Mechanically stimulated motion and fatigue response of Mimosa pudica by Ong, Samuel Yong Zheng

“…Mimosa pudica is a common weed found in Singapore and its offshore islands, mainly in grassy fields or under trees and shrubs. Its compound leaves fold inward and droop when touched, shaken, or blown, only to re-open minutes later. …”
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Unbiased metabolomics of volatile secondary metabolites in essential oils originated from Myrtaceae species by Manickavasagam, Ganapaty, San, Priscilla Wong Chie, Gorji, Sara Ghorbani, Sungthong, Bunleu, Yong, Yoke Keong, Fitzgerald, Melissa, Dewi, Firli Rahmah Primula, Lim, Vuanghao

“…In this study, an untargeted metabolomic approach was applied to analyze volatile secondary metabolites in five different essential oils (i.e., anise myrtle oil, honey myrtle oil, lemon myrtle oil, lemon-scented tea tree oil, and peppermint gum oil) from the Myrtaceae family, originating from the Australian bush plants. …”
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DNA computation by Wang, Qi Wen.

“…The aim is to compare the two different algorithms in terms of complexity, performance and efficiency.…”
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Mean square consensus of multi-agent systems over fading networks with directed graphs by Xu, Liang, Zheng, Jianying, Xiao, Niao, Xie, Lihua

“…It is then shown that the mean square consensusability is solely determined by the edge state dynamics on a directed spanning tree. As a result, sufficient conditions are provided for mean square consensus over fading networks with directed graphs in terms of fading parameters, the network topology and the agent dynamics. …”
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Study of LIDAR mapping technology by Liu, Jing.

“…Measurements from unwanted features and objects such as trees, vehicles should be classified and removed so as to generate a DTM. …”
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Real-time visual object classification for augmented reality by Xu, Haoran

“…The study on the deep CNN models has experienced great success in terms of image classification tasks. Considering the users’ requirements on object of interest may keep changing, the image classification models for an AR application are required to keep updating and retraining. …”
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Tiny Pointers by Bender, Michael, Conway, Alex, Farach-Colton, Martin, Kuszmaul, William, Tagliavini, Guido

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Machine learning techniques for building predictive maintenance: a review by Adhikari, Aravinda, Karunaratne, Tharindu, Sumanarathna, Nipuni

“…Results: The results show a distinct relationship between the two terms, yet co-author analysis reveals a lack of global collaboration among authors. …”
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A performance analysis of prediction techniques in handling high-dimensional uncertain data for the application of skyline query over data stream by Ahmed Mohamud, Mudathir, Ibrahim, Hamidah, Sidi, Fatimah, Mohd Rum, Siti Nurulain, Dzolkhifli, Zarina, Xiaowei, Zhang

“…Given this, the following techniques are selected - Linear Regression (LR), k-Nearest Neighbour (k-NN), Random Forest (RF), Decision Trees (DT), and Centre and Range Method (CRM) and their effectiveness is evaluated in terms of execution time, precision, recall, F1-score, and root mean square error (RMSE). …”
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A generalized stereotypical trust model by Fang, Hui, Zhang, Jie, Sensoy, Murat, Thalmann, Nadia Magnenat

“…We then propose a fuzzy semantic decision tree (FSDT) learning method to construct trust stereotypes that generalizes over seller non-nominal attributes by splitting their values in a fuzzy manner, and generalizes over nominal attributes by replacing their specific values with more general terms according to the ontology. …”
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Specification and Planning of UAV Missions: A Process Algebra Approach by Karaman, Sertac, Rasmussen, Steven, Kingston, Derek, Frazzoli, Emilio

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Machine learning attack on hardware implementation of one-way function by Lauw, Andri Renardi

“…It turns out that Support Vector Machine (SVM) is the most effective learning algorithm among all the six algorithms tested (Naïve Bayes, Decision Tree, Logistic Regression, Gradient Boosting, Neural Network, and SVM) to attack the PUF in terms of effectiveness and efficiency, which has prediction accuracy of 99% with relatively small amount of training data. …”
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Automated breast masses segmentation in digitized mammograms by Zhang, Han, Foo, Say Wei, Thng, Choon Hua, Krishnan, Shankar M.

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Fog-based pub/sub index with Boolean expressions in the internet of industrial vehicles by Li, Yanhong, Zhang, Wang, Zhu, Rongbo, Li, Guohui, Ma, Maode, Shu, Lihchyun, Luo, Changyin

“…Simulation results show that RnetBE and the proposed algorithm are efficient in terms of memory consumption and matching time.…”
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RoboGrammar: Graph Grammar for Terrain-Optimized Robot Design by Zhao, Allan, Xu, Jie, Konakovic-Lukovic, Mina, Hughes, Josephine, Spielberg, Andrew, Rus, Daniela, Matusik, Wojciech

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A New Formulation for Optimising Coal Procurement in Power Generation by Ibrahim, Jafni Azhan, Hashim, Amir

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Tissue-specific study across the stem reveals the chemistry and transcriptome dynamics of birch bark by Alonso-Serra, Juan, Safronov, Omid, Lim, Kean-Jin, Fraser-Miller, Sara J., Blokhina, Olga B., Campilho, Ana, Chong, Sun-Li, Fagerstedt, Kurt, Haavikko, Raisa, Helariutta, Ykä, Immanen, Juha, Kangasjärvi, Jaakko, Kauppila, Tiina J., Lehtonen, Mari, Ragni, Laura, Rajaraman, Sitaram, Räsänen, Riikka-Marjaana, Safdari, Pezhman, Tenkanen, Maija, Yli-Kauhaluoma, Jari T., Teeri, Teemu H., Strachan, Clare J., Nieminen, Kaisa, Salojärvi, Jarkko

“…Tree bark is a highly specialized array of tissues that plays important roles in plant protection and development. …”
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Comprehensive analysis of feature extraction methods for emotion recognition from multichannel EEG recordings by Yuvaraj, Rajamanickam, Thagavel, Prasanth, Thomas, John, Fogarty, Jack, Ali, Farhan

“…Performance was evaluated using two classifier methods, support vector machine (SVM) and classification and regression tree (CART), across five independent and publicly available datasets linking EEG to emotional states: MAHNOB-HCI, DEAP, SEED, AMIGOS, and DREAMER. …”
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Recognition of human activities using a multiclass relevance vector machine by He, Weihua, Yow, Kin Choong, Guo, Yongcai

“…In summary, the mRVM, especially the mRVM2, has advantages both in terms of recognition rate and sparsity, along with a simple feature extraction process. …”
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Dynamic traffic safety risk assessment in road tunnel entrance zone based on drivers' psychophysiological perception states: methodology and case-study insights by Niu, Jia'an, Liang, Bo, Wong, Yiik Diew, He, Shiyong, Qin, Can, Wen, Sen

“…Second, a Traffic Safety Risk Value (TSRV) is quantified in terms of the difference in safe speeds and a traffic safety risk model that is established for the tunnel entrance zone. …”
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