Adoption deep learning approach using realistic synthetic data for enhancing network intrusion detection in intelligent vehicle systems by Said A. Salloum, Tarek Gaber, Mohammed Amin Almaiah, Rami Shehab, Romel Al-Ali, Theyazan H.H Aldahyani

“…Traditional Network Intrusion Detection Systems (NIDS) often fall short in detecting emerging and sophisticated intrusion methods, primarily due to their reliance on static datasets that fail to capture the nuanced dynamics and complexity of modern network intrusions. …”
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SED-NET: Real-Time Suspicious Event Detection via Deep Learning-Based Di-Stream Neural Network by D. Siva Senthil, T. S. Sivarani

“…However, existing approaches have high false positive rates difficulty distinguishing suspicious from normal behaviors, and limited adaptability to dynamic environments. This research introduces a novel deep learning-based SED-NET model for detecting suspicious events in public places. …”
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Assessment of seawater intrusion in coastal aquifers by modified CCME-WQI Indicators: Decadal dynamics in North Jiaozhou Bay, China by Dong Ji, Junzhuo Xue, Wenxiang Wang, Jian Ma, Zeyong Wang

“…The modified CCME-WQI outperformed conventional single-indicator assessment methods based on chloride concentrations by detecting nuanced ion-exchange mechanisms and freshening processes in aquifer systems. …”
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Pulmonary hypertension and NT-proBNP dynamics during the course of adulticide treatment in dogs naturally infected by Dirofilaria immitis by Noelia Costa-Rodríguez, Daniel Julio Vera-Rodríguez, Soraya Falcón-Cordón, Beatriz Regina Morales, José Alberto Montoya-Alonso, Rodrigo Morchón, Elena Carretón

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Monte carlo simulation for evaluating spatial dynamics of toxic metals and potential health hazards in sebou basin surface water by Hatim Sanad, Rachid Moussadek, Latifa Mouhir, Majda Oueld Lhaj, Houria Dakak, Khadija Manhou, Abdelmjid Zouahri

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DIFFERENTIAL AND DIAGNOSTIC CRITERIA OF THE RECURRENCE OF GLIOMAS IN THE POST-OPERATIONAL PERIOD USING OF DYNAMIC CONTRAST-ENHANCED MRA AND PERFUSION MRI by O. Yu. Borodin, V. Yu. Usov

“…Objective: to elaborate differential diagnostic criteria for recurrent gliomas after combination treatment, by using dynamic contrast-enhanced magnetic resonance angiography (DCE-MRA) and T2*-weighted perfusion magnetic resonance imaging (MRI).Material and methods. …”
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Automatic Detection and 3D Modeling of City Furniture Objects using LiDAR and Imagery Mobile Mapping Data by H. Doi, A. Yarroudh, I. Jeddoub, R. Hajji, R. Billen

“…This study implements two methodologies for detecting, classifying, and positioning City Furniture objects, as well as one approach for their automatic 3D modeling. …”
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Regional classification and logistic regression modeling for surface freeze/thaw detection on the Qinghai-Tibet Plateau using CYGNSS data by Jiaxing He, Nanshan Zheng, Rui Ding, Xuexi Liu, Zhiyong Ma

“…To overcome these limitations, this study proposes an innovative approach that integrates the application of GNSS-R data with regional classification and logistic regression modeling, establishing an efficient framework for detecting surface F/T states. The method involves pre-classifying the Qinghai-Tibet Plateau (QTP) into five regions based on characteristic data, followed by logistic regression to predict soil states. …”
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An Improved COLD Approach for Monitoring Construction Dynamics Using HLS and LULC Data: A Case Study in the New Capital of Egypt by M. Abdallah, M. Abdallah, M. Abdallah, E. Ali, E. Ali, X. Ding, X. Ding, S. Wu, S. Wu

“…We focused on tracking construction dynamics from 2016 to the present. The spatiotemporal detection of land disturbances uses the COLD algorithm with a dataset of 559 images from Harmonized Landsat and Sentinel missions. …”
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Spatiotemporal dynamics and predictive modelling of land use and land cover changes for sustainable watershed management in the Karamana River Basin, India by Ganga Krishnan, Radhakrishnan Shanthi Priya, Geetha Ramesh Kumar, Ramalingam Senthil

“…Multi-temporal satellite imagery was analyzed to classify LULC into nine categories, followed by change detection analysis and spectral indices to quantify the nature and extent of transformation. …”
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GenCoder++: A Protocol-Aware and Adversarially Robust Adaptive Intrusion Detection Framework for Hybrid CAN-Ethernet Vehicular Networks by Mikhail Smolin

“…This paper presents GenCoder++, a robust and adaptive Intrusion Detection System (IDS) framework designed for hybrid vehicular networks that incorporates the Controller Area Network (CAN) and Ethernet protocols. …”
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Western Range Limit, Population Density, and Flight Dynamics of the Fruit Pest <i>Grapholita inopinata</i> (Lepidoptera: Tortricidae) in Russia by Evgeny N. Akulov, Margarita G. Kovalenko, Julia A. Lovtsova, Dmitrii L. Musolin, Natalia I. Kirichenko

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Clinical characteristics, risk stratifications, and long-term follow-up of childhood differentiated thyroid cancer: a single-center experience by Sirmen Kızılcan Çetin, Zehra Aycan, Zeynep Şıklar, Elif Özsu, Suat Fitöz, Koray Ceyhan, Aydın Yağmurlu, Gülnur Göllü Bahadır, Emel Ünal, Nurdan Taşyıldız, Metin Kır, Çiğdem Soydal, Merih Berberoğlu

“…During follow-up, cervical metastases were detected in 27 patients, and one had distant metastasis. …”
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Diagnostic validity of dynamic salivary gland scintigraphy with ascorbic acid stimulation in patients with Sjögren's syndrome: Comparation with unstimulated whole sialometry by Dugonjić Sanja, Ajdinović Boris, Stefanović Dušan, Jauković Ljiljana

“…The fifth item of the European Union and the United States of America (EU-US) revised diagnostic classification criteria in 2002, is an objective evidence of xerostomia, diagnosed by one of the tests: unstimulated whole sialometry (UWS), parotid sialography, and dynamic salivary gland scintigraphy (DSGS). The aim of this study was to evaluate senstitivity, specificity, positive and negative predictive value and accuracy of DSGS with ascorbic acid stimulation in detecting xerostomia in SS patients and to compare DSGS findings with UWS values. …”
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Potential of solar-induced chlorophyll fluorescence for monitoring long-term dynamics of soil salinity in Central Asia the Xinjiang Region China by Kuangda Cui, Kuangda Cui, Jianli Ding, Jianli Ding, Jinjie Wang, Jinjie Wang, Jiao Tan, Jiao Tan, Lijing Han, Jiangtao Li, Jiangtao Li

“…Model performance, seasonal sensitivity, and spatial variation were analyzed across Central Asian countries and Xinjiang.ResultsSIF effectively detected salinization dynamics, with highest sensitivity in Kazakhstan and Xinjiang. …”
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Dynamic changes in serum adenosine and the adenosine metabolism-based signature for prognosis in HER2-positive metastatic breast cancer patients by Lijun Wang, Yizhi Ge, Li Yin, Dan Zong, Yang Li, Jianfeng Wu, Xia He

“…The adenosine levels were dynamically detected, and the difference in immune microenvironment between the subgroups was assessed by the immune cells that were recorded in our center. …”
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A 6-tsRNA signature for early detection, treatment response monitoring, and prognosis prediction in diffuse large B cell lymphoma by Jun Rao, Lin Xia, Qiong Li, NaYa Ma, Xinlei Li, Jiali Li, Lidan Zhu, Pan Zhao, Yunjing Zeng, Sha Zhou, Huanping Guo, Shijia Lin, Song Dong, Shifeng Lou, Fangyi Fan, Jin Wei, Jiang F. Zhong, Li Gao, Shengwen Calvin Li, Xi Zhang

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HSF: A Hybrid SVM-RF Machine Learning Framework for Dual-Plane DDoS Detection and Mitigation in Software-Defined Networks by Abdinasir Hirsi, Lukman Audah, Mohammed A. Alhartomi, Adeb Salh, Godwin Okon Ansa, Mustafa Maad Hamdi, Diani Galih Saputri, Salman Ahmed, Abdullahi Farah

“…In particular, the framework utilizes a hybrid model that combines a Support Vector Machine (SVM) and Random Forest (RF) classifiers (HSF), which significantly improves intrusion detection accuracy. …”
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Shoreline Change Detection Using DSAS: Case Study in PT IWIP Mining Industrial Area, North Maluku Province, Indonesia by Nurhalis Wahidin, Adi Noman Susanto, Irham, Zulhan Arifin Harahap, Salnuddin, Muhammad Aris

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Understanding and detection of process instabilities in wire arc directed energy deposition additive manufacturing using meltpool imaging and machine learning by André Ramalho, Anis Assad, Benjamin Bevans, Fernando Deschamps, Telmo G. Santos, J.P. Oliveira, Prahalada Rao

“…The objectives were two-fold: (1) observe and understand, through in-operando high-speed meltpool imaging, the causal dynamics of two common WA-DED process instabilities, namely, humping and humping-induced porosity; and (2) leverage the high-speed meltpool imaging data within machine learning algorithms for real-time detection of process instabilities. …”
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