410 research outputs found
The Australian Digital Market: Opportunities and Challenges
No full textWhile Australia was a latecomer in introducing ADSL, most Internet subscribers quickly migrated from dial-up service, with 96.4% broadband connections at June 2012. The national commitment to the universal provision of high-speed broadband (speeds to 100 Mbps) is a key Government objective and is implemented through the National Broadband Network (NBN). Although in an early-deployment phase the NBN is enabling, for example, selected IT companies to receive 40 Mbps upload speeds that can support many costumers at affordable prices. Furthermore, technological advance has facilitated the development and delivery of a wide range of consumer data services and applications. In particular, broadband is commonly used for shopping, search, gaming, media entertainment and social networking. Consumers are purchasing goods and services online, with shoppers increasingly using smartphones for this purpose. Also, the use of tablets and Internet-enabled mobile phones is popular and is facilitating mobile commerce and fundamentally changing the mode of business-customer interaction. This changing consumer behaviour is reshaping retail landscapes, stimulating retailers to develop digital strategies to meet customer expectations. For businesses, e-commerce provides opportunities to reduce costs and enhance sales. Indeed $189 billion of online orders were received during 2010/11. Importantly, 43% businesses report an online presence via a Website, eBay store or social media page.This digital revolution is also encouraging online service delivery and engagement by the Government. The Government recognises that online service delivery is both convenient and efficient. Examples of these developments include the Digital Local Government Program that helps communities in NBN-deployment areas to develop planning applications, consultations and reports. Another program, Tell US Once, is an ongoing initiative that aims to ensure customers only provide information once rather than repeatedly to several agencies. This chapter presents a snapshot of an increasingly dynamic Australian digital market and discusses evolving opportunities and challenges offered to consumers, businesses and the government
FIGURE 11 in Diversification in ancient Lake Biwa: integrative taxonomy reveals overlooked species diversity of the Japanese freshwater snail genus Semisulcospira (Mollusca: Semisulcospiridae)
No full textFIGURE 11 Shells of Semisulcospira salebrosa sp. nov. A–G, Holotype, KUZ Z4131. H–J, Paratype, KUZ Z4133. K–L, Paratype, KUZ Z4135. M–O, Specimen from Take-shima Island, KUZ Z4138. A–C, H, K, M, Adult shell. A–C, H, M, Female. K, Male. D, I, L, N, Operculum. E–G, J, O, Embryonic shell. Scale bars: 10 mm (A–D, H–I, K–L, M–N), 1 mm (E–G, J, O). All specimens were treated with 3% sodium hypochloritePublished as part of Sawada, Naoto & Fuke, Yusuke, 2023, Diversification in ancient Lake Biwa: integrative taxonomy reveals overlooked species diversity of the Japanese freshwater snail genus Semisulcospira (Mollusca: Semisulcospiridae), pp. 1-37 in Contributions to Zoology 92 (1) on page 22, DOI: 10.1163/18759866-BJA10035, http://zenodo.org/record/834961
FIGURE 10 in Diversification in ancient Lake Biwa: integrative taxonomy reveals overlooked species diversity of the Japanese freshwater snail genus Semisulcospira (Mollusca: Semisulcospiridae)
No full textFIGURE 10 Shells of Semisulcospira nakanoi sp. nov. A–G, Holotype, KUZ Z4122. H–J, Paratype, KUZ Z4125. K–L, Paratype, KUZ Z4126. M–Q, Specimens from Onoe Port, KUZ Z4129, Z4130. A–C, H, K, M, P, Adult shell. A–C, H, M, Female. K, P, Male. D, I, L, N, Q, Operculum. E–G, J, O, Embryonic shell. Scale bars: 10 mm (A–D, H–I, K–L, M–N, P–Q), 1 mm (E–G, J, O). All specimens were treated with 3% sodium hypochloritePublished as part of Sawada, Naoto & Fuke, Yusuke, 2023, Diversification in ancient Lake Biwa: integrative taxonomy reveals overlooked species diversity of the Japanese freshwater snail genus Semisulcospira (Mollusca: Semisulcospiridae), pp. 1-37 in Contributions to Zoology 92 (1) on page 21, DOI: 10.1163/18759866-BJA10035, http://zenodo.org/record/834961
Almost sure exponential stability of the Euler–Maruyama approximations for stochastic functional differential equations
No full textBy the continuous and discrete nonnegative semimartingale convergence theorems, this paper investigates conditions under which the Euler–Maruyama (EM) approximations of stochastic functional differential equations (SFDEs) can share the almost sure exponential stability of the exact solution. Moreover, for sufficiently small stepsize, the decay rate as measured by the Lyapunov exponent can be reproduced arbitrarily accurately
Q&A: Yi-Li Wu, Author of Reproducing Women
No full textMEC: Your book examines “medicine for women” (科 fuke) in Qing China. How did the practice of fuke then differ from present-day obstetrics and gynecology? What has changed in the Chinese understanding of women’s medicine
Efeito da incorporação de farinhas de cevada sobre as características sensoriais e de qualidade do pão de forma.
No full text
Investigating the Generalizability of Deep Learning-based Clone Detectors
No full textChoi E., Fuke N., Fujiwara Y., et al. Investigating the Generalizability of Deep Learning-based Clone Detectors. IEEE International Conference on Program Comprehension 2023-May, 181 (2023); https://doi.org/10.1109/ICPC58990.2023.00032.The generalizability of Deep Learning (DL) models is a significant challenge, as poor generalizability indicates that the model has overfitted to the training data and is not able to generalize to new data. Despite numerous DL-based clone detectors emerging in recent years, their generalizability has not been thoroughly assessed. This study investigates the generalizability of three DL-based clone detectors (CCLearner, ASTNN, and CodeBERT) by comparing their detection accuracy on different training and testing clone benchmarks. The results show that all three clone detectors do not generalize well to new data and there is a strong relationship between clone types and generalizability for CCLearner and ASTNN
Investigating the Generalizability of Deep Learning-based Clone Detectors
No full textChoi E., Fuke N., Fujiwara Y., et al. Investigating the Generalizability of Deep Learning-based Clone Detectors. IEEE International Conference on Program Comprehension 2023-May, 181 (2023); https://doi.org/10.1109/ICPC58990.2023.00032.The generalizability of Deep Learning (DL) models is a significant challenge, as poor generalizability indicates that the model has overfitted to the training data and is not able to generalize to new data. Despite numerous DL-based clone detectors emerging in recent years, their generalizability has not been thoroughly assessed. This study investigates the generalizability of three DL-based clone detectors (CCLearner, ASTNN, and CodeBERT) by comparing their detection accuracy on different training and testing clone benchmarks. The results show that all three clone detectors do not generalize well to new data and there is a strong relationship between clone types and generalizability for CCLearner and ASTNN
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