Entanglement in smart hydrogels: fast response time, anti-freezing and anti-drying by Feng, Yuqin, Wang, Shancheng, Li, Yaqin, Ma, Wenxia, Zhang, Gang, Yang, Ming, Li, Haibo, Yang, Yongsheng, Long, Yi

“…Different from the conventional methods which hinder the movement of the polymer network, through entanglement with HPC fibers, the composite hydrogel shows both improved Young's modulus and toughness and more importantly improved smart functionalities including response speed, anti-drying, and anti-freezing capabilities and cycle stability. …”
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A novel tuning method for implementing dynamic matrix control on a water tank system by Sudarshan, Srinivasa Ramanujam.

“…Lower the value of ’k’, system performance increases and becomes faster. The novel NlStar tuning technique was found to provide the same level of performance as the Shridhar-Cooper tuning method with greater ease to tune manually.…”
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An Effective Med-VQA Method Using a Transformer with Weights Fusion of Multiple Fine-Tuned Models by Al-Hadhrami, Suheer, Menai, Mohamed El Bachir, Al-Ahmadi, Saad, Alnafessah, Ahmad

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Evaluating Adaptive Layer Freezing through Hyperparameter Optimization for Enhanced Fine-Tuning Performance of Language Models by Figueroa, Reinaldo

“…When dealing with data scarcity, transfer learning has become the go-to method to use these models in specialized downstream tasks via fine-tuning. …”
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Effect of different drying methods on retention of colour, total phenolic content, flavonoid content and antioxidant activity in Pereskia bleo leaves by Nurain Nabilah Zulkipli, Iman Nur Sabrina Norasmadi, Suhaizan Lob, Wan Zaliha Wan Sembok, Nurud Iliani Suhaimi, Aidilla Mubarak

“…The tested drying methods include shade, oven, microwave, and freeze-drying. …”
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Unsupervised bayesian generative methods by Li, Shaohua

“…Probabilistic generative models are recent development in unsupervised learning. The generative modeling framework can model rich structures and learn diverse types of relations within the data, which are usually difficult to do using traditional methods. …”
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Thermal conductivity variations with composition of gelatin-silica aerogel-sodium dodecyl sulfate with functionalized multi-walled carbon nanotube doping in their composites by Mahesh, Sachithanadam, Joshi, Sunil Chandrakant

“…This paper discusses the variations in thermal conductivity of a binder-treated gelatin silica aerogel-sodium dodecyl sulfate (GSA-SDS) composite blocks doped with COOH group functionalized multi-walled carbon nanotubes (FMWNT) prepared via freeze drying and frothing methods. The thermal conductivity of GSA-SDS and GSA-SDS/FMWNT composites was evaluated with several mass ratios of the composite mix for 1-D steady-state heat transfer at mean temperature, Tm (300-370K), using Lee’s Disc method. …”
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AI-powered COVID-19 forecasting: a comprehensive comparison of advanced deep learning methods by Tariq, Muhammad Usman, Ismail, Shuhaida

“…Methods: This study utilized a comprehensive dataset encompassing confirmed COVID-19 cases, demographic statistics, and socioeconomic indicators. …”
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AI-powered COVID-19 forecasting: a comprehensive comparison of advanced deep learning methods by Tariq, Muhammad Usman, Ismail, Shuhaida

“…Methods: This study utilized a comprehensive dataset encompassing confirmed COVID-19 cases, demographic statistics, and socioeconomic indicators. …”
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Effect of drying methods on the proximate composition of chrysomya larvae reared on trash fish / by Ling, Sheau Jing, 1990-, author 569257, Zainoha Zakaria, supervisor 566648, Naji Arafat Mahat, supervisor 569255, Fakulti Sains 8004

Effect of drying methods on the proximate composition of chrysomya larvae reared on trash fish / by Ling Sheau Jing, 1990-, author 569257

Signature methods in machine learning by Lyons, T, McLeod, A

Signature methods in machine learning by Lyons, T, McLeod, AD

Refining malware analysis with enhanced machine learning algorithms using hyperparameter tuning by El Mouhtadi, Walid, El Bakkali, Mohamed, Maleh, Yassine, Mounir, Soufyane, Ouazzane, Karim

“…The study addresses these limitations using ensemble methods and pre-processing techniques, including feature selection and hyperparameter tuning. …”
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The devil is in the details: an evaluation of recent feature encoding methods by Chatfield, K, Lempitsky, V, Vedaldi, A, Zisserman, A

“…While several authors have reported very good results on the challenging PASCAL VOC classification data by means of these new techniques, differences in the feature computation and learning algorithms, missing details in the description of the methods, and different tuning of the various components, make it impossible to compare directly these methods and hard to reproduce the results reported. …”

Machine learning and deep learning methods for exchange-traded fund trading by Jeremia, Alexander

“…Machine Learning and Deep Learning has been growing in the popularity in many fields in the past few years especially in the field of Exchange Traded Funds (ETF) due to its ability to analyse large amount of data and detect patterns that might not be oblivious to traders. …”
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Two-step machine learning enables optimized nanoparticle synthesis by Mekki-Berrada, Flore, Ren, Zekun, Huang, Tan, Wong, Wai Kuan, Zheng, Fang, Xie, Jiaxun, Tian, Isaac Parker Siyu, Jayavelu, Senthilnath, Mahfoud, Zackaria, Bash, Daniil, Hippalgaonkar, Kedar, Khan, Saif, Buonassisi, Tonio, Li, Qianxiao, Wang, Xiaonan

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Variations in the composition and biochemical attributes of Eucalyptus camaldulensis L. leaves essential oil as function of drying methods by Saleem, Misbah, Shaheen, Muhammad Ashraf, Qadir, Rahman, Saba, Iram, Rehman, Muhammad Misbah ur, Paracha, Rizwan Nasir, Ahmad, Nazir, Riaz, Muhammad, Anwar, Farooq

Physical and chemical changes of seven selected herbs used as herbal bath affected by different drying methods by Md Zuki, Rose Fazila, Ismail, Mohd Firdaus, Aziz, Julia Abdul

“…The effect of oven drying (OD) at 50±5°C, sun drying (SD), and fresh leaves (control) of seven selected herbs used in herbal preparation as herbal baths were evaluated. …”
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A comparative analysis of vitrification and two slow freezing methods for gonocyte-containing neonatal calf testicular tissue and subsequent in vitro culture by Tang, S, Jones, C, Davies, J, Lane, S, Coward, K

“…No significant differences were observed in the proportion of seminiferous tubules containing PGP9.5-positive germ cells when compared between the three methods. Comparable densities of germ cells per unit area were observed in the controlled/uncontrolled slow freezing groups, and the vitrification group (7.89 ± 1.83, 7.75 ± 1.75, and 7.92 ± 1.23/104 µm2 , respectively). …”