Hasil untuk "Technology"

B. Jiang, Jingtang Zheng, Shi Qiu et al.

D. McKnight, Michelle Carter, J. Thatcher et al.

T. Chow

A significant amount of research and development work on the photovoltaic/thermal (PVT) technology has been done since the 1970s. Many innovative systems and products have been put forward and their quality evaluated by academics and professionals. A range of theoretical models has been introduced and their appropriateness validated by experimental data. Important design parameters are identified. Collaborations have been underway amongst institutions or countries, helping to sort out the suitable products and systems with the best marketing potential. This article gives a review of the trend of development of the technology, in particular the advancements in recent years and the future work required.

B. Drew, A R Plummer, M. Sahinkaya

G. Kennedy, T. Judd, Anna Churchward et al.

This paper reports on a study conducted in 2006 with more than 2,000 incoming first-year Australian university students. Students were asked about their access to, use of and preferences for an array of established and emerging technologies and technology based tools. The results show that many first year students are highly tech-savvy. However, when one moves beyond entrenched technologies and tools (e.g. computers, mobile phones, email), the patterns of access and use of a range of other technologies show considerable variation. The findings are discussed in light of Prensky's (2001a) notions of the 'Digital Natives' and the implications for using technology to support teaching and learning in higher education.

Sarit K. Das, Stephen U. S. Choi, Wenhua Yu

A. Faghri

J. Colinge

L. Maissel, R. Glang, P. Budenstein

D. Ihde

I. Ali, V. Gupta

R. Neches, R. Fikes, Timothy W. Finin et al.

A. Laupacis, D. Feeny, A. Detsky et al.

E. H. Nicollian, J. Brews

R. Phaal, C. Farrukh, D. Probert

Yuan Wang, Norazmawati Md Sani, Jing Cai et al.

Background As aging populations continue to grow, smart home technologies—such as smart locks—have become increasingly essential to support older adults’ independent living. Long-term use remains a challenge, however, with most studies focusing on initial adoption rather than sustained engagement. Methods In this study, we examined the key factors related to older adults’ continuance intention toward smart locks, applying a socio-technical framework that integrated the Expectation-Confirmation Model of Information Systems (ECM-IS), the Task-Technology Fit (TTF) model, and external variables, including privacy and security, trust, and habit. We analyzed survey data from 422 Chinese participants aged 55 and older using Partial Least Squares Structural Equation Modeling (PLS-SEM) and Importance-Performance Matrix Analysis (IPMA). Results The model explained 71.6% of the variance in continuance intention (R2 = 0.716) and showed strong predictive relevance (Q2 = 0.623). Trust and perceived usefulness were positively related to continuance intention, followed by satisfaction. Task-technology fit and confirmation were significantly associated with perceived usefulness and satisfaction. Habit and privacy and security were not significant with respect to continuance intention. Conclusions These findings provide theoretical and practical insight for designing age-inclusive, trust-enhancing smart locks that better support older adults’ needs in post-adoption contexts.

Ifiok Udoidiok, Fuhao Li, Jielun Zhang

Machine learning (ML) has become a cornerstone of critical applications, but its vulnerability to data poisoning attacks threatens system reliability and trustworthiness. Prior studies have begun to investigate the impact of data poisoning and proposed various defense or evaluation methods; however, most efforts remain limited to quantifying performance degradation, with little systematic comparison of internal behaviors across model architectures under attack and insufficient attention to interpretability for revealing model vulnerabilities. To tackle this issue, we build a reproducible evaluation pipeline and emphasize the importance of integrating robustness with interpretability in the design of secure and trustworthy ML systems. To be specific, we propose a unified poisoning evaluation framework that systematically compares traditional ML models, deep neural networks, and large language models under three representative attack strategies including label flipping, random corruption, and adversarial insertion, at escalating severity levels of 30%, 50%, and 75%, and integrate LIME-based explanations to trace the evolution of model reasoning. Experimental results demonstrate that traditional models collapse rapidly under label noise, whereas Bayesian LSTM hybrids and large language models maintain stronger resilience. Further interpretability analysis uncovers attribution failure patterns, such as over-reliance on neutral tokens or misinterpretation of adversarial cues, providing insights beyond accuracy metrics.

WANG Jiawei(王佳薇), GONG Shuying(龚淑英), FAN Fangyuan(范方媛) et al.

Granular green tea is a significant category of famous high-quality green tea in Zhejiang Province. In this study, we conducted comparative experiments on key technical parameters, including moisture resurgence, second fixation and stir-frying techniques, during the primary processing of granular green tea and systematically analyzed their effects on sensory quality and chemical composition. The results indicated that appropriately controlling the rehumidification time (1.5 h), reducing the moisture content of the second fixed leaves (40%), decreasing the amount of tea leaves per frying pan (4 kg/pan), and selecting a frying pan with better air permeability (60-type) effectively enhanced the dry tea appearance and the emerald color of the tea liquor and improved the freshness of the aroma and taste. Moderate rehumidification and a lower moisture content in the second fixed leaves increased the content of catechins and some key umami amino acids, whereas a lower loading amount of tea leaves per frying pan increased the total amino acid content; a higher moisture content in the second fixed leaves increased the water extract content. Higher-quality samples with superior aroma and freshness had higher levels of floral compounds such as linalool, geraniol, and α-terpineol. Conversely, a longer rehumidification time, greater moisture content in the second fixed leaves, more tea leaves per frying pan, and lower air permeability of the stir-frying machine led to higher temperatures and moisture and increased the relative content of compounds such as n-hexadecanoic acid, heptanoic acid, and 6, 10, 14-trimethyl-2-pentadecanone in the aroma profile. In conclusion, this study identifies an optimal processing combination for improving the overall quality of granular green tea and provides a theoretical basis for refining its processing technology.(颗粒形绿茶是浙江省名优绿茶的重要品类。本研究针对颗粒形绿茶初制中回潮、二青、炒制等工序的关键技术参数开展对比试验，系统分析不同技术参数对颗粒形绿茶感官品质及化学组分的影响。结果表明，适当控制回潮时间（1.5 h）、降低二青叶含水率（40%）、适当减少炒制投叶量（4 kg/小锅）及选用透气性能较好的炒锅（60型），能够提升颗粒形绿茶外形及茶汤的翠绿色泽，并提高香气滋味的鲜爽性。适度回潮和较低的二青叶含水率有助于提升儿茶素含量及部分对鲜味具有重要贡献的氨基酸含量；较低的炒制投叶量可提升氨基酸总量；而较高的二青叶含水率则有利于提升水浸出物含量。在香气鲜爽性高、品质较优的样品中，芳樟醇、香叶醇、α-松油醇等具有花香特征的化合物的相对含量较高；而长时间回潮、较高的二青叶含水率、较高的炒制投叶量及较低透气性的锅型所引起的较高温度及含水率，则会促进正十六烷酸、庚酸、6，10，14-三甲基-2-十五烷酮等香气组分的积累。本研究明确了提升颗粒形绿茶综合品质的适宜工艺组合，为优化其加工技术提供了理论依据。)

Abdulrahman Alrumayh, Khaled Alhassoon, Fahd Alsaleem et al.

This paper presents a novel design of a continuum robot driven by electromagnets and springs, offering enhanced precision in multi-degree-of-freedom bending for diverse applications. Traditional continuum robots, while effective in navigating constrained environments, often face limitations in actuation methods, such as wire-based systems or pre-curved tubes. Our design overcomes these challenges by utilizing electromagnetically driven actuation, which allows each segment of the robot to bend independently at any angle, providing unprecedented flexibility and control. The technical challenges discussed emphasize the goals of this work, with the main aim being to develop a motion control system that uses electromagnets and springs to improve the accuracy and consistency of the robot’s movements. By balancing magnetic and spring forces, our system ensures predictable and stable motion in 3D space. The integration of this mechanism into multi-segmented robots opens up new possibilities in fields such as medical devices, search and rescue operations, and industrial inspection. Finite element method (FEM) simulations validate the efficiency of the proposed approach, demonstrating the precise control of the robot’s motion trajectory and enhancing its operational reliability in complex scenarios.