund of 2018

Capital Mobility, Financial Risk, Institutions and Redistributive Spending

As democracy spreads, the importance of redistribution policies is believed to increase, bringing with them the threat of weakening incentives and slowing growth. Yet, to date the determinants of redistribution policies have rarely been investigated outside a few OECD countries and outside the context of narrowly defined transfer payments. This paper examines the determinants of a broader class of redistribution policies, namely, the share of public spending on health, education and welfare in total government spending in a larger set of countries (a panel data set consisting of 105 countries) over the period 1988-2000. In particular, the paper views redistributive spending as emanating from two global trends: deregulation of international capital movements and the spread of democratic institutions. Our basic hypothesis is that because of the risks involved in international capital mobility and the fact that their use of standard macroeconomic policies is increasingly limited by international rules of the game, governments find redistributive spending policies convenient tools for dealing with the distributive effects inherent in these risks, especially when financial crises actually occur. The results, with both fixed and random effects models, support most of the hypotheses, several of them quite strongly

The Effects of Weight Quantization on Online Federated Learning for the IoT: A Case Study

Many weight quantization approaches were explored to save the communication bandwidth between the clients and the server in federated learning using high-end computing machines. However, there is a lack of weight quantization research for online federated learning using TinyML devices which are restricted by the mini-batch size, the neural network size, and the communication method due to their severe hardware resource constraints and power budgets. We name Tiny Online Federated Learning (TinyOFL) for online federated learning using TinyML devices in the Internet of Things (IoT). This paper performs a comprehensive analysis of the effects of weight quantization in TinyOFL in terms of accuracy, stability, overfitting, communication efficiency, energy consumption, and delivery time, and extracts practical guidelines on how to apply the weight quantization to TinyOFL. Our analysis is supported by a TinyOFL case study with three Arduino Portenta H7 boards running federated learning clients for a keyword spotting task. Our findings include that in TinyOFL, a more aggressive weight quantization can be allowed than in online learning without FL, without affecting the accuracy thanks to TinyOFL’s quasi-batch training property. For example, using 7-bit weights achieved the equivalent accuracy to 32-bit floating point weights, while saving communication bandwidth by 4.6× . Overfitting by increasing network width rarely occurs in TinyOFL, but may occur if strong weight quantization is applied. The experiments also showed that there is a design space for TinyOFL applications by compensating for the accuracy loss due to weight quantization with an increase of the neural network size

Effects of heat stress on conception in Holstein and Jersey cattle and oocyte maturation in vitro

Korea, located in East Asia in the northern hemisphere, is experiencing severe climate changes. Specifically, the heat stress caused by global warming is negatively affecting the dairy sector, including milk production and reproductive performance, as the major dairy cattle Holstein-Friesian is particularly susceptible to heat stress. Here, we collected artificial insemination and pregnancy data of the Holstein and the Jersey cows from a dairy farm from 2014 to 2021 and analyzed the association between the conception rate and the temperature-humidity index, calculated using the data from the closest official weather station. As the temperature-humidity index threshold increased, the conception rate gradually decreased. However, this decrease was steeper in the Holstein breed than in the Jersey one at a temperature-humidity index threshold of 75. To evaluate the effects of heat stress on the oocyte quality, we examined the nuclear and cytoplasmic maturation of Holstein (n = 158, obtained from six animals) and Jersey oocytes (n = 123, obtained from six animals), obtained by ovum pick-up. There were no differences in the nuclear maturation between the different conditions (heat stress: 40.5°C, non- heat stress: 37.5°C) or breeds, although the Holstein oocytes seemed to have a lower metaphase II development (p = 0.0521) after in vitro maturation under heat stress conditions. However, we found that the Holstein metaphase II oocytes exposed to heat stress presented more reactive oxygen species and a peripheral distribution of the mitochondria, compared to those of the Jersey cattle. Here, we show that weather information from local meteorological stations can be used to calculate the temperature-humidity index threshold at which heat stress influences the conception rate, and that the Jersey cows are more tolerant to heat stress in terms of their conception rate at a temperature-humidity index over 75. The lower fertility of the Holstein cows is likely attributed to impaired cytoplasmic maturation induced by heat stress. Thus, the Jersey cows can be a good breed for the sustainability of dairy farms for addressing climate changes in South Korea, as they are more resistant to hyperthermia

Using contextual information in learners’ spoken language communication: an eye-tracking study

The efficiency of oral communication can vary depending on how quickly language users process not only language but also non-language information and on how that information is used. Various psycholinguistic experiments have shown that first language (L1) users incrementally form a representation by utilizing context information, and furthermore, can predict the forthcoming information. Since this topic has not been sufficiently studied using second language (L2) learners, theory and application of L2 processing are thus insufficient. This study aims to investigate, using an eye-tracking experiment, whether EFL learners can utilize visually presented contextual information during spoken language comprehension. Specifically, it eye tracked the comprehension processes of EFL learners when auditory inputs with four two-dimensional figures (e.g. Where is the large red circle?)were presented. Twenty-four learners with advanced English proficiency were asked to eye-spot figures corresponding to auditory inputs. Two conditions were manipulated in terms of figure size, color, and shape: (1) one pair of contrasting objects and; (2) two pairs of contrasting objects. It was revealed that the eye often moved to the target object before the noun (e.g. circle) was heard, adjectival information (e.g. large, red) being sufficient to restrict the domain of reference to one object in the visual display. Eye movements were thus quicker in the first condition that requires relatively little context information to distinguish the target than in the second condition that does not. The findings suggest that the subjects utilized real-time contextual information and top-down processing strategy of linguistic information in terms of Paul Grice‘s maxim of quantity

Submodel Decomposition for Solving Limited Memory Influence Diagrams (Student Abstract)

This paper presents a systematic way of decomposing a limited memory influence diagram (LIMID) to a tree of single-stage decision problems, or submodels and solving it by message passing. The relevance in LIMIDs is formalized by the notion of the partial evaluation of the maximum expected utility, and the graph separation criteria for identifying submodels follow. The submodel decomposition provides a graphical model approach for updating the beliefs and propagating the conditional expected utilities for solving LIMIDs with the worst-case complexity bounded by the maximum treewidth of the individual submodels

Korean Resultative Constructions

This paper aims to investigate the typology of resultative constructions (henceforth RC) in Korean, to provide their relevant constraints and finally to propose formal structures of RCs in a unified wa