Готові списки джерел за темами / Feature behavior analysis

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Добірка наукової літератури з теми "Feature behavior analysis"

Автор: Grafiati

Опубліковано: 10 січня 2023

Оновлено: 31 липня 2025

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Статті в журналах з теми "Feature behavior analysis"

KARA, LEVENT BURAK, and THOMAS F. STAHOVICH. "Causal reasoning using geometric analysis." Artificial Intelligence for Engineering Design, Analysis and Manufacturing 16, no. 5 (2002): 363–84. http://dx.doi.org/10.1017/s0890060402165036.

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We describe an approach that uses causal and geometric reasoning to construct explanations for the purposes of the geometric features on the parts of a mechanical device. To identify the purpose of a feature, the device is simulated with and without the feature. The simulations are then translated into a “causal-process” representation, which allows qualitatively important differences to be identified. These differences reveal the behaviors caused and prevented by the feature and thus provide useful cues about the feature's purpose. A clear understanding of the feature's purpose, however, requ

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T.Sajana, Monali Gulhane,. "Human Behavior Prediction and Analysis Using Machine Learning-A Review." Turkish Journal of Computer and Mathematics Education (TURCOMAT) 12, no. 5 (2021): 870–76. http://dx.doi.org/10.17762/turcomat.v12i5.1499.

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Nowadays many trends are being in the area of medicine to predict the human behaviour and analysis of patient behaviour is being studied but the technical difficulty of cost efficient method to predict the behaviour of user is overcome in the proposed researched methodology .The mental health of the used can lead to good immunity system to be healthy in this pandemic of COVID-19. Hence After a detailed study on different human health disease classification techniques it is found that machine learning techniques are reliable for the feature extraction and analysis of the different human paramet

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Lu, Jia, Jun Shen, Wei Qi Yan, and Boris Bačić. "An Empirical Study for Human Behavior Analysis." International Journal of Digital Crime and Forensics 9, no. 3 (2017): 11–27. http://dx.doi.org/10.4018/ijdcf.2017070102.

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This paper presents an empirical study for human behavior analysis based on three distinct feature extraction techniques: Histograms of Oriented Gradients (HOG), Local Binary Pattern (LBP) and Scale Invariant Local Ternary Pattern (SILTP). The utilised public videos representing spatio-temporal problem area of investigation include INRIA person detection and Weizmann pedestrian activity datasets. For INRIA dataset, both LBP and HOG were able to eliminate redundant video data and show human-intelligible feature visualisation of extracted features required for classification tasks. However, for

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Dang, Zijun, Shunshun Liu, Tong Li, and Liang Gao. "Analysis of Stadium Operation Risk Warning Model Based on Deep Confidence Neural Network Algorithm." Computational Intelligence and Neuroscience 2021 (July 5, 2021): 1–10. http://dx.doi.org/10.1155/2021/3715116.

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In this paper, a deep confidence neural network algorithm is used to design and deeply analyze the risk warning model for stadium operation. Many factors, such as video shooting angle, background brightness, diversity of features, and the relationship between human behaviors, make feature attribute-based behavior detection a focus of researchers’ attention. To address these factors, researchers have proposed a method to extract human behavior skeleton and optical flow feature information from videos. The key of the deep confidence neural network-based recognition method is the extraction of th

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Qi, Yu, Siyu Xiong, and Bo Wu. "Analysis, Evaluation, and Prediction of Machine Learning-Based Animal Behavior Imitation." Electronics 14, no. 14 (2025): 2816. https://doi.org/10.3390/electronics14142816.

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Expressive imitation in the performing arts is typically trained through animal behavior imitation, aiming not only to reproduce action trajectories but also to recreate rhythm, style and emotional states. However, evaluation of such animal imitation behaviors relies heavily on teachers’ subjective judgments, lacking structured criteria, exhibiting low inter-rater consistency and being difficult to quantify. To enhance the objectivity and interpretability of the scoring process, this study develops a machine learning and structured pose data-based auxiliary evaluation framework for imitation q

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Donia, Manar M. F., Wessam H. El-Behaidy, and Aliaa A. A. Youssif. "Impulsive Aggression Break, Based on Early Recognition Using Spatiotemporal Features." Big Data and Cognitive Computing 7, no. 3 (2023): 150. http://dx.doi.org/10.3390/bdcc7030150.

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The study of human behaviors aims to gain a deeper perception of stimuli that control decision making. To describe, explain, predict, and control behavior, human behavior can be classified as either non-aggressive or anomalous behavior. Anomalous behavior is any unusual activity; impulsive aggressive, or violent behaviors are the most harmful. The detection of such behaviors at the initial spark is critical for guiding public safety decisions and a key to its security. This paper proposes an automatic aggressive-event recognition method based on effective feature representation and analysis. T

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Hsiang-Hua Hung, Hsiang-Hua Hung, Jiann-Liang Chen Hsiang-Hua Hung, and Yi-Wei Ma Jiann-Liang Chen. "Machine Learning Approaches to Malicious PowerShell Scripts Detection and Feature Combination Analysis." 網際網路技術學刊 25, no. 1 (2024): 167–73. http://dx.doi.org/10.53106/160792642024012501014.

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<p>With advances in communication technology, modern society relies more than ever on the Internet and various user-friendly digital tools. It provides access to and enables the manipulation of files, trips, and the Windows API. Attackers frequently use various obfuscation techniques PowerShell scripts to avoid detection by anti-virus software. Their doing so can significantly reduce the readability of the script. This work statically analyzes PowerShell scripts. Thirty-three features that were based on the script&rsquo;s keywords, format, and string combinations were used herein to

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Maitham, Ali Naji, Ahmed Salman Ghalib, and Jasim Fadhil Muthna. "Face recognition using selected topographical features." International Journal of Electrical and Computer Engineering (IJECE) 10, no. 5 (2020): 4695–700. https://doi.org/10.11591/ijece.v10i5.pp4695-4700.

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This paper represents a new features selection method to improve an existed feature type. Topographical (TGH) features provide large set of features by assigning each image pixel to the related feature depending on image gradient and Hessian matrix. Such type of features was handled by a proposed features selection method. A face recognition feature selector (FRFS) method is presented to inspect TGH features. FRFS depends in its main concept on linear discriminant analysis (LDA) technique, which is used in evaluating features efficiency. FRFS studies feature behavior over a dataset of images t

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Bhavya, Rajeev*1 &. Mohammed Malik C. K2. "PERSONALITY AND SOCIAL NETWORK MENTAL DISORDER PREDICTION VIA TWITTER ANALYSIS." INTERNATIONAL JOURNAL OF ENGINEERING SCIENCES & RESEARCH TECHNOLOGY Metanoia 19 (April 4, 2019): 6–11. https://doi.org/10.5281/zenodo.2629143.

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With the rise in popularity of social networking, various types of social network mental disorders (SNMDs), such as Cyber-Relationship Addiction, Information Overload, and Net Compulsion, has shown up on the surface. Symptoms of these mental disorders are usually observed passively, resulting in delayed clinical intervention. From the studies it was observed that the core reason for some of this addictive behavior was depression. In this paper we propose a machine learning framework, enhanced with sentimental analysis that exploits features extracted from social network data, to accurately ide

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Karaaslan, Mahmut, Bahaeddin Turkoglu, Ersin Kaya, and Tunc Asuroglu. "Voice Analysis in Dogs with Deep Learning: Development of a Fully Automatic Voice Analysis System for Bioacoustics Studies." Sensors 24, no. 24 (2024): 7978. https://doi.org/10.3390/s24247978.

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Extracting behavioral information from animal sounds has long been a focus of research in bioacoustics, as sound-derived data are crucial for understanding animal behavior and environmental interactions. Traditional methods, which involve manual review of extensive recordings, pose significant challenges. This study proposes an automated system for detecting and classifying animal vocalizations, enhancing efficiency in behavior analysis. The system uses a preprocessing step to segment relevant sound regions from audio recordings, followed by feature extraction using Short-Time Fourier Transfor

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Дисертації з теми "Feature behavior analysis"

Wang, Jincheng. "Selective laser melting of Ti-35NB alloy: Processing, microstructure and properties." Thesis, Edith Cowan University, Research Online, Perth, Western Australia, 2021. https://ro.ecu.edu.au/theses/2450.

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The initiative of a sustainable material system needs to lower the environmental and economic impact of production processes and adopt new ways of synthesizing and re-using materials. Even though the current conventional manufacturing processes, such as powder metallurgy, casting, forging, and rolling, have already shown their excellent ability to manufacture a large variety of parts and efficiently yield high volume products. Nevertheless, there are still many obstacles in manufacturing metallic components, such as complicated process procedures, high-energy consumption, large material waste,

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Cheng, Heng-Tze. "Learning and Recognizing The Hierarchical and Sequential Structure of Human Activities." Research Showcase @ CMU, 2013. http://repository.cmu.edu/dissertations/293.

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The mission of the research presented in this thesis is to give computers the power to sense and react to human activities. Without the ability to sense the surroundings and understand what humans are doing, computers will not be able to provide active, timely, appropriate, and considerate services to the humans. To accomplish this mission, the work stands on the shoulders of two giants: Machine learning and ubiquitous computing. Because of the ubiquity of sensor-enabled mobile and wearable devices, there has been an emerging opportunity to sense, learn, and infer human activities from the sen

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SHAHID, MUHAMMAD. "Social Interactions Analysis through Deep Visual Nonverbal Features." Doctoral thesis, Università degli studi di Genova, 2021. http://hdl.handle.net/11567/1040976.

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Human social interaction is as common as complex to understand. It is a part of our routine life ranging from houses to communal places either in direct face-to-face interaction or through digital media. During these interactions, humans exchange their thoughts, intentions, and emotions effectively. They use verbal language along with non-verbal social signals such as variation in voice tune, hand gestures, facial expressions, and body posture. This non-verbal part of communication is still less understood despite the fact of recent huge research progression and computational advancement. Rece

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Kim, Jonathan Chongkang. "Classification of affect using novel voice and visual features." Diss., Georgia Institute of Technology, 2014. http://hdl.handle.net/1853/54301.

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Emotion adds an important element to the discussion of how information is conveyed and processed by humans; indeed, it plays an important role in the contextual understanding of messages. This research is centered on investigating relevant features for affect classification, along with modeling the multimodal and multitemporal nature of emotion. The use of formant-based features for affect classification is explored. Since linear predictive coding (LPC) based formant estimators often encounter problems with modeling speech elements, such as nasalized phonemes and give inconsistent results fo

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Green, Steven Paul. "Intelligent Person Behaviour Analysis in Low Resolution Beach Video Imagery." Thesis, Griffith University, 2011. http://hdl.handle.net/10072/366650.

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Object detection in complex scenes plays an important role in many real world applications, such as scene analysis, security, traffic violation detection, and medical research. The Object Detection and Behaviour Classification (ODBC) system created from this PhD research, is ground-breaking and concentrates solely on the domain of people and behaviour detection in low resolution beach scene imagery. The video source for this research was obtained from Coastalwatch beach webcams, which are located throughout Australia. Current object detection systems, overall, utilise a similar methodology, fo

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Leoputra, Wilson Suryajaya. "Video foreground extraction for mobile camera platforms." Thesis, Curtin University, 2009. http://hdl.handle.net/20.500.11937/1384.

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Foreground object detection is a fundamental task in computer vision with many applications in areas such as object tracking, event identification, and behavior analysis. Most conventional foreground object detection methods work only in a stable illumination environments using fixed cameras. In real-world applications, however, it is often the case that the algorithm needs to operate under the following challenging conditions: drastic lighting changes, object shape complexity, moving cameras, low frame capture rates, and low resolution images. This thesis presents four novel approaches for fo

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Regard, Viktor. "Studying the effectiveness of dynamic analysis for fingerprinting Android malware behavior." Thesis, Linköpings universitet, Databas och informationsteknik, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-163090.

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Android is the second most targeted operating system for malware authors and to counter the development of Android malware, more knowledge about their behavior is needed. There are mainly two approaches to analyze Android malware, namely static and dynamic analysis. Recently in 2017, a study and well labeled dataset, named AMD (Android Malware Dataset), consisting of over 24,000 malware samples was released. It is divided into 135 varieties based on similar malicious behavior, retrieved through static analysis of the file classes.dex in the APK of each malware, whereas the labeled features wer

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Rickard, Renee E. "Dialectical behaviour therapists' experience of young people with features of borderline personality disorder : a qualitative analysis." Thesis, Bangor University, 2012. https://research.bangor.ac.uk/portal/en/theses/dialectical-behaviour-therapists-experience-of-young-people-with-features-of-borderline-personality-disorder--a-qualitative-analysis(73cc85c9-1146-451a-86f8-d40d0ccdb3b4).html.

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This thesis examines mental health professionals' responses toward patients diagnosed with Borderline Personality Disorder (BPD) and presents a qualitative study of Dialectical Behaviour Therapists' (DBT) experiences in their work with young people with BPD features. A review of empirical literature regarding emotional, behavioural and attitudinal responses of professionals toward these patients identified a range of negative responses, distinguishable from responses toward patients with other mental health problems. The review highlights the consistency of responses in professionals working i

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Lutz, Vanessa [Verfasser], and Jörn [Akademischer Betreuer] Bennewitz. "Genetic analyses of feather pecking and related behavior traits of laying hens / Vanessa Lutz ; Betreuer: Jörn Bennewitz." Hohenheim : Kommunikations-, Informations- und Medienzentrum der Universität Hohenheim, 2017. http://d-nb.info/1128211157/34.

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Iffland, Hanna [Verfasser], and Jörn [Akademischer Betreuer] Bennewitz. "Genomic analyses of behavior traits in laying hen lines divergently selected for feather pecking / Hanna Iffland ; Betreuer: Jörn Bennewitz." Hohenheim : Kommunikations-, Informations- und Medienzentrum der Universität Hohenheim, 2021. http://nbn-resolving.de/urn:nbn:de:bsz:100-opus-19395.

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Книги з теми "Feature behavior analysis"

Filippov, Mihail, Svetlana Savel'eva, and Elena Belous. Conflicts among adolescents and mediation techniques for their resolution. INFRA-M Academic Publishing LLC., 2025. https://doi.org/10.12737/2141118.

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The textbook reveals the main causes, conditions and current techniques for overcoming conflicts among adolescents in the education system. The issues of conflict prevention and ways of their resolution are considered. The analysis of the conflict behavior of adolescents in educational institutions and recommendations for its resolution are given. The manual also includes technologies for studying and diagnosing conflict situations, contains specific descriptions of diagnostic techniques and mediation techniques, features of their implementation, generalization, analysis and data processing. M

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Galas, Marina, and Lyudmila Brushkova. Self-identification of Russian youth in a transforming world. INFRA-M Academic Publishing LLC., 2025. https://doi.org/10.12737/2162821.

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The monograph examines and systematizes the value orientations of the Russian youth of the digital generation, which form self-identification. In this context, the social, economic, sociocultural, and family value orientations of young Russian citizens are studied; the features of their civic self-identification are revealed. The analysis of youth's assessment of the inclusivity and quality of higher education and its role in social adaptation and competitiveness is carried out. The influence of modern institutions and channels on the self-identification of Russian youth of the digital generat

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Schramm, Elisabeth, McCullough James P. Jr, and J. KIm Penberthy. Cognitive Behavioral Analysis System of Psychotherapy: Distinctive Features. Taylor & Francis Group, 2014.

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Cognitive Behavioral Analysis System of Psychotherapy: Distinctive Features. Taylor & Francis Group, 2014.

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Schoen, Harald, Sigrid Roßteutscher, Rüdiger Schmitt-Beck, Bernhard Weßels, and Christof Wolf. Voters and Voting in Context. Oxford University Press, 2017. http://dx.doi.org/10.1093/oso/9780198792130.003.0001.

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After a brief review of the scholarly discussion about the idea that context affects political behavior, this chapter proposes a model for the analysis of contextual effects on opinion formation and voting behavior. It highlights theoretical issues in the interplay of various contextual features and voter predispositions in bringing about contextual effects on voters. This model guides the analyses of contextual effects on voter behavior in Germany in the early twenty-first century. These analyses draw on rich data from multiple voter surveys and various sources of information about contextual

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Aspell, Luke. Shivers. Liverpool University Press, 2019. http://dx.doi.org/10.3828/liverpool/9781911325970.001.0001.

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Shivers (1975) was David Cronenberg's first commercial feature and his first horror film. In a modern apartment block, a scientific project to unleash the id results in the equation of passion with contagion and predation. Because the writer-director's imaginative landscape arrived in the genre fully formed, the unique forms of this début have often been overlooked or mistaken for shortcomings. Cronenberg's most comedic film until Map to the Stars, Shivers is also his most spectacularly unnerving, throwing more images of extreme behavior at us than any of his subsequent films; it remains, with

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McCarty, Nolan. Polarization and American Political Development. Edited by Richard Valelly, Suzanne Mettler, and Robert Lieberman. Oxford University Press, 2015. http://dx.doi.org/10.1093/oxfordhb/9780199697915.013.17.

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One of the most fertile areas of research has been the question of why the American political system has polarized so sharply over the past four decades. The academic debates about polarization have largely been carried out by mainstream scholars of political behavior and institutions. Scholars of American Political Development (APD) have a major opportunity to participate in a vital debate about the emergence of a central feature of the contemporary American system while mainstream scholars should come to appreciate that one cannot easily develop explanations for dynamic change with static mo

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Potter, Nancy Nyquist. Interpreting defiant behavior in children: Constructs, norms, and intersectionalities. Oxford University Press, 2016. http://dx.doi.org/10.1093/med/9780199663866.003.0004.

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The primary argument of this chapter is that children’s and youth’s defiance may be misread and misinterpreted unless a greater understanding of the interplay of genders, races, and ethnicities is grasped. It analyzes various types of aggression to illustrate that the norms that determine harms from aggressive behavior need to be articulated and critiqued. The chapter sets out central characteristics of Oppositional Defiant Disorder (ODD) and Conduct Disorder (CD), then analyzes the larger context for understanding defiant behavior. Research on features of aggression in children’s play is incl

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Deurzen, Emmy Van, and Claire Arnold-Baker. Existential Therapy: Distinctive Features. Taylor & Francis Group, 2018.

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Deurzen, Emmy Van, and Claire Arnold-Baker. Existential Therapy: Distinctive Features. Taylor & Francis Group, 2018.

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Частини книг з теми "Feature behavior analysis"

Uddin, Md Zia. "Feature Analysis Using Python." In Machine Learning and Python for Human Behavior, Emotion, and Health Status Analysis. CRC Press, 2024. http://dx.doi.org/10.1201/9781003425908-3.

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Gopinath, Divya, Luca Lungeanu, Ravi Mangal, Corina Păsăreanu, Siqi Xie, and Huanfeng Yu. "Feature-Guided Analysis of Neural Networks." In Fundamental Approaches to Software Engineering. Springer Nature Switzerland, 2023. http://dx.doi.org/10.1007/978-3-031-30826-0_7.

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AbstractApplying standard software engineering practices to neural networks is challenging due to the lack of high-level abstractions describing a neural network’s behavior. To address this challenge, we propose to extract high-level task-specific features from the neural network internal representation, based on monitoring the neural network activations. The extracted feature representations can serve as a link to high-level requirements and can be leveraged to enable fundamental software engineering activities, such as automated testing, debugging, requirements analysis, and formal verificat

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Karmakar, Mousumi, Md Abdullah Al Kafi, Arafat Sahin Afridi, Wahid Sabbir, and Dewan Mamun Raza. "Feature Engineering for Predicting Consumer Purchase Behavior: A Comprehensive Analysis." In Communications in Computer and Information Science. Springer Nature Switzerland, 2024. http://dx.doi.org/10.1007/978-3-031-64067-4_10.

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Lorbach, Malte, Ronald Poppe, Elsbeth A. van Dam, Lucas P. J. J. Noldus, and Remco C. Veltkamp. "Automated Recognition of Social Behavior in Rats: The Role of Feature Quality." In Image Analysis and Processing — ICIAP 2015. Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-23234-8_52.

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Tang, Ye, Junqiang Sun, Guangjin Wang, Wenjin Hong, and Li Li. "Analysis of Campus Crowd Behavior Based on Location Data and Physical Environment Data: A Case Study of Southeast University Wuxi Campus." In Computational Design and Robotic Fabrication. Springer Nature Singapore, 2025. https://doi.org/10.1007/978-981-96-3433-0_36.

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Abstract The study on the behavior of on-campus individuals provides valuable insights for campus management, resource allocation, and planning layout. The application of multi-source data offers more objective and in-depth opportunities for exploring behavioral phenomena. Focusing on the Wuxi campus of Southeast University, this research utilized Wi-Fi probe positioning technology combined with a physical environment sensor system to comprehensively collect 28.87 million positioning data points and 340,000 environmental data points over a period of 14 days. After cleaning redundant, missing,

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Kasubi, John W., and D. H. Manjaiah. "Feature Selection Strategy for Multi-residents Behavior Analysis in Smart Home Environment." In Data Management, Analytics and Innovation. Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-16-2937-2_2.

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Li, Yuqing, Jinman Luo, and Lina Wang. "Electricity Customer Behavior Analysis Method Based on Adaptive Feature Weight Clustering Algorithm." In Sustainable Civil Infrastructures. Springer Nature Switzerland, 2024. https://doi.org/10.1007/978-3-031-78276-3_14.

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Wang, Xuan, Jindong Zhao, Yingjie Wang, Jun Lv, and Weiqing Yan. "Vehicle Feature Point Trajectory Clustering and Vehicle Behavior Analysis in Complex Traffic Scenes." In Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering. Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-44751-9_17.

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Luo, Qiumin, Hongzhi Wang, Gang Li, and Zunyi Shang. "College Students Learning Behavior Analysis Based on SVM and Fisher-Score Feature Selection." In Lecture Notes in Electrical Engineering. Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-13-9409-6_306.

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Chen, Tingting, and Sitong Gao. "Improved Slow Feature Analysis Algorithm and Its Application in Abnormal Human Behavior Recognition." In Proceedings of the World Conference on Intelligent and 3-D Technologies (WCI3DT 2022). Springer Nature Singapore, 2023. http://dx.doi.org/10.1007/978-981-19-7184-6_32.

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Тези доповідей конференцій з теми "Feature behavior analysis"

Yang, Liu, Nie Xiao, Yue Zhusen, He Chaoqun, and Li Yunfeng. "Electric power stealing behavior analysis and identification method based on electricity feature extraction." In 2024 IEEE 6th International Conference on Civil Aviation Safety and Information Technology (ICCASIT). IEEE, 2024. https://doi.org/10.1109/iccasit62299.2024.10827871.

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Allagi, Shridhar, Toralkar Pawan, Kavita Mainalli, and Nagaraj Dharwadkar. "Leveraging AI and ML for Predictive Analysis and Feature Attribution in Abnormal Network Behavior Detection." In 2024 2nd World Conference on Communication & Computing (WCONF). IEEE, 2024. http://dx.doi.org/10.1109/wconf61366.2024.10692056.

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He, Mingjie, Weihai Li, and Zikai Xu. "A Lower-Cost Insider Threat Detection Framework Based on User Cluster and Behavior Feature Analysis." In 2024 IEEE International Conference on Security, Privacy, Anonymity in Computation and Communication and Storage (SpaCCS). IEEE, 2024. https://doi.org/10.1109/spaccs63173.2024.00010.

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Wall, F. D., and G. E. Stoner. "Electrochemical Characterization and Occluded Environment Analysis of Localized Corrosion in Advanced Aluminum Alloys." In CORROSION 1994. NACE International, 1994. https://doi.org/10.5006/c1994-94546.

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Abstract In order for advanced aluminum alloys to be used in structural applications it is necessary to understand and mitigate failures that can occur due to localized corrosion events. Mechanical and electrochemical stresses interacting with a microstructural heterogeneity can result in the rapid growth of a flaw in the material; this phenomenon is a form of environmentally assisted cracking (EAC). One possible mechanism of EAC in Al-Li-X alloys is the preferential dissolution of an electrochemically active microstructural feature along a grain or sub-grain boundary. To examine this mechanis

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Sturrock, C. P., and W. F. Bogaerts. "Classification and Prediction of Corrosion Phenomena via Cluster Analysis." In CORROSION 1996. NACE International, 1996. https://doi.org/10.5006/c1996-96383.

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Abstract The data that describe corrosion phenomena in terms of individual cases and feature values specify a mapping onto an abstract multidimensional feature space. Regions of high density, or clusters, signify areas of interest, and possibly, similar corrosion phenomena. This paper describes a method for calculating the similarity between cases based on a generalized measure of Euclidean distance. Evidence for a correlation between this similarity and observed corrosion phenomena is presented for a real-world database on chloride stress corrosion cracking (SCC) of Type 304 stainless steel i

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Yu, Mengshan, Yanping Li, Trevor Place, and Adrian Gosselin. "External Corrosion Behavior of Oil Pipelines with Polyethylene Coating under Pressure Fluctuations." In CORROSION 2019. NACE International, 2019. https://doi.org/10.5006/c2019-13199.

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Abstract External corrosion on buried pipe steels has been demonstrated to be a major threat to pipeline integrity. Although it has been extensively investigated and well understood electrochemically, there is no particular corrosion rate model that is widely accepted by industry due to the complexities associated with coating performance, and heterogeneity of the soil environment (including bacteria, drainage, bulk resistivity, CP level, etc.). This paper demonstrates that the severity of external corrosion on Polyethylene (PE) tape coated oil pipe is exacerbated by the proximity to upstream

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Li, Jiateng, Zhao Liu, and Yaping Lai. "Structural Behavior of a Long-span Half-through Arch Bridge: Network Hangers versus Vertical Hangers." In IABSE Symposium, Tokyo 2025: Environmentally Friendly Technologies and Structures: Focusing on Sustainable Approaches. International Association for Bridge and Structural Engineering (IABSE), 2025. https://doi.org/10.2749/tokyo.2025.0429.

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<p>Half-through arch bridges feature a roadway deck passing through the mid-height of the arch, and the choice of the hanger arrangement requires a comprehensive study of structural performance and aesthetics. With a 470m-span half-through arch bridge across the Yangtze River in China as a target bridge, this paper establishes two analysis models using network and vertical hangers based on the design parameters. The differences between the two arrangements are evaluated regarding the static response under typical loads, fatigue stress of hangers, natural vibration characteristics, and ma

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Lu, Li, Jia He, Zhijie Xu, et al. "Crowd behavior understanding through SIOF feature analysis." In 2017 23rd International Conference on Automation and Computing (ICAC). IEEE, 2017. http://dx.doi.org/10.23919/iconac.2017.8082086.

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Dai, Yuwen, Peng Zhang, Tianqi Wu, et al. "User Identification based on Behavior Feature Analysis." In 2023 7th International Conference on Electrical, Mechanical and Computer Engineering (ICEMCE). IEEE, 2023. http://dx.doi.org/10.1109/icemce60359.2023.10490778.

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Sarkar, Sayantan, Vishal M. Patel, and Rama Chellappa. "Deep feature-based face detection on mobile devices." In 2016 IEEE International Conference on Identity, Security and Behavior Analysis (ISBA). IEEE, 2016. http://dx.doi.org/10.1109/isba.2016.7477230.

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Звіти організацій з теми "Feature behavior analysis"

Lalisse, Matthias. Measuring the Impact of Campaign Finance on Congressional Voting: A Machine Learning Approach. Institute for New Economic Thinking Working Paper Series, 2022. http://dx.doi.org/10.36687/inetwp178.

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How much does money drive legislative outcomes in the United States? In this article, we use aggregated campaign finance data as well as a Transformer based text embedding model to predict roll call votes for legislation in the US Congress with more than 90% accuracy. In a series of model comparisons in which the input feature sets are varied, we investigate the extent to which campaign finance is predictive of voting behavior in comparison with variables like partisan affiliation. We find that the financial interests backing a legislator’s campaigns are independently predictive in both chambe

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Jury, William A., and David Russo. Characterization of Field-Scale Solute Transport in Spatially Variable Unsaturated Field Soils. United States Department of Agriculture, 1994. http://dx.doi.org/10.32747/1994.7568772.bard.

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This report describes activity conducted in several lines of research associated with field-scale water and solute processes. A major effort was put forth developing a stochastic continuum analysis for an important class of problems involving flow of reactive and non reactive chemicals under steady unsaturated flow. The field-scale velocity covariance tensor has been derived from local soil properties and their variability, producing a large-scale description of the medium that embodies all of the local variability in a statistical sense. Special cases of anisotropic medium properties not alig

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Dinovitzer, Aaron, Brian Leis, Ravi Krishnamurthy, Chris Alexander, and Mures Zarea. PR214-203804-R01 Systematize 20 Years of Mechanical Damage Research. Pipeline Research Council International, Inc. (PRCI), 2022. http://dx.doi.org/10.55274/r0012226.

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This research was funded in part under the Department of Transportation, Pipeline and Hazardous Materials Safety Administration's Pipeline Safety Research and Development Program. The views and conclusions contained in this document are those of the authors and should not be interpreted as representing the official policies, either expressed or implied, of the Pipeline and Hazardous Materials Safety Administration, or the U.S. Government. Research over the past 20 years has improved the pipeline industry's understanding of the behavior and failure processes for mechanical damage. This new unde

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Osadchyi, Viacheslav V., Hanna B. Varina, Kateryna P. Osadcha, Olesia O. Prokofieva, Olha V. Kovalova, and Arnold E. Kiv. Features of implementation of modern AR technologies in the process of psychological and pedagogical support of children with autism spectrum disorders. [б. в.], 2020. http://dx.doi.org/10.31812/123456789/4413.

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The article deals with the actual issue of the specificity and algorithm of the introduction of innovative AR technologies in the process of psychological and pedagogical support of children with autism spectrum disorders (ASD). An innovative element of theoretical and methodological analysis of the problem and empirical research is the detection of vectors of a constructive combination of traditional psycho-correctional and psycho-diagnostic approaches with modern AR technologies. The analysis of publications on the role and possibilities of using AR technologies in the process of support chi

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Maceira, Daniel, and Maria Victoria Murillo. Social Sector Reform in Latin America and the Role of Unions. Inter-American Development Bank, 2001. http://dx.doi.org/10.18235/0010797.

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This paper analyzes the reaction of teachers' and doctors' unions to a series of social sector reforms in the region, including administrative decentralization, provider payment mechanisms, and the introduction of performance evaluation and private provision. It combines the literature of economics and political science to understand the conditions that shape different patterns of union behavior and their effect on policy implementation. The paper suggests that the main conditions influencing union behavior in the health sector are related to the structure of the market (size and level of comp

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Maranghides, A. Initial Reconnaissance of the 2011 Wildland-Urban Interfaces Fires in Amarillo, Texas. National Institute of Standards and Technology, 2011. http://dx.doi.org/10.6028/nist.tn.1708.

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The National Institute of Standards and Technology (NIST) is working to reduce the risk of fire spread in Wildland-Urban Interface (WUI) communities. An objective of this work is to develop first generation tools for improved risk assessment and risk mitigation in WUI communities at risk from wildfires. These tools will be developed and tested through a coordinated effort that includes laboratory and field measurements, physics-based fire behavior models, and economic cost analysis models. NIST and Texas Forest Service (TFS) worked together in October 2010 to train TFS personnel in the NIST-de

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O'Connor, Jack, Caitlyn Eberle, Liliana Narvaez, et al. Interconnected Disaster Risks. United Nations University - Institute for Environment and Human Security (UNU-EHS), 2022. http://dx.doi.org/10.53324/usdg7258.

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The 2021/2022 edition of the Interconnected Disaster Risks report analyses 10 disasters from around the world and explains that these events are interconnected with each other, with other larger, underlying societal processes, and with our collective behaviors and actions. Through forensic analysis, the key root causes featured among the 10 cases were an Insufficient risk governance, related to laws and practices that perpetuated or created complications in the formation of the disaster, and Undervaluing environmental costs, signifying the tendency to prioritize the economic costs of an endeav

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PEREMANS, Herbert, Glen McLACHLAN, Piotr MAJDAK, and Jonas REIJNIERS. Ideal versus non-ideal observer models for sound localization. Verlag der Österreichischen Akademie der Wissenschaften, 2025. https://doi.org/10.1553/ica_2022_observer-models.

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Previously we derived an information theoretic measure to quantify sound localization performance complementing measures such as angular error and number of front-back confusions. It is based on Bayesian inference to derive the probability sound originates from particular directions given received acoustic input and prior information about possible source locations. In this model, we considered the joint probability of lateral and polar angles of the sound direction using ITD and both left and right monaural spectra as acoustic input. Ideally, all acoustic information is being considered when

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Steinbock, Thilo, and Klemens Kerssen. Evaluation on the capabilities of MATLAB Simulink’s Embedded Coder for rapid prototyping of micro-controller based control systems for switching converters. Universitatsbibliothek Kiel, 2025. https://doi.org/10.38071/2025-00178-9.

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Switching converters play a crucial role in modern power electronics, offering efficient voltage conversion in various electronic devices. This paper presents an approach to the rapid prototyping for micro-controller based control systems, applied to the buck-converter topology. The methodology utilized features from MATLAB Simulink and it’s Embedded Coder extension to model and implement the control system, enabling a simplified transition from simulation to hardware implementation. For this purpose the paper evaluates two control systems, namely the error-amplifier and the PID controller. Co

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Diehl, Rebecca, Jonathan Friedman, Rebecca Diehl, and Jonathan Friedman. Modelling effects of flow withdrawal scenarios on riverine and riparian features of the Yampa River in Dinosaur National Monument. National Park Service, 2024. http://dx.doi.org/10.36967/2305338.

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The National Park Service (NPS) is charged with maintaining natural riverine resources and processes in its parks along the Yampa River and downstream along the Green River. This mission requires information on how proposed water withdrawals would affect resources. We present a methodology that quantifies the impact on natural riverine and riparian features of Dinosaur National Monument based on alternative withdrawals that vary in volume and timing. This methodology uses a reverse quantification and develops tools to enable the NPS to ensure that if withdrawals must occur, the adverse impacts

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