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Journal articles on the topic 'Navigation behavior patterns'

Author: Grafiati

Published: 3 June 2025

Last updated: 31 July 2025

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1

Graves, Kathryn N., James W. Antony, and Nicholas B. Turk-Browne. "Finding the Pattern: On-Line Extraction of Spatial Structure During Virtual Navigation." Psychological Science 31, no. 9 (2020): 1183–90. http://dx.doi.org/10.1177/0956797620948828.

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While navigating the world, we pick up on patterns of where things tend to appear. According to theories of memory and studies of animal behavior, knowledge of these patterns emerges gradually over days or weeks via consolidation of individual navigation episodes. Here, we discovered that navigation patterns can also be extracted on-line, prior to the opportunity for off-line consolidation, as a result of rapid statistical learning. Thirty human participants navigated a virtual water maze in which platform locations were drawn from a spatial distribution. Within a single session, participants

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Gamon, Michael, and Arnd König. "Navigation Patterns from and to Social Media." Proceedings of the International AAAI Conference on Web and Social Media 3, no. 1 (2009): 203–6. http://dx.doi.org/10.1609/icwsm.v3i1.13960.

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With the rapid rise of social media content, the question how people navigate to and from social media becomes important in order to understand what new tools and approaches are most beneficial to allow users to discover and interact with this social media data. In this study we analyze session log data to describe navigation patterns involving these sites. Our findings suggest that there are distinct patterns of insular navigation behavior around social media, with blogs being the most transitory in the way users interact with them.

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Issa, John B., Gilad Tocker, Michael E. Hasselmo, James G. Heys, and Daniel A. Dombeck. "Navigating Through Time: A Spatial Navigation Perspective on How the Brain May Encode Time." Annual Review of Neuroscience 43, no. 1 (2020): 73–93. http://dx.doi.org/10.1146/annurev-neuro-101419-011117.

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Interval timing, which operates on timescales of seconds to minutes, is distributed across multiple brain regions and may use distinct circuit mechanisms as compared to millisecond timing and circadian rhythms. However, its study has proven difficult, as timing on this scale is deeply entangled with other behaviors. Several circuit and cellular mechanisms could generate sequential or ramping activity patterns that carry timing information. Here we propose that a productive approach is to draw parallels between interval timing and spatial navigation, where direct analogies can be made between t

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Vesna, Kumbaroska, and Mitrevski Pece. "BRAIN Journal - Exploring User Engagement in Information Networks: Behavioural – based Navigation Modelling, Ideas and Directions." BRAIN - Broad Research in Artificial Intelligence and Neuroscience 7, no. 4 (2016): 93–107. https://doi.org/10.5281/zenodo.1044986.

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ABSTRACT Revealing an endless array of user behaviors in an online environment is a very good indicator of the user’s interests either in the process of browsing or in purchasing. One such behavior is the navigation behavior, so detected user navigation patterns are able to be used for practical purposes such as: improving user engagement, turning most browsers into buyers, personalize content or interface, etc. In this regard, our research represents a connection between navigation modelling and user engagement. A usage of the Generalized Stochastic Petri Nets concept for stochastic behaviora

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Laor, Tal, and Yair Galily. "In WAZE we trust? GPS-based navigation application users’ behavior and patterns of dependency." PLOS ONE 17, no. 11 (2022): e0276449. http://dx.doi.org/10.1371/journal.pone.0276449.

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Functional technological applications have become an integral part of our lives changing our patterns of reasoning and behavior. The current study examines whether, how and why use of WAZE app, a popular GPS-based navigation application, demonstrate behaviors and patterns which resemble those of technological dependency. We conducted semi-structured in-depth interviews with 50 WAZE users. The questions took inspiration from the model of IT addiction, which identifies six behavioral parameters: withdrawal, conflict, mood modification, relapse, tolerance, and saliency. The novelty of the study l

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Ho, Tang Swee, Goh Chok How, Yeong Che Fai, Tey Wei Kang, and Eileen Su Lee Ming. "Vision Recognition on Line Pattern Following Behavior on POB-Bot." Applied Mechanics and Materials 432 (September 2013): 453–57. http://dx.doi.org/10.4028/www.scientific.net/amm.432.453.

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Robust development in the industries had lead to the fast development of the robots and sensors. Mobile robot is able to replace human power for many things due to its low cost and high accuracy. Types of navigation of the mobile robot had been in the research for past decades, the simplest and straight forward method of mobile robot navigation will be line following. Line following basically allows the robot to move along the predefined line. This paper is proposing a novel method of line following for more functions for mobile robot. 12 patterns have been defined to perform different functio

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N.Sanfia, Sehnaz* Dr.I.Elizabeth Shanthi. "MINING OF WEB LOG FILES USING RELEVANT COMPUTING TECHNIQUES FOR IMPROVING FUTURE ANTICIPATION USAGE OF WEB NAVIGATION." INTERNATIONAL JOURNAL OF ENGINEERING SCIENCES & RESEARCH TECHNOLOGY 5, no. 5 (2016): 536–41. https://doi.org/10.5281/zenodo.51534.

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The Internet has evolved extensively over the past few decades. Web navigation refers to the process of navigating a network of information resources in the World Wide Web, which is organized as hypertext or hypermedia.  The navigation related to web navigation usability gets solved by comparing the actual and anticipated usage patterns. The actual usage pattern removed from web server logs are sporadically recorded in operational websites for handling the log data. This process is used to identify the users, user session and user task oriented transactions. The pattern can be discovered

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Raissa, Paula, Sérgio Dias, Mark Song, and Luis Zárate. "Minimal implications base for social network analysis." International Journal of Web Information Systems 14, no. 1 (2018): 62–77. http://dx.doi.org/10.1108/ijwis-04-2017-0028.

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Purpose Currently, social network (SN) analysis is focused on the discovery of activity and social relationship patterns. Usually, these relationships are not easily and completely observed. Therefore, it is relevant to discover substructures and potential behavior patterns in SN. Recently, formal concept analysis (FCA) has been applied for this purpose. FCA is a concept analysis theory that identifies concept structures within a data set. The representation of SN patterns through implication rules based on FCA enables the identification of relevant substructures that cannot be easily identifi

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Li, Jinhao. "Intelligent Algorithm Deep Learning Reinforcement Learning Module Integrated into the Navigation System to Enhance the Ability of Navigation to Accurately Serve Users." MATEC Web of Conferences 410 (2025): 04014. https://doi.org/10.1051/matecconf/202541004014.

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In the increasingly competitive automotive industry, the in - car navigation system, a crucial aspect of the user experience, demands greater personalization and intelligence. This research aims to design a navigation system that better caters to users’ needs, thereby enhancing the driving experience and user satisfaction. The research employs a combination of user research, data analysis, and prototype design methods. Initially, the navigation requirements of different user groups are gathered through questionnaire surveys and user interviews. Subsequently, machine - learning algorithms are u

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Gao, Miao, Guoyou Shi, and Shuang Li. "Online Prediction of Ship Behavior with Automatic Identification System Sensor Data Using Bidirectional Long Short-Term Memory Recurrent Neural Network." Sensors 18, no. 12 (2018): 4211. http://dx.doi.org/10.3390/s18124211.

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The real-time prediction of ship behavior plays an important role in navigation and intelligent collision avoidance systems. This study developed an online real-time ship behavior prediction model by constructing a bidirectional long short-term memory recurrent neural network (BI-LSTM-RNN) that is suitable for automatic identification system (AIS) date and time sequential characteristics, and for online parameter adjustment. The bidirectional structure enhanced the relevance between historical and future data, thus improving the prediction accuracy. Through the “forget gate” of the long short-

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Nakirikanti, Santosh. "Leveraging User Behavior Analytics for Advanced E-Commerce Fraud Detection." European Journal of Computer Science and Information Technology 13, no. 7 (2025): 74–93. https://doi.org/10.37745/ejcsit.2013/vol13n77493.

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E-commerce platforms face the critical challenge of balancing seamless customer experiences with robust security measures to prevent fraud. Traditional rule-based detection systems have proven increasingly inadequate against sophisticated threats, generating excessive false positives while missing complex fraud attempts. This article explores how behavioral analytics transforms fraud prevention by analyzing digital footprints customers leave while navigating online stores. By leveraging machine learning algorithms to establish behavioral baselines and detect anomalies, merchants can identify f

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Dingus, Thomas A., Jonathan P. Antin, Melissa C. Hulse, and Walter w. Wierwille. "Human Factors Issues Associated with in-Car Navigation System Usage." Proceedings of the Human Factors Society Annual Meeting 32, no. 19 (1988): 1448–52. http://dx.doi.org/10.1177/154193128803201930.

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Two research studies were recently performed to evaluate and test human factors aspects of a commercially available in-car navigation system. The first study addressed the driver visual attentional demand requirements of the system and its effects on driving performance and behavior. The second study addressed the effectiveness of the system as a navigation tool as well as methodological aspects of navigation. The results of the first study indicate that several tasks performed during navigation required high visual attentional demand. Design changes are discussed which would likely reduce thi

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Youn, Ik-Hyun, and Jung-Min Lee. "Seafarers’ Physical Activity and Sleep Patterns: Results from Asia-Pacific Sea Routes." International Journal of Environmental Research and Public Health 17, no. 19 (2020): 7266. http://dx.doi.org/10.3390/ijerph17197266.

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Prolonged ocean voyages constrain the regular physical activity and sleep patterns of seafarers. However, there is a lack of information on seafarers’ physical activity and sleep behavior. The purpose of this study was to systematically examine physical activity and sleep patterns among seafarers using a single wrist-worn accelerometer. Fifty-one senior maritime students (mean age = 22.8 years; 80.0% male) in a university navigation department participated in the study. Data were collected from participants on three sea voyages in the Asia-Pacific region. Indicators of moderate to vigorous int

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Zhang, Jun, Enze Wu, and Taizhi Lv. "Research on Anomaly Detection of Ship Behavior Based on Data Mining." Frontiers in Science and Engineering 4, no. 10 (2024): 133–41. http://dx.doi.org/10.54691/yzaagq42.

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With the increase in the number of ships and the intensifying maritime traffic, maritime accidents such as ship collisions and grounding occur frequently, posing serious threats to people's lives and property. Therefore, timely detection and correction of abnormal ship behaviors are of great significance for improving navigation safety. The Automatic Identification System (AIS) can provide real-time information on ships' positions, speeds, headings, and more, offering a rich data resource for data mining. Through the analysis of these data, it is possible to deeply explore the navigation patte

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Lou, Jingfeng, and Aiguo Cheng. "Detecting Pattern Changes in Individual Travel Behavior from Vehicle GPS/GNSS Data." Sensors 20, no. 8 (2020): 2295. http://dx.doi.org/10.3390/s20082295.

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Although stable in the short term, individual travel behavior generally tends to change over the long term. The ability to detect such changes is important for product and service providers in continuously changing environments. The aim of this paper is to develop a methodology that detects changes in the patterns of individual travel behavior from vehicle global positioning system (GPS)/global navigation satellite system (GNSS) data. For this purpose, we first define individual travel behavior patterns in two dimensions: a spatial pattern and a frequency pattern. Then, we develop a method tha

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Raposo-Rivas, Manuela, Mª Esther Martínez-Figueira, José Antonio Sarmiento-Campos, and Angeles Parrilla Latas. "Teens' Behavior Patterns on the Web: Surfing or Wrecking?" Digital Education Review, no. 39 (July 1, 2021): 60–75. http://dx.doi.org/10.1344/der.2021.39.60-75.

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Adolescents’ relationship with technology is controversial both because of the possibilities it offers and because of the risks it entails, even being perceived by them as a real need. In order to improve the knowledge about it, a non-experimental research of transversal style has been carried out using a methodology based on data mining. 1,048 students of Secondary Education participated and answered a questionnaire about their use of the Internet and social networks. Six factors were indentified, which could be recognized as patterns of behavior in the network. They are grouped around: (1) t

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Chen, Shuzhe, Chong Zhang, Lei Wu, et al. "Collision Avoidance Behavior Mining Model Considering Encounter Scenarios." Applied Sciences 15, no. 5 (2025): 2616. https://doi.org/10.3390/app15052616.

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With the development of intelligent waterborne transportation, mining collision avoidance patterns based on spatiotemporal and motion data of ships are crucial for the autonomous navigation of intelligent ships, which requires accurate collision avoidance information under various encounter scenarios. Addressing the existing issues of low precision and false detection in data mining algorithms, this paper proposes a collision avoidance behavior mining model considering encounter scenarios. The model is based on the Automatic Identification System (AIS) and the International Regulations for Pre

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Mukesh Kumar, Dharminder Kumar. "Analysing User Navigation Patterns through Association Rule Mining and Clustering: A Case Study on Web Server Logs." Journal of Information Systems Engineering and Management 10, no. 38s (2025): 50–65. https://doi.org/10.52783/jisem.v10i38s.6823.

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Web usage mining improves the efficiency and personalization of Web-based services by using data mining techniques to identify patterns in user activity from Web log data. Preprocessing, pattern finding, and pattern analysis are its three primary stages. Among other methods, association rule mining is essential for identifying connections between user actions or viewed web sites. In addition to offering a thorough taxonomy of current research and commercial systems in the field, this study investigates the application of association rule mining within the larger framework of Web usage mining.

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Klein, Mason, Bruno Afonso, Ashley J. Vonner, et al. "Sensory determinants of behavioral dynamics in Drosophila thermotaxis." Proceedings of the National Academy of Sciences 112, no. 2 (2014): E220—E229. http://dx.doi.org/10.1073/pnas.1416212112.

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Complex animal behaviors are built from dynamical relationships between sensory inputs, neuronal activity, and motor outputs in patterns with strategic value. Connecting these patterns illuminates how nervous systems compute behavior. Here, we study Drosophila larva navigation up temperature gradients toward preferred temperatures (positive thermotaxis). By tracking the movements of animals responding to fixed spatial temperature gradients or random temperature fluctuations, we calculate the sensitivity and dynamics of the conversion of thermosensory inputs into motor responses. We discover th

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Wahjoedi, Wahjoedi, Magistyo Purboyo Priambodo, Ni'matul Istiqomah, Emma Yunika Puspasari, and Fariha Nuraini. "The Intersection between Environmentally Friendly Consumption Behavior and Students' Ability to Utilize Information and Technology in Accelerating the National Green Economy." Proceedings Of International Conference On Communication Science 3, no. 1 (2024): 16–28. http://dx.doi.org/10.29303/iccsproceeding.v3i1.822.

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Realizing a green economy in Indonesia can be achieved through environmentally friendly consumption starting with the younger generation. Students as part of consumers need to apply environmentally friendly consumption patterns as a contribution to the national green economy. This study seeks to analyze how the variables of insight into food and beverages, attitudes towards environmentally friendly consumption behavior, the tendency of environmentally friendly consumption behavior, IT technical and operational skills, IT navigation and processing skills, and IT communication skills influence e

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Ramesh, C., K. V. Chalapathi Rao, and A. Govardhan. "Using Domain Ontology and Sequential Rule Mining for Extracting Behavior Patterns from Web Navigation Logs." CVR Journal of Science & Technology 7, no. 1 (2014): 8–12. http://dx.doi.org/10.32377/cvrjst0702.

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Huang, Liwen, Jiahao Chen, Luping Xu, Haoyu Li, Guozhu Hao, and Yixiong He. "Research on Decision-Making Methods for Autonomous Navigation in Inland Tributary Waterways." Applied Sciences 15, no. 7 (2025): 3823. https://doi.org/10.3390/app15073823.

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The inherent complexity of traffic patterns in inland river tributary waterways presents significant challenges in predicting ship behavior, resulting in elevated accident risks compared to general waterways. With the intelligent development of inland navigation, conducting research on autonomous navigation decision-making for tributary waterway ships is crucial to improving navigation safety and efficiency. Based on the characteristics of the navigation environment, a digital traffic environment model for inland waterways with tributaries is constructed to meet the information requirements of

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Ramanathaiah, Ramakrishnan M., Bhawna Nigam, and M. Niranjanamurthy. "Construction of User’s Navigation Sessions from Web Logs for Web Usage Mining." Journal of Computational and Theoretical Nanoscience 17, no. 9 (2020): 4432–37. http://dx.doi.org/10.1166/jctn.2020.9091.

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Web Usage Mining applies fewer techniques in record data to pull out the behavior of users. The knowledge mined from the web log can be utilized in web personalization, Prediction, prefetching, restructuring of web sites etc. It consists of three steps in preprocessing, pattern detection and analysis. Web log information is typically noisy and uncertain and preprocessing is a significant process ahead of mining. The Patterns discovered after applying the mining techniques are dependent on the accuracy of the weblog which in turn depends on the preprocessing phase. The output of preprocessing s

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Jackermeier, Robert, and Bernd Ludwig. "Smartphone-Based Activity Recognition in a Pedestrian Navigation Context." Sensors 21, no. 9 (2021): 3243. http://dx.doi.org/10.3390/s21093243.

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In smartphone-based pedestrian navigation systems, detailed knowledge about user activity and device placement is a key information. Landmarks such as staircases or elevators can help the system in determining the user position when located inside buildings, and navigation instructions can be adapted to the current context in order to provide more meaningful assistance. Typically, most human activity recognition (HAR) approaches distinguish between general activities such as walking, standing or sitting. In this work, we investigate more specific activities that are tailored towards the use-ca

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Hoffmann, Susanne, Daria Genzel, Selina Prosch, et al. "Biosonar navigation above water I: estimating flight height." Journal of Neurophysiology 113, no. 4 (2015): 1135–45. http://dx.doi.org/10.1152/jn.00263.2014.

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Locomotion and foraging on the wing require precise navigation in more than just the horizontal plane. Navigation in three dimensions and, specifically, precise adjustment of flight height are essential for flying animals. Echolocating bats drink from water surfaces in flight, which requires an exceptionally precise vertical navigation. Here, we exploit this behavior in the bat, Phyllostomus discolor, to understand the biophysical and neural mechanisms that allow for sonar-guided navigation in the vertical plane. In a set of behavioral experiments, we show that for echolocating bats, adjustmen

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Ma, Jie, Wenkai Li, Chengfeng Jia, Chunwei Zhang, and Yu Zhang. "Risk Prediction for Ship Encounter Situation Awareness Using Long Short-Term Memory Based Deep Learning on Intership Behaviors." Journal of Advanced Transportation 2020 (November 29, 2020): 1–15. http://dx.doi.org/10.1155/2020/8897700.

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Encounter risk prediction is critical for safe ship navigation, especially in congested waters, where ships sail very near to each other during various encounter situations. Prior studies on the risk of ship collisions were unable to address the uncertainty of the encounter process when ignoring the complex motions constituting the dynamic ship encounter behavior, which may seriously affect the risk prediction performance. To fill this gap, a novel AIS data-driven approach is proposed for ship encounter risk prediction by modeling intership behavior patterns. In particular, multidimensional fe

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Dettmers, John M., Steve Gutreuter, David H. Wahl, and Daniel A. Soluk. "Patterns in abundance of fishes in main channels of the upper Mississippi River system." Canadian Journal of Fisheries and Aquatic Sciences 58, no. 5 (2001): 933–42. http://dx.doi.org/10.1139/f01-046.

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Abundance of fishes of the main channels of the upper Mississippi River system and of other large North American rivers is largely unknown because historic sampling methods have been inadequate. We used a bottom trawl to estimate spatial and temporal patterns in abundance in the navigation channels of Pool 26 of the Mississippi River and the lower Illinois River. Total biomass density averaged 21 and 29 kg·ha1 in the navigation channels of Pool 26 and the lower Illinois River, respectively. We identified spatial and temporal patterns in catches of key species using a generalized linear model

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Hu, Pengwei, Panpan Huang, Zhenbing Qiu, Jian Yang, and Xin Liu. "A 3D Attitude Estimation Method Based on Attitude Angular Partial Feedback for Polarization-Based Integrated Navigation System." Sensors 22, no. 3 (2022): 710. http://dx.doi.org/10.3390/s22030710.

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Polarization (POL) navigation is inspired by insects’ behavior of precepting celestial polarization patterns to orient themselves. It has the advantages of being autonomous and having no accumulative error, which allows it to be used to correct the errors of the inertial navigation system (INS). The integrated navigation system of the POL-based solar vector with INS is capable of 3D attitude determination. However, the commonly used POL-based integrated navigation system generally implements the attitude update procedure without considering the performance difference with different magnitudes

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Kuhar, Maja, and Tanja Merčun. "Navigating an Online Bookstore: User Experience Insights from Eye- Tracking and Think-Aloud." KNOWLEDGE ORGANIZATION 51, no. 5 (2024): 320–29. http://dx.doi.org/10.5771/0943-7444-2024-5-320.

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Navigating online bookstores and library catalogues for leisure reading can be challenging, especially when people want to engage in a more exploratory and serendipitous search. This study investigated how users navigate and select novels in an online bookstore environment, focusing on the impact of individual user interface elements and information architecture on their experience. Employing a combination of screen recordings with eye-tracking and concurrent think-aloud, the study examined user interactions to understand their navigation patterns, emotional responses, and perceptions related

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Zheng, Lili, Tian Gao, Lin Meng, Tongqiang Ding, and Wenhao Chen. "Research on the Route Choice Behavior of Urban Freight Vehicles Based on GPS Data." Mathematics 12, no. 2 (2024): 291. http://dx.doi.org/10.3390/math12020291.

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In order to provide urban freight vehicles with navigation routes that better align with their travel preferences, it is necessary to analyze the patterns and characteristics of their route choices. This paper focuses on freight vehicles traveling within the city and examines their route selection behavior. Through an analysis of the GPS data collected from freight truck journeys in Changchun, China, this study outlines the characteristics of freight vehicle travel within the city. Variables that may influence their route selection behavior are defined as feature factors. The study employs the

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Mukhamadiev, Timur, Zafar Adilov, Zayd Balassem, Mahadevan P, Feruza Shoimova, and Priya Vij. "Impact of underwater noise pollution from maritime traffic on marine mammal communication patterns." International Journal of Aquatic Research and Environmental Studies 5, S1 (2025): 143–51. https://doi.org/10.70102/ijares/v5s1/5-s1-15.

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This paper focuses on the effect of noise pollution on the communication of marine mammals. Animals such as whales, dolphins, and seals use sound for navigation, socializing, and reproduction, making them Oceano zoological. Their survival, ecological interaction, and social structure rely heavily on marine acoustics. Human activities like shipping traffic, military sonar or offshore drilling, and seismic surveying cause noise pollution that interferes with marine life communication. The masking of signals severely impacts marine mammals’ communication and the behaviors necessary to feed, mate,

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Nitish Ratan Appanasamy. "Leveraging Implicit User Feedback in Enterprise Search Retrieval Systems." International Journal of Scientific Research in Computer Science, Engineering and Information Technology 11, no. 2 (2025): 2648–53. https://doi.org/10.32628/cseit25112737.

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Enterprise search systems are fundamentally transforming organizational knowledge management through sophisticated integration of implicit user feedback mechanisms. These advanced systems harness complex user behavior patterns, including detailed click-through rates, engagement time measurements, and comprehensive navigation path analyses. The implementation of refined filtering techniques and position bias compensation methods enables significantly more accurate content discovery while effectively reducing redundant information access. Modern query expansion strategies and real-time click min

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Weinberg, Alysse. "Web Tracking and Students' Work Patterns in Online Language-learning Activities." CALICO Journal 25, no. 1 (2013): 31–47. http://dx.doi.org/10.1558/cj.v25i1.31-47.

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In previous publications the author reported on the use of a website dedicated to French songs for an advanced French comprehension course at the university level. The present article analyzes web-tracking data captured from the website over two terms--fall 2003 and winter 2004. The variations in the amount of time students spent working on the online activities and their online behavior as they navigated through the Chansons de la francophonie web activities are presented. Research queries are made into the data to explore web behavior differences between day and evening students, male and fe

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Clem, Timothy, and Patrick Thomson. "Static Analysis at GitHub." Queue 19, no. 4 (2021): 42–67. http://dx.doi.org/10.1145/3487019.3487022.

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The Semantic Code team at GitHub builds and operates a suite of technologies that power symbolic code navigation on github.com. We learned that scale is about adoption, user behavior, incremental improvement, and utility. Static analysis in particular is difficult to scale with respect to human behavior; we often think of complex analysis tools working to find potentially problematic patterns in code and then trying to convince the humans to fix them. Our approach took a different tack: use basic analysis techniques to quickly put information that augments our ability to understand programs in

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Migdał, Paweł, Ewelina Berbeć, Paweł Bieńkowski, Mateusz Plotnik, Agnieszka Murawska, and Krzysztof Latarowski. "Exposure to Magnetic Fields Changes the Behavioral Pattern in Honeybees (Apis mellifera L.) under Laboratory Conditions." Animals 12, no. 7 (2022): 855. http://dx.doi.org/10.3390/ani12070855.

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Earth’s magnetic field (MF) plays an important role for many species, including the honeybee, in navigation. Nowadays, much larger alternating fields are emitted by miscellaneous electric infrastructure components, such as transformers and power lines, and the environment is therefore polluted by an anthropogenic electromagnetic field, though little is known regarding its impact on living organisms. The behavior of animals is the first and easiest way to establish the impact of stress. It shows if the animal can detect the exposure and react to it. To investigate this, one-day-old bees were ex

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Yi, Chuho, Young Ceol Oh, Il Hong Suh, and Byung-Uk Choi. "Indoor Place Classification Using Robot Behavior and Vision Data." International Journal of Advanced Robotic Systems 8, no. 5 (2011): 61. http://dx.doi.org/10.5772/45699.

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To realize autonomous navigation of intelligent robots in a variety of settings, analysis and classification of places, and the ability to actively collect information are necessary. In this paper, visual data are organized into an orientation histogram to roughly express input images by extracting and cumulating straight lines according to direction angle. In addition, behavioral data are organized into a behavioral histogram by cumulating motions performed to avoid obstacles encountered while the robot is executing specified behavioral patterns. These visual and behavioral data are utilized

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Wang, Mengni, David J. Foster, and Brad E. Pfeiffer. "Alternating sequences of future and past behavior encoded within hippocampal theta oscillations." Science 370, no. 6513 (2020): 247–50. http://dx.doi.org/10.1126/science.abb4151.

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Neural networks display the ability to transform forward-ordered activity patterns into reverse-ordered, retrospective sequences. The mechanisms underlying this transformation remain unknown. We discovered that, during active navigation, rat hippocampal CA1 place cell ensembles are inherently organized to produce independent forward- and reverse-ordered sequences within individual theta oscillations. This finding may provide a circuit-level basis for retrospective evaluation and storage during ongoing behavior. Theta phase procession arose in a minority of place cells, many of which displayed

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Huang, I.-Lun, Man-Chun Lee, Li Chang, and Juan-Chen Huang. "Development and Application of an Advanced Automatic Identification System (AIS)-Based Ship Trajectory Extraction Framework for Maritime Traffic Analysis." Journal of Marine Science and Engineering 12, no. 9 (2024): 1672. http://dx.doi.org/10.3390/jmse12091672.

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This study addresses the challenges of maritime traffic management in the western waters of Taiwan, a region characterized by substantial commercial shipping activity and ongoing environmental development. Using 2023 Automatic Identification System (AIS) data, this study develops a robust feature extraction framework involving data cleaning, anomaly trajectory point detection, trajectory compression, and advanced processing techniques. Dynamic Time Warping (DTW) and the Hierarchical Density-Based Spatial Clustering of Applications with Noise (HDBSCAN) algorithms are applied to cluster the traj

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Foxman, Ellen F., James J. Campbell, and Eugene C. Butcher. "Multistep Navigation and the Combinatorial Control of Leukocyte Chemotaxis." Journal of Cell Biology 139, no. 5 (1997): 1349–60. http://dx.doi.org/10.1083/jcb.139.5.1349.

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Cells migrating within tissues may encounter multiple chemoattractant signals in complex spatial and temporal patterns. To understand leukocyte navigation in such settings, we have explored the migratory behavior of neutrophils in model scenarios where they are presented with two chemoattractant sources in various configurations. We show that, over a wide range of conditions, neutrophils can migrate “down” a local chemoattractant gradient in response to a distant gradient of a different chemoattractant. Furthermore, cells can chemotax effectively to a secondary distant agonist after migrating

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Reiter, Sam, Hua-Peng Liaw, Tracy M. Yamawaki, Robert K. Naumann, and Gilles Laurent. "On the Value of Reptilian Brains to Map the Evolution of the Hippocampal Formation." Brain, Behavior and Evolution 90, no. 1 (2017): 41–52. http://dx.doi.org/10.1159/000478693.

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Our ability to navigate through the world depends on the function of the hippocampus. This old cortical structure plays a critical role in spatial navigation in mammals and in a variety of processes, including declarative and episodic memory and social behavior. Intense research has revealed much about hippocampal anatomy, physiology, and computation; yet, even intensely studied phenomena such as the shaping of place cell activity or the function of hippocampal firing patterns during sleep remain incompletely understood. Interestingly, while the hippocampus may be a ‘higher order' area linked

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Lambert, Jacob, Leslie Liang, Luis Yoichi Morales, et al. "Tsukuba Challenge 2017 Dynamic Object Tracks Dataset for Pedestrian Behavior Analysis." Journal of Robotics and Mechatronics 30, no. 4 (2018): 598–612. http://dx.doi.org/10.20965/jrm.2018.p0598.

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Navigation in social environments, in the absence of traffic rules, is the difficult task at the core of the annual Tsukuba Challenge. In this context, a better understanding of the soft rules that influence social dynamics is key to improve robot navigation. Prior research attempts to model social behavior through microscopic interactions, but the resulting emergent behavior depends heavily on the initial conditions, in particular the macroscopic setting. As such, data-driven studies of pedestrian behavior in a fixed environment may provide key insight into this macroscopic aspect, but approp

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Li, Junfei, and Simon X. Yang. "Intelligent Fish-Inspired Foraging of Swarm Robots with Sub-Group Behaviors Based on Neurodynamic Models." Biomimetics 9, no. 1 (2024): 16. http://dx.doi.org/10.3390/biomimetics9010016.

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This paper proposes a novel intelligent approach to swarm robotics, drawing inspiration from the collective foraging behavior exhibited by fish schools. A bio-inspired neural network (BINN) and a self-organizing map (SOM) algorithm are used to enable the swarm to emulate fish-like behaviors such as collision-free navigation and dynamic sub-group formation. The swarm robots are designed to adaptively reconfigure their movements in response to environmental changes, mimicking the flexibility and robustness of fish foraging patterns. The simulation results show that the proposed approach demonstr

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A., Valerie, Huemer M.S., Miwa Hayashi, et al. "Characterizing Scan Patterns in a Spacecraft Cockpit Simulator: Expert Vs. Novice Performance." Proceedings of the Human Factors and Ergonomics Society Annual Meeting 49, no. 1 (2005): 83–87. http://dx.doi.org/10.1177/154193120504900119.

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Operating a spacecraft is a complex and demanding task that requires years of training and constant monitoring of both navigation and systems parameters. By examining differences in scanning between “expert” and “novice” operators, we can develop cognitive models of scanning behavior or enhance training. In the Intelligent Spacecraft Interface Systems (ISIS) laboratory, we measure eye movements and record performance parameters in a part-task space shuttle cockpit simulator. We trained airline transport pilots (as our “novice” group) on fundamentals of flying an ascent (”launch-to-orbit”) in t

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Marino, Francesco, and Giorgio Guglieri. "Beyond Static Obstacles: Integrating Kalman Filter with Reinforcement Learning for Drone Navigation." Aerospace 11, no. 5 (2024): 395. http://dx.doi.org/10.3390/aerospace11050395.

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Autonomous drones offer immense potential in dynamic environments, but their navigation systems often struggle with moving obstacles. This paper presents a novel approach for drone trajectory planning in such scenarios, combining the Interactive Multiple Model (IMM) Kalman filter with Proximal Policy Optimization (PPO) reinforcement learning (RL). The IMM Kalman filter addresses state estimation challenges by modeling the potential motion patterns of moving objects. This enables accurate prediction of future object positions, even in uncertain environments. The PPO reinforcement learning algor

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Saleem, Usama, Abid Saeed, and Rabiya Zulfiqar. "Impact of Customer Perceived Value and E-Trust on E-Purchase Intention in Online Retail." Online Media and Society 5, no. 3 (2024): 73–85. https://doi.org/10.71016/oms/9eqvjp18.

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Aim of the Study: This investigation seeks to understand how online shoppers' perceived value interacts with their trust in digital platforms, likelihood to make online purchases, and overall satisfaction with the shopping experience. Methodology: The research utilized online questionnaires to collect data from Pakistani consumers through convenience sampling. The researchers employed PLS-SEM (Partial Least Squares Structural Equation Modeling) to analyze the data and validate the study's hypotheses, including moderating variables. Finding: The research highlights several critical elements tha

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Yang, Yuan, Jingjie Yan, Jing Guo, et al. "Driving Behavior Analysis of City Buses Based on Real-Time GNSS Traces and Road Information." Sensors 21, no. 3 (2021): 687. http://dx.doi.org/10.3390/s21030687.

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The driving behavior of bus drivers is related to the safety of all passengers and regulation of urban traffic. In order to analyze the relevant characteristics of speed and acceleration, accurate bus trajectories and patterns are essential for driver behavior analysis and development of effective intelligent public transportation. Exploiting real-time vehicle tracking, this paper develops a platform with vehicle-mounted terminals using differential global navigation satellite system (DGNSS) modules for driver behavior analysis. The DGNSS traces were used to derive the vehicle trajectories, wh

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Valiveti, Sesha Sai Sravanthi. "AI-Driven Behavioral Biometrics for 401(k) Account Security." International Research Journal of Advanced Engineering and Technology 02, no. 06 (2025): 23–26. https://doi.org/10.55640/irjaet-v02i06-04.

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As cyber threats evolve, attackers increasingly target financial retirement accounts like 401(k)s, exploiting their high-value nature and weak user-level security controls. Traditional defenses—passwords, OTPs, and device fingerprinting—have proven insufficient in detecting sophisticated account takeovers. This paper presents a behavioral biometrics framework that uses artificial intelligence to continuously authenticate users based on typing patterns, mouse movements, login behavior, and navigation habits. Instead of static credentials, the system builds a behavioral profile for each user and

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Seguin, Caio, Ye Tian, and Andrew Zalesky. "Network communication models improve the behavioral and functional predictive utility of the human structural connectome." Network Neuroscience 4, no. 4 (2020): 980–1006. http://dx.doi.org/10.1162/netn_a_00161.

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The connectome provides the structural substrate facilitating communication between brain regions. We aimed to establish whether accounting for polysynaptic communication in structural connectomes would improve prediction of interindividual variation in behavior as well as increase structure-function coupling strength. Connectomes were mapped for 889 healthy adults participating in the Human Connectome Project. To account for polysynaptic signaling, connectomes were transformed into communication matrices for each of 15 different network communication models. Communication matrices were (a) us

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Mission, Roger. "Website Traffic Patterns and User Behavior: A Comprehensive Study of Visitor Interactions and Engagement Metrics." Journal of Innovative Technology Convergence 5, no. 1 (2023): 11–20. http://dx.doi.org/10.69478/jitc2023v5n1a02.

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Websites play a crucial role in disseminating information, promoting communication, and engaging various stakeholders. In the context of universities, websites serve as central online hubs for academic programs, campus life, faculty profiles, resources, news, and more. This study focuses on the website of the University of Antique (UA), a state university in the Philippines, to analyze visitor behavior and engagement. The research objectives include collecting and analyzing data on website visits, page views, bounce rates, time spent on pages, and navigation patterns. The study aims to identif

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Karydis, Ioannis, Markos Avlonitis, Konstantinos Chorianopoulos, and Spyros Sioutas. "Identifying Important Segments in Videos: A Collective Intelligence Approach." International Journal on Artificial Intelligence Tools 23, no. 02 (2014): 1440010. http://dx.doi.org/10.1142/s0218213014400107.

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This work studies collective intelligence behavior of Web users that share and watch video content. Accordingly, it is proposed that the aggregated users' video activity exhibits characteristic patterns. Such patterns may be used in order to infer important video scenes leading thus to collective intelligence concerning the video content. To this end, experimentation is based on users' interactions (e.g., pause, seek/scrub) that have been gathered in a controlled user experiment with information-rich videos. Collective information seeking behavior is then modeled by means of the corresponding

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