Design of path planning robot simulator by applying sampling based method by Heru Suwoyo, Julpri Andika, Andi Adriansyah

“…The level of computational efficiency, path optimality, and the ability to adapt to variant environments are some of the issues that still arise, although these techniques have shown good results in many cases. …”
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Family-to-Work Facilitation, Sex, and Gender: A Sample of University Employees by Selda Coşkuner Aktaş, Birgül Çiçek

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Prevalence of decreased olfactory function in adults in a Brazilian population sample by Wilker Antunes Lira, Gilmar Felisberto Junior, Marco Aurélio Fornazieri, Wilma Terezinha Anselmo Lima, Ingrid Werner Picinini, Vanessa Ramos Pires Dinarte

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Sample Size in Multilevel Structural Equation Modeling - the Monte Carlo Approach by Adam Sagan

“…In the process of sample selection, an important issue is the relationship between sample size and the type and complexity of the statistical model, which is the basis for testing research hypotheses. …”
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Adaptive Ensemble Framework With Synthetic Sampling for Tackling Class Imbalance Problem by R. Sasirekha, B. Kanisha

“…ASEB integrates Adaptive Synthetic Sampling (ADASYN) and Generative Adversarial Networks (GANs) for synthetic sample generation, dynamic class weighting, and ensemble learning strategies. …”
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Adaptive Multi-Gradient Guidance with Conflict Resolution for Limited-Sample Regression by Yu Lin, Jiaxiang Lin, Keju Zhang, Qin Zheng, Liqiang Lin, Qianqian Chen

“…Recent studies report that gradient guidance extracted from a single-reference model can improve Limited-Sample regression. However, one reference model may not capture all relevant characteristics of the target function, which can restrict the capacity of the learner. …”
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Attitude Towards Marketing Surveys: The Comparison of Student and Non-Student Samples by Ufuk Pala, Kalender Özcan Atılgan

“…Using student samples in marketing research is a debated issue. …”
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Identification of the Oscillation Period of Chemical Reactors by Chaotic Sampling of the Conversion Degree by Lawnik Marcin, Berezowski Marek

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Human density and sampling time explain richness of anurans in the brazilian biomes by Arielson dos Santos Protázio, Lennise Costa Conceição, Airan dos Santos Protázio

“…However, investigations on this issue have focused on the influence of abiotic factors without considering the joint effect of many existing variables, including the data sampling methodology and human demography. …”
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An Adaptive Sampling Algorithm for Target Tracking in Underwater Wireless Sensor Networks by Yanlong Sun, Yazhou Yuan, Xiaolei Li, Qimin Xu, Xinping Guan

“…In this paper, we propose an adaptive sampling algorithm for target tracking in UWSNs to address this issue. …”
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Non-specific TVLA method based on two-sample KS test by Zhen ZHENG, Yingjian YAN, Juesong CAI, Yanjiang LIU

“…Test vector leakage assessment (TVLA) is prone to “false negative” when the power consumption sample size is small.To address this issue, it was found that for non-specific TVLA, when the power consumption sample size changes, the test statistic t-values obtained at the leakage sampling points in the power trace vary accordingly, while the t-values at the non-leakage sampling points do not significantly vary.Therefore, when there is leakage, the distributions of the t-values obtained under different sample sizes will be different.Based on this, it was proposed to implement non-specific TVLA under different sample sizes and perform two-sample KS test on the obtained t-value sequences to evaluate whether there was leakage.Verifications were carried out based on unprotected-aligned simulation power consumption, protected-aligned power consumption dataset DPA Contest v4_2 and protected-non-aligned self-collected power consumption respectively.The results showed that the sample size required by the proposed method on the aligned simulation power consumption and DPA Contest v4_2 was reduced by at most 46.1% and 39.0% respectively.And after the alignment, the required sample size of the proposed method on the self-collected power consumption is also smaller than that of other schemes, with a maximum reduction of 29.4%.Therefore, the proposed method can effectively reduce the probability of “false negative” when the power consumption sample size is small.…”
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An interpretable approach for trustworthy intrusion detection systems against evasion samples by Ngoc Tai Nguyen, Hien Do Hoang, The Duy Phan, Van-Hau Pham

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Machine learning-based single-sample molecular classifier for cancer grading by Zoia Antysheva, Nikita Kotlov, Mariia V. Guryleva, Ivan Valiev, Viktor Svekolkin, Anna Belozerova, Sheila T. Yong, Dmitry Tabakov, Alexander Bagaev, Vladimir Kushnarev

“…Next, we showed that mGrades were effective in assessing risk levels for G2 samples. Finally, we identified common and unique biological and genetic features in samples of low and high mGrades across breast, lung, and renal cancers. …”
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An interpretable approach for trustworthy intrusion detection systems against evasion samples by Ngoc Tai Nguyen, Hien Do Hoang, The Duy Phan, Van-Hau Pham

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Exploring the Perceptions of EFL Learners on Ambiguity Tolerance: Sakarya University Sample by Orhan Kocaman, Melek Pamukoğlu

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NORM in soil and sludge samples in Dukhan oil Field, Qatar state by mohammad mohammad hushari

“…Recently NORM subjected to restricted regulation issued by high legal authority at Qatar state. Twenty five samples of soil from Dukhan onshore oil field and 10 sludge samples collected from 2 offshore fields at Qatar state. …”
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Sample Inflation Interpolation for Consistency Regularization in Remote Sensing Change Detection by Zuo Jiang, Haobo Chen, Yi Tang

“…However, while these methods enhance noise robustness, they also risk overlooking subtle but meaningful changes, leading to information loss and missed detections. To address this issue, we introduce a simple yet efficient method called Sample Inflation Interpolation (SII). …”
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Enhanced Helicopter Vibration Prediction With Hybrid Sampling and Cost Mining Techniques by Jeonghun Kim, Keunho Choi, Donghee Yoo

“…To address these challenges, this study develops a machine learning-based prediction model using vibration test data from the cockpit of a Korean utility helicopter. To mitigate the issue of class imbalance in the dataset, two hybrid sampling techniques are proposed and analyzed: first oversampling and last undersampling (FOLU) and first undersampling and last oversampling (FULO). …”
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Collaborative Filtering Recommendation-Based Random Negative Sampling and Graph Attention by Weiqiang Li, Xianghui Li, Xiaowen Liu, Xinhuan Chen, Ming Ma

“…To address this issue, this paper proposes a collaborative filtering recommendation based on random negative sampling and graph attention (NGACF). …”
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Characterization of sleep apnea among a sample of adults from Samoa by Lacey W. Heinsberg, Alysa Pomer, Brian E. Cade, Jenna C. Carlson, Take Naseri, Muagututia Sefuiva Reupena, Satupa'itea Viali, Daniel E. Weeks, Stephen T. McGarvey, Susan Redline, Nicola L. Hawley

“…Sleep apnea is a global public health concern, but little research has examined this issue in low- and middle-income countries, including Samoa. …”
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