A Background Jitter Calibration for ADCs Using TDC Phase Information From ADPLL by Haoyang Shen, Hao Zheng, Daniel O'Hare, Deepu John, Barry Cardiff

“…This paper addresses this issue within the context of a Time-to-Digital Converter (TDC)-based All-Digital Phase-Locked Loop (ADPLL) responsible for generating the sampling clock for ADCs. …”
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How to Perform a Postgraduate Research and Write a Scientific Paper: The Underpinning Facts! by Mohanchandra Mandal, Soma Chakraborty, Debojyoti Das, Suman Chattopadhyay, Suchitra Pal

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FHQ-RRT*: An Improved Path Planning Algorithm for Mobile Robots to Acquire High-Quality Paths Faster by Xingxiang Dong, Yujun Wang, Can Fang, Kemeng Ran, Guohui Liu

“…The proposed algorithm enhances the exploration efficiency and path quality of mobile robots through three key innovations: First, a dynamic sparse sampling strategy that adaptively adjusts the sampling density according to the growth rate of the random tree, thereby increasing the algorithm’s growth speed while maintaining adaptability to complex environments. …”
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HEAVY CONCENTRATE GOLD ASSOCIATIONS IN THE BASIN OF THE KUKULKINDZHA CREEK (OKHOTSK REGION OF THE KHABAROVSK KRAI) by A.Ya. Nefedova, I.K. Kotova, М.А. Pavlova, D.I. Smirnov, D.А. Guskov, S.V. Petrov

“…This article highlights an insufficiently studied issue of a primary source of placer gold in alluvium of the basin of the Kukulkindzha Creek (Okhotsk region, Khabarovsk krai) be means of the analysis of mineralogical and geochemical features of samples. …”
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FalconSign: An Efficient and High-Throughput Hardware Architecture for Falcon Signature Generation by Yi Ouyang, Yihong Zhu, Wenping Zhu, Bohan Yang, Zirui Zhang, Hanning Wang, Qichao Tao, Min Zhu, Shaojun Wei, Leibo Liu

“…Our approach involves a new scheduling flow and architecture for Fast-Fourier Sampling to enhance computing unit reuse and reduce processing time. …”
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Intrinsic immunosuppressive features of monocytes suppress CAR-T19 through IL-1 pathway modulation in mantle cell lymphoma by Kun Yun, R. Leo Sakemura, Ismail Can, Omar Gutierrez Ruiz, Ekene J. Ogbodo, Shuwen Zhang, Ateka Saleh, Truc N. Huynh, Claudia Manriquez Roman, Olivia L. Sirpilla, Carli M. Stewart, James H. Girsch, Jennifer M. Feigin, Long Mai, Hong Xia, Brooke Kimball, Lionel A. Kankeu Fonkoua, Mehrdad Hefazi, Michael W. Ruff, Fariborz Rakhshan Rohakhtar, Vernadette Simon, Elizabeth L. Siegler, Mike Mattie, Sao-Mai Nguyen-Mau, Simone Filosto, Saad S. Kenderian

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Analyzing and Mitigating Bias for Vulnerable Road Users by Addressing Class Imbalance in Datasets by Dewant Katare, David Solans Noguero, Souneil Park, Nicolas Kourtellis, Marijn Janssen, Aaron Yi Ding

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EXPERIENCE IN DEVELOPMENT MEDICAL KITS FOR MEDICAL SERVICES OF THE RUSSIAN FEDERATION ARMED FORCES by E. O. Rodionov, Yu. V. Miroshnichenko, V. N. Kononov, A. V. Tikhonov, I. V. Klochkova

“…The aim of the study was the formation of programs of development of modern samples of complete-standard-issue equipment. Materials and methods. …”
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Surveying emigrants worldwide–using Facebook and Instagram to recruit respondents in cross-national (e)migration research by Steffen Pötzschke, Bernd Weiß

“…The method also yielded good results in world regions where other surveys faced severe coverage issues. Furthermore, a considerable share of the sample could not have been reached using German population registers as a sampling frame, which otherwise constitutes the most promising alternative approach.…”
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ADWTune: an adaptive dynamic workload tuning system with deep reinforcement learning by Cuixia Li, Junhai Wang, Jiahao Shi, Liqiang Liu, Shuyan Zhang

“…In this model, ADWTune employs the idea of multiple sampling to gather workload data at different time points during the observation period. …”
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Comparison of Dynamic State Estimation Methods in the Time Domain by Saeed Javadi, Ali Hesami Naghshbandy

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Seamless multi-skill learning: learning and transitioning non-similar skills in quadruped robots with limited data by Jiaxin Tu, Peng Zhai, Yueqi Zhang, Xiaoyi Wei, Zhiyan Dong, Lihua Zhang

“…Our experiments highlight potential issues with baseline methods when imitating incomplete expert datasets and demonstrate the superior performance of the SMSL framework. …”
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Analytical Approach to the Selection of Research Topics for Gallstone Disease and Acute Cholecystitis (an Overview of Cochrane Reviews) by S. I. Panin, T. V. Nechay, A. V. Sazhin, A. V. Puzikova

“…The same applies to mortality, the probability of developing serious complications and the conversion rate of various minimally invasive procedures, as the required sample sizes (hundreds of thousands of observations) are difficult to achieve — currently range is from 0.03 to 21.9 %. …”
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The illusion of success: Test set disproportion causes inflated accuracy in remote sensing mapping research by Yuanjun Xiao, Zhen Zhao, Jingfeng Huang, Ran Huang, Wei Weng, Gerui Liang, Chang Zhou, Qi Shao, Qiyu Tian

“…A rigorous approach for accuracy assessment was suggested, and an example of tea plantations mapping is used to demonstrate the process and analyse potential issues in traditional approaches. A scale factor (λ) was constructed to measure the discrepancy in sample size ratios between test sets and actual conditions. …”
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Designing a hybrid stack ensemble model to enhance sepsis classification using data triangulation approach by Safiya Parvin A․, Saleena B․

“…Sepsis is a major health issue affecting newborns, often caused by factors such as premature birth, birth asphyxia, pneumonia, and meningitis. …”
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Default Priors in a Zero-Inflated Poisson Distribution: Intrinsic Versus Integral Priors by Junhyeok Hong, Kipum Kim, Seong W. Kim

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Application of Semi-Supervised Clustering with Membership Information and Deep Learning in Landslide Susceptibility Assessment by Hua Xia, Zili Qin, Yuanxin Tong, Yintian Li, Rui Zhang, Hongxia Luo

“…To address this issue, this study proposes a novel Landslide Susceptibility Index–based Semi-supervised Fuzzy C-Means (LSI-SFCM) sampling strategy combining membership degrees. …”
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Optimal View Estimation Algorithm and Evaluation with Deviation Angle Analysis by Meng Yuan, Hongjun Li

“…To address the first issue, this paper proposes a spherical viewpoint sampling method based on a combination of analytical methods and motion adjustment, and designs a viewpoint-based projection image acquisition algorithm. …”
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Graph signal processing based pilot pattern design and channel estimation for OFDM system by Bin HE, Guobing LI, Yuan CHEN, Guomei ZHANG

“…Orthogonal frequency division multiplexing (OFDM) is one of the key technologies in the physical layer of the internet of things (IoT).Pilot design and channel estimation are key issues in OFDM systems.In view of the problem of performance loss by fixed pilot pattern due to the complexity and variety of IoT communication scenarios, a pilot design and channel estimation scheme based on graph signal processing (GSP) was proposed.Firstly, the time-frequency resource block was modeled as a graph signal, and the channel estimation problem was reformulated into a sampling and reconstruction problem of the graph signal.Then, considering the influence of time-frequency fading, a weighted graph adjacency matrix was designed to construct a graph topology structure based on the time-frequency position.On this basis, the pilot position is selected based on the graph signal sampling theory, a greedy pilot pattern design algorithm based on weighted graph topology was proposed.At the same time, signal reconstruction was performed based on the graph signal reconstruction method, and a channel estimation method based on the graph smoothness constraint was proposed.Compared with the conventional scheme, simulation results show that the proposed method achieves higher channel estimation accuracy in high-speed scenarios of double selective channels, and effectively reduces pilot overhead in low-speed scenarios.…”
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MEFA-Net: Multilevel Feature Extraction and Fusion Attention Network for Infrared Small-Target Detection by Jingcui Ma, Nian Pan, Dengyu Yin, Di Wang, Jin Zhou

“…Infrared small-target detection encounters significant challenges due to a low image signal-to-noise ratio, limited target size, and complex background noise. To address the issues of sparse feature loss for small targets during the down-sampling phase of the traditional U-Net network and the semantic gap in the feature fusion process, a multilevel feature extraction and fusion attention network (MEFA-Net) is designed. …”
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