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Littérature scientifique sur le sujet « Profiling and Behavioral Analysis »

Auteur : Grafiati
Publié le 16 novembre 2024

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Articles de revues sur le sujet "Profiling and Behavioral Analysis"

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FINTZY, ROBERT T. « Criminal Profiling : An Introduction to Behavioral Evidence Analysis ». American Journal of Psychiatry 157, no 9 (septembre 2000) : 1532–34. http://dx.doi.org/10.1176/appi.ajp.157.9.1532.

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Martineau, Melissa, Elena Spiridon et Mary Aiken. « A Comprehensive Framework for Cyber Behavioral Analysis Based on a Systematic Review of Cyber Profiling Literature ». Forensic Sciences 3, no 3 (22 juillet 2023) : 452–77. http://dx.doi.org/10.3390/forensicsci3030032.

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Cybercrime presents a significant threat to global society. With the number of cybercrimes increasing year after year and the financial losses escalating, law enforcement must advance its capacity to identify cybercriminals, collect probative evidence, and bring cybercriminals before the courts. Arguably to date, the approach to combatting cybercrime has been technologically centric (e.g., anti-virus, anti-spyware). Cybercrimes, however, are the result of human activities based on human motives. It is, therefore, important that any comprehensive law enforcement strategy for combatting cybercrime includes a deeper understanding of the hackers that sit behind the keyboards. The purpose of this systematic review was to examine the state of the literature relating to the application of a human-centric investigative tool (i.e., profiling) to cybercrime by conducting a qualitative meta-synthesis. Adhering to the PRISMA 2020 guidelines, this systematic review focuses specifically on cybercrime where a computer is the target (e.g., hacking, DDoS, distribution of malware). Using a comprehensive search strategy, this review used the following search terms: “cybercrime”, “computer crime”, “internet crime”, “cybercriminal”, “hacker”, “black hat”, “profiling”, “criminal profiling”, “psychological profiling”, “offender profiling”, “criminal investigative analysis”, “behavioral profiling”, “behavioral analysis”, “personality profiling”, “investigative psychology”, and “behavioral evidence analysis” in all combinations to identify the relevant literature in the ACM Digital Library, EBSCOhost databases, IEEE Xplore, ProQuest, Scopus, PsychInfo, and Google Scholar. After applying the inclusion/exclusion criteria, a total of 72 articles were included in the review. This article utilizes a systematic review of the current literature on cyber profiling as a foundation for the development of a comprehensive framework for applying profiling techniques to cybercrime—described as cyber behavioral analysis (CBA). Despite decades of research, our understanding of cybercriminals remains limited. A lack of dedicated researchers, the paucity of research regarding human behavior mediated by technology, and limited access to datasets have hindered progress. The aim of this article was to advance the knowledge base in cyber behavioral sciences, and in doing so, inform future empirical research relating to the traits and characteristics of cybercriminals along with the application of profiling techniques and methodologies to cybercrime.
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Yu, Szde. « BEHAVIORAL EVIDENCE ANALYSIS ON FACEBOOK : A TEST OF CYBER-PROFILING ». Defendologija 16, no 33 (10 mai 2013) : 19–30. http://dx.doi.org/10.5570/dfnd.en.1333.02.

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Li, Hai, Luke Lunhua Mao, James Jianhui Zhang et Jiaxi Xu. « Classifying and Profiling Sports Lottery Gamblers : A Cluster Analysis Approach ». Social Behavior and Personality : an international journal 43, no 8 (18 septembre 2015) : 1299–317. http://dx.doi.org/10.2224/sbp.2015.43.8.1299.

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We developed a typology of sports gamblers based on the Scale of Assessing Problem Gambling and then to describe the clusters we identified according to the demographic and behavioral characteristics of each. Participants (N = 4,980) were Chinese sports lottery players selected using a multistage sampling procedure. All participants completed the survey. Through cluster analyses, we identified 5 distinctive clusters of sports gamblers: casual players, escalated players, at-risk players, compulsive players, and problem players. A profiling analysis revealed that these 5 clusters differed in both terms of demographic and behavioral characteristics. This typology of sports gamblers provides diagnostic information that can be used by regulatory institutions to develop relevant intervention programs.
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Harini, Karthick, Suliman Yousef Alomar, Mohammed Vajagathali, Salim Manoharadas, Anbazhagan Thirumalai, Koyeli Girigoswami et Agnishwar Girigoswami. « Niosomal Bupropion : Exploring Therapeutic Frontiers through Behavioral Profiling ». Pharmaceuticals 17, no 3 (12 mars 2024) : 366. http://dx.doi.org/10.3390/ph17030366.

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Bupropion (Bup) belongs to the norepinephrine–dopamine reuptake inhibitor (NDRI) class and it is the only FDA-approved drug of its class for the treatment of major depressive disorder (MDD), sold under the name of Wellbutrin. Although bupropion is effective in suppressing the symptoms, its regular use and overdose might lead to seizures and liver failure. Thus, we aimed to nanoformulate bupropion onto a niosomal vesicle to improve its efficacy and achieve the same therapeutic effect at lower scheduled doses. A thin film hydration method was adopted to synthesize and optimize Bup entrapped niosomes using three different surfactants of the sorbitan ester series (Span 20, 40, and 60) in combination with cholesterol. The optimization data determined that the niosome formulated with a cholesterol-to-surfactant ratio of 1:1.5 is the most stable system, with the Bup entrapped niosomes containing Span 20 (Bup@N20C) exhibiting minimal in vitro and in vivo toxicity, and demonstrating the sustained release of Bup in artificial cerebrospinal fluid (ACSF). The Bup@N20C formulation showed increased exploration activity and reduced irregular movements in reserpine-induced depression in the adult zebrafish model, suggesting the potential for mood improvement through the suppression of depression-like behavior which was established by statistical analysis and trajectory data. The Bup@N20C-treated group even surpasses the treatment effect of the positive control group and is comparable to the control group. Hence, it can be inferred that niosomal formulations of Bup represent a promising delivery system capable of achieving the brain delivery of the cargo by bypassing the blood–brain barrier facilitated by their small architectural structure.
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SABUNCU, Ä°brahim, Edanur TÃœRKAN et Hilal POLAT. « CUSTOMER SEGMENTATION AND PROFILING WITH RFM ANALYSIS ». TURKISH JOURNAL OF MARKETING 5, no 1 (25 avril 2020) : 22–36. http://dx.doi.org/10.30685/tujom.v5i1.84.

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This paper is a case study on segmentation and profiling of customers according to their lifetime value by using the RFM (Recency, Frequency and Monetary Value) model which is an analytical method for behavioral customer segmentation. Real customer data that is gathered from a fuel station in Istanbul, Turkey is used for the case study. The data contain 1015 customers’ arrival frequency, last arrival date and total spend amount in the first half of 2016, and 10 descriptor variables of customers. First, demographic characteristics of fuel station customers were analyzed by descriptive statistics. Then customers' RFM score was calculated through SPSS program, and customers were divided into 5 segments according to their RFM scores by cluster analysis. Finally, the customer profile of segments has been created by using Correspond analysis and Discriminant analysis. Although fuel station managers think that the most valuable customer for their company are automobile drivers, result of the analysis suggests that the most valuable customers are Truck drivers. At the end of the paper, recommendations are made based on customer profiles of two most valuables segments that are named VIP and GOLD.
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von Ziegler, Lukas, Oliver Sturman et Johannes Bohacek. « Big behavior : challenges and opportunities in a new era of deep behavior profiling ». Neuropsychopharmacology 46, no 1 (29 juin 2020) : 33–44. http://dx.doi.org/10.1038/s41386-020-0751-7.

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AbstractThe assessment of rodent behavior forms a cornerstone of preclinical assessment in neuroscience research. Nonetheless, the true and almost limitless potential of behavioral analysis has been inaccessible to scientists until very recently. Now, in the age of machine vision and deep learning, it is possible to extract and quantify almost infinite numbers of behavioral variables, to break behaviors down into subcategories and even into small behavioral units, syllables or motifs. However, the rapidly growing field of behavioral neuroethology is experiencing birthing pains. The community has not yet consolidated its methods, and new algorithms transfer poorly between labs. Benchmarking experiments as well as the large, well-annotated behavior datasets required are missing. Meanwhile, big data problems have started arising and we currently lack platforms for sharing large datasets—akin to sequencing repositories in genomics. Additionally, the average behavioral research lab does not have access to the latest tools to extract and analyze behavior, as their implementation requires advanced computational skills. Even so, the field is brimming with excitement and boundless opportunity. This review aims to highlight the potential of recent developments in the field of behavioral analysis, whilst trying to guide a consensus on practical issues concerning data collection and data sharing.
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Adeyiga, J. A., S. O. Olabiyisi et E. O. Omidiora. « A comparative analysis of selected clustering algorithms for criminal profiling ». Nigerian Journal of Technology 39, no 2 (16 juillet 2020) : 464–71. http://dx.doi.org/10.4314/njt.v39i2.16.

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Several criminal profiling systems have been developed to assist the Law Enforcement Agencies in solving crimes but the techniques employed in most of the systems lack the ability to cluster criminal based on their behavioral characteristics. This paper reviewed different clustering techniques used in criminal profiling and then selects one fuzzy clustering algorithm (Expectation Maximization) and two hard clustering algorithm (K-means and Hierarchical). The selected algorithms were then developed and tested on real life data to produce "profiles" of criminal activity and behavior of criminals. The algorithms were implemented using WEKA software package. The performance of the algorithms was evaluated using cluster accuracy and time complexity. The results show that Expectation Maximization algorithm gave a 90.5% clusters accuracy in 8.5s, while K-Means had 62.6% in 0.09s and Hierarchical with 51.9% in 0.11s. In conclusion, soft clustering algorithm performs better than hard clustering algorithm in analyzing criminal data. Keywords: Clustering Algorithm, Profiling, Crime, Membership value
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Cantore, Daniele. « On Biometrics and Profiling ». International Journal of Technoethics 2, no 4 (octobre 2011) : 84–93. http://dx.doi.org/10.4018/jte.2011100106.

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This paper advances an analysis of biometrics and profiling. Biometrics represents the most effective technology in order to prove someone’s identity. Profiling regards the capability of collecting and organizing individuals’ preferences and attitudes as consumers and costumers. Moreover, biometrics is already used in order to gather and manage biological and behavioral data and this tendency may increase in Ambient Intelligence context. Therefore, dealing with individuals’ data, both biometrics and profiling have to tackle many ethical issues related to privacy on one hand and democracy on the other. After a brief introduction, the author introduces biometrics, exploring its methodology and applications. The following section focuses on profiling both in public and private sector. The last section analyzes those issues concerning privacy and democracy, within also the Ambient Intelligence.
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Trusov, Michael, Liye Ma et Zainab Jamal. « Crumbs of the Cookie : User Profiling in Customer-Base Analysis and Behavioral Targeting ». Marketing Science 35, no 3 (mai 2016) : 405–26. http://dx.doi.org/10.1287/mksc.2015.0956.

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Thèses sur le sujet "Profiling and Behavioral Analysis"

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Lane, Erin C. « Urban disadvantage, social disorganization, and racial profiling an analysis of ecology and police officers' race-specific search behaviors / ». [Gainesville, Fla.] : University of Florida, 2005. http://purl.fcla.edu/fcla/etd/UFE0012660.

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Schmidt, Elisabeth. « Profiling the german Gazela vinho verde consumer : a market segmentation based on product quality ». Master's thesis, [s.n.], 2013. http://hdl.handle.net/10284/4105.

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Dissertação apresentada à Universidade Fernando Pessoa como parte dos requisitos de obtenção do grau de Mestre em Ciências da Comunicação, ramo de Marketing e Publicidade
The core objective of this study was to find out what preferences and wine consumer patterns characterize specific segments in the German market for Vinho Verde. For this purpose an exploratory research using a self-administered questionnaire was applied. The basis for a cluster analysis was a measurement scale about the perceived product quality of Gazela. Four segments were derived from the cluster analysis: (1) refusing, (2) enthusiastic, (3) indifferent and (4) enjoying Vinho Verde drinker. The second and the fourth segments were found to be the main target groups for Gazela. The findings about the associations between Portugal as the country of origin of Gazela and Portuguese wine were rather negative. The managerial implications suggest developing an advertising campaign in order to successfully promote Gazela in Germany. Two alternatives are suggested: keeping the country of origin on the label or removing it. The first suggestion requires extensive measures and actions to improve the image of wine, which is “made in Portugal”. The results of this study show the need of increasing the awareness of Vinho Verde among German consumers and indicate the need of improvement of the perceptions about Portugal and Portuguese wine and examine possibilities for enhancing the acceptance of Portuguese wine, especially Vinho Verde in Germany.
O objetivo principal deste estudo foi o de descobrir as preferências e os padrões de consumo de vinho que caracterizam os segmentos específicos do mercado alemão para o Vinho Verde. Para este objectivo esta pesquisa exploratória utilizou um questionário auto-administrado. A escala base escolhida para a análise de cluster foi a de medição sobre a qualidade do produto percebida aplicada à marca Gazela. Foram obtidos quatros segmentos a partir da análise de cluster: (1) Objector (2), entusiasta, (3) indiferente e (4) Fruidor de Vinho Verde. Os segmentos 2 e 4 são os grupos alvos de Gazela. Os resultados sobre as associações com Portugal, o país de origem do Gazela, e vinho português demostraram relações bastante negativas. As implicações ao nível da gestão sugerem o desenvolvimento de uma campanha publicitária para promover o sucesso de Gazela na alemanha. Duas alternativas são sugeridas: manter o país de origem no rótulo ou removê-lo. A primeira sugestão requer medidas e ações mais abrangentes para melhorar a imagem do vinho "made in Portugal". Os resultados deste estudo apontam para a necessidade de aumentar a consciência sobre o Vinho Verde entre os consumidores alemães e indicam a necessidade de melhoria das percepções sobre Portugal e sobre o vinho português e de estudar as possibilidades de aumentar a aceitação de vinho português, especialmente o Vinho Verde na Alemanha.
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Yan, Dacong. « Program Analyses for Understanding the Behavior and Performance of Traditional and Mobile Object-Oriented Software ». The Ohio State University, 2014. http://rave.ohiolink.edu/etdc/view?acc_num=osu1406064286.

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Farahbakhsh, Reza. « Profiling professional and regular users on popular Internet services based on implementation of large scale Internet measurement tools ». Thesis, Evry, Institut national des télécommunications, 2015. http://www.theses.fr/2015TELE0012/document.

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Les services Internet populaires modèlent et remodèlent fondamentalement les moyens traditionnels de communication des personnes, ayant ainsi un impact majeur sur leur vie sociale. Deux des services Internet très populaires avec cette caractéristique sont les Réseaux sociaux en ligne (OSN) et les systèmes Peer-to-Peer (P2P). Les ONS fournissent un environnement virtuel où les gens peuvent partager leurs informations et leurs intérêts tout en étant en contact avec d'autres personnes. D'autre part, les systèmes P2P, qui sont toujours l'un des services populaires avec une grande proportion de l'ensemble du trafic Internet, offrent une occasion en or pour leurs clients de partager un type de contenu différent, y compris le contenu protégé. En dehors de l'énorme popularité des ONS et des systèmes de P2P parmi les utilisateurs réguliers, ils sont intensivement utilisés par les professionnels (grandes entreprises, politiciens, athlètes, célébrités en cas d'ONS et éditeurs de contenu professionnels en cas de P2P) afin d'interagir avec les gens à des fins différentes (campagnes marketing, les commentaires des clients, amélioration de la réputation publique, etc.) Dans cette thèse, nous caractérisons le comportement des utilisateurs réguliers et professionnels dans les deux services mentionnés populaires (ONS et P2P) en termes de stratégies de publication, de consommation de contenu et d'analyse comportementale. À cette fin, cinq de nos études menées sont présentées dans ce manuscrit comme suit: - "L'évolution des contenus multimédias", qui présente une analyse approfondie sur l'évolution du contenu multimédia disponible en BitTorrent en se concentrant sur quatre mesures pertinentes à travers différentes catégories de contenu : la disponibilité du contenu, la popularité du contenu, la taille de contenu et les commentaires de l'utilisateur - "La réaction des utilisateurs professionnels face aux actions de lutte contre le piratage", en examinant l'impact de deux grandes actions de lutte contre le piratage - la fermeture de Megaupload et la mise en œuvre de la loi anti-piratage française (HADOPI) - sur le comportement des publicateurs professionnels dans le plus grand portail de BitTorrent qui sont les principaux fournisseurs de contenu en ligne protégé. - "La quantité d'informations divulguées sur Facebook", en enquêtant sur l'exposition publique des profils utilisateurs, une grande base de données comprenant un demi-million d'utilisateurs réguliers. - "Les utilisateurs professionnels Cross Posting Activity», en analysant le modèle de publication des utilisateurs professionnels de mêmes informations sur trois grands ONS à savoir Facebook, Google+ et Twitter. - "Les stratégies des utilisateurs professionnels dans les ONS", où nous étudions la stratégie globale d'utilisateurs professionnels par secteur (par exemple, les entreprises de voitures, l'habillement, politiques, etc.) sur Facebook, Google+ et Twitter. Les résultats de cette thèse fournissent une vision d'ensemble pour comprendre certains aspects comportementaux importants de différents types d'utilisateurs des services Internet populaires et ces contributions peuvent être utilisées dans divers domaines (par exemple analyse de campagne marketing et publicité, etc.) et les différentes parties peuvent bénéficier des résultats et des méthodologies mises en œuvre telles que les FAI et les propriétaires des services pour leur planification ou l'expansion des services actuels à venir, ainsi que les professionnels pour accroître leur succès sur les médias sociaux
Popular Internet services are fundamentally shaping and reshaping traditional ways of people communication, thus having a major impact on their social life. Two of the very popular Internet services with this characteristic are Online Social Networks (OSNs) and Peer-to-Peer (P2P) systems. OSNs provide a virtual environment where people can share their information and interests as well as being in contact with other people. On the other hand, P2P systems, which are still one of the popular services with a large proportion of the whole Internet traffic, provide a golden opportunity for their customers to share different type of content including copyrighted content. Apart from the huge popularity of OSNs and P2P systems among regular users, they are being intensively used by professional players (big companies, politician, athletes, celebrities in case of OSNs and professional content publishers in case of P2P) in order to interact with people for different purposes (marketing campaigns, customer feedback, public reputation improvement, etc.). In this thesis, we characterize the behavior of regular and professional users in the two mentioned popular services (OSNs and P2P systems) in terms of publishing strategies, content consumption and behavioral analysis. To this end, five of our conducted studies are presented in this manuscript as follows: - “The evolution of multimedia contents", which presents a thorough analysis on the evolution of multimedia content available in BitTorrent by focusing on four relevant metrics across different content categories: content availability, content popularity, content size and user's feedback. - “The reaction of professional users to antipiracy actions", by examining the impact of two major antipiracy actions, the closure of Megaupload and the implementation of the French antipiracy law (HADOPI), on professional publishers behavior in the largest BitTorrent portal who are major providers of online copyrighted content. - “The amount of disclosed information on Facebook", by investigating the public exposure of Facebook users' profile attributes in a large dataset including half million regular users. - “Professional users Cross Posting Activity", by analyzing the publishing pattern of professional users which includes same information over three major OSNs namely Facebook, Google+ and Twitter. - “Professional Users' Strategies in OSNs", where we investigate the global strategy of professional users by sector (e.g., Cars companies, Clothing companies, Politician, etc.) over Facebook, Google+ and Twitter. The outcomes of this thesis provide an overall vision to understand some important behavioral aspects of different types of users on popular Internet services and these contributions can be used in various domains (e.g. marketing analysis and advertising campaign, etc.) and different parties can benefit from the results and the implemented methodologies such as ISPs and owners of the Services for their future planning or expansion of the current services as well as professional players to increase their success on social media
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Farahbakhsh, Reza. « Profiling professional and regular users on popular Internet services based on implementation of large scale Internet measurement tools ». Electronic Thesis or Diss., Evry, Institut national des télécommunications, 2015. http://www.theses.fr/2015TELE0012.

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Résumé :
Les services Internet populaires modèlent et remodèlent fondamentalement les moyens traditionnels de communication des personnes, ayant ainsi un impact majeur sur leur vie sociale. Deux des services Internet très populaires avec cette caractéristique sont les Réseaux sociaux en ligne (OSN) et les systèmes Peer-to-Peer (P2P). Les ONS fournissent un environnement virtuel où les gens peuvent partager leurs informations et leurs intérêts tout en étant en contact avec d'autres personnes. D'autre part, les systèmes P2P, qui sont toujours l'un des services populaires avec une grande proportion de l'ensemble du trafic Internet, offrent une occasion en or pour leurs clients de partager un type de contenu différent, y compris le contenu protégé. En dehors de l'énorme popularité des ONS et des systèmes de P2P parmi les utilisateurs réguliers, ils sont intensivement utilisés par les professionnels (grandes entreprises, politiciens, athlètes, célébrités en cas d'ONS et éditeurs de contenu professionnels en cas de P2P) afin d'interagir avec les gens à des fins différentes (campagnes marketing, les commentaires des clients, amélioration de la réputation publique, etc.) Dans cette thèse, nous caractérisons le comportement des utilisateurs réguliers et professionnels dans les deux services mentionnés populaires (ONS et P2P) en termes de stratégies de publication, de consommation de contenu et d'analyse comportementale. À cette fin, cinq de nos études menées sont présentées dans ce manuscrit comme suit: - "L'évolution des contenus multimédias", qui présente une analyse approfondie sur l'évolution du contenu multimédia disponible en BitTorrent en se concentrant sur quatre mesures pertinentes à travers différentes catégories de contenu : la disponibilité du contenu, la popularité du contenu, la taille de contenu et les commentaires de l'utilisateur - "La réaction des utilisateurs professionnels face aux actions de lutte contre le piratage", en examinant l'impact de deux grandes actions de lutte contre le piratage - la fermeture de Megaupload et la mise en œuvre de la loi anti-piratage française (HADOPI) - sur le comportement des publicateurs professionnels dans le plus grand portail de BitTorrent qui sont les principaux fournisseurs de contenu en ligne protégé. - "La quantité d'informations divulguées sur Facebook", en enquêtant sur l'exposition publique des profils utilisateurs, une grande base de données comprenant un demi-million d'utilisateurs réguliers. - "Les utilisateurs professionnels Cross Posting Activity», en analysant le modèle de publication des utilisateurs professionnels de mêmes informations sur trois grands ONS à savoir Facebook, Google+ et Twitter. - "Les stratégies des utilisateurs professionnels dans les ONS", où nous étudions la stratégie globale d'utilisateurs professionnels par secteur (par exemple, les entreprises de voitures, l'habillement, politiques, etc.) sur Facebook, Google+ et Twitter. Les résultats de cette thèse fournissent une vision d'ensemble pour comprendre certains aspects comportementaux importants de différents types d'utilisateurs des services Internet populaires et ces contributions peuvent être utilisées dans divers domaines (par exemple analyse de campagne marketing et publicité, etc.) et les différentes parties peuvent bénéficier des résultats et des méthodologies mises en œuvre telles que les FAI et les propriétaires des services pour leur planification ou l'expansion des services actuels à venir, ainsi que les professionnels pour accroître leur succès sur les médias sociaux
Popular Internet services are fundamentally shaping and reshaping traditional ways of people communication, thus having a major impact on their social life. Two of the very popular Internet services with this characteristic are Online Social Networks (OSNs) and Peer-to-Peer (P2P) systems. OSNs provide a virtual environment where people can share their information and interests as well as being in contact with other people. On the other hand, P2P systems, which are still one of the popular services with a large proportion of the whole Internet traffic, provide a golden opportunity for their customers to share different type of content including copyrighted content. Apart from the huge popularity of OSNs and P2P systems among regular users, they are being intensively used by professional players (big companies, politician, athletes, celebrities in case of OSNs and professional content publishers in case of P2P) in order to interact with people for different purposes (marketing campaigns, customer feedback, public reputation improvement, etc.). In this thesis, we characterize the behavior of regular and professional users in the two mentioned popular services (OSNs and P2P systems) in terms of publishing strategies, content consumption and behavioral analysis. To this end, five of our conducted studies are presented in this manuscript as follows: - “The evolution of multimedia contents", which presents a thorough analysis on the evolution of multimedia content available in BitTorrent by focusing on four relevant metrics across different content categories: content availability, content popularity, content size and user's feedback. - “The reaction of professional users to antipiracy actions", by examining the impact of two major antipiracy actions, the closure of Megaupload and the implementation of the French antipiracy law (HADOPI), on professional publishers behavior in the largest BitTorrent portal who are major providers of online copyrighted content. - “The amount of disclosed information on Facebook", by investigating the public exposure of Facebook users' profile attributes in a large dataset including half million regular users. - “Professional users Cross Posting Activity", by analyzing the publishing pattern of professional users which includes same information over three major OSNs namely Facebook, Google+ and Twitter. - “Professional Users' Strategies in OSNs", where we investigate the global strategy of professional users by sector (e.g., Cars companies, Clothing companies, Politician, etc.) over Facebook, Google+ and Twitter. The outcomes of this thesis provide an overall vision to understand some important behavioral aspects of different types of users on popular Internet services and these contributions can be used in various domains (e.g. marketing analysis and advertising campaign, etc.) and different parties can benefit from the results and the implemented methodologies such as ISPs and owners of the Services for their future planning or expansion of the current services as well as professional players to increase their success on social media
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Casserly, Alison P. « Integrated Analysis of miRNA/mRNA Expression in the Neurocircuitry Underlying Nicotine Dependence ». eScholarship@UMMS, 2018. https://escholarship.umassmed.edu/gsbs_diss/985.

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Nicotine dependence is responsible for perpetuating the adverse health effects due to tobacco use, the leading cause of preventable death worldwide. Nicotine is an agonist for nicotinic acetylcholine receptors, which are enriched in the mesocorticolimbic and habenulo-interpeduncular circuitries, underlying nicotine reward and withdrawal, respectively. Drugs of abuse, including nicotine, induce stable neuroadaptations, requiring protein synthesis through regulation of transcription factors, epigenetic mechanisms, and non-coding RNAs. It also been shown that miRNAs in brain are regulated by nicotine and that miRNA dysregulation contributes to brain dysfunction, including drug addiction. While much is known about the neurocircuitry responsible for the behaviors associated with nicotine reward or withdrawal, the underlying molecular mechanisms of how these changes in behavior are induced are less clear. Using miRNA-/mRNA-Seq, we demonstrate that there are widespread changes in both miRNA and mRNA expression in brain regions comprising the mesocorticolimbic circuit after chronic nicotine treatment, and the habenulo-interpeduncular circuit during acute nicotine withdrawal. Conserved, differentially expressed miRNAs were predicted to target inversely regulated mRNAs. We determined that expression of miR-106b-5p is up-regulated and Profilin 2 (Pfn2), an actin-binding protein enriched in the brain, is down-regulated in the interpeduncular nucleus (IPN) during acute nicotine withdrawal. Further we show that miR-106b-5p represses Pfn2 expression. We demonstrate that knockdown of Pfn2 in the IPN is sufficient to induce anxiety, a symptom of withdrawal. This novel role of Pfn2 in nicotine withdrawal-associated anxiety is a prime example of this dataset’s utility, allowing for the identification of a multitude of miRNAs/mRNA which may participate in the molecular mechanisms underlying the neuroadaptations of nicotine dependence.
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Kumar, Tushar. « Characterizing and controlling program behavior using execution-time variance ». Diss., Georgia Institute of Technology, 2016. http://hdl.handle.net/1853/55000.

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Immersive applications, such as computer gaming, computer vision and video codecs, are an important emerging class of applications with QoS requirements that are difficult to characterize and control using traditional methods. This thesis proposes new techniques reliant on execution-time variance to both characterize and control program behavior. The proposed techniques are intended to be broadly applicable to a wide variety of immersive applications and are intended to be easy for programmers to apply without needing to gain specialized expertise. First, we create new QoS controllers that programmers can easily apply to their applications to achieve desired application-specific QoS objectives on any platform or application data-set, provided the programmers verify that their applications satisfy some simple domain requirements specific to immersive applications. The controllers adjust programmer-identified knobs every application frame to effect desired values for programmer-identified QoS metrics. The control techniques are novel in that they do not require the user to provide any kind of application behavior models, and are effective for immersive applications that defy the traditional requirements for feedback controller construction. Second, we create new profiling techniques that provide visibility into the behavior of a large complex application, inferring behavior relationships across application components based on the execution-time variance observed at all levels of granularity of the application functionality. Additionally for immersive applications, some of the most important QoS requirements relate to managing the execution-time variance of key application components, for example, the frame-rate. The profiling techniques not only identify and summarize behavior directly relevant to the QoS aspects related to timing, but also indirectly reveal non-timing related properties of behavior, such as the identification of components that are sensitive to data, or those whose behavior changes based on the call-context.
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Gao, Wei. « CONSTRUCTING USER BEHAVIORAL PROFILES USING DATA-MINING-BASED APPROACH ». Diss., Tucson, Arizona : University of Arizona, 2005. http://etd.library.arizona.edu/etd/GetFileServlet?file=file:///data1/pdf/etd/azu%5Fetd%5F1261%5F1%5Fm.pdf&type=application/pdf.

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Toure, Almamy. « Collection, analysis and harnessing of communication flows for cyber-attack detection ». Electronic Thesis or Diss., Valenciennes, Université Polytechnique Hauts-de-France, 2024. http://www.theses.fr/2024UPHF0023.

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La complexité croissante des cyberattaques, caractérisée par une diversification des techniques d'attaque, une expansion des surfaces d'attaque et une interconnexion croissante d'applications avec Internet, rend impérative la gestion du trafic réseau en milieu professionnel. Les entreprises de tous types collectent et analysent les flux réseau et les journaux de logs pour assurer la sécurité des données échangées et prévenir la compromission des systèmes d'information. Cependant, les techniques de collecte et de traitement des données du trafic réseau varient d'un jeu de données à l'autre, et les approches statiques de détection d'attaque présentent des limites d'efficacité et précision, de temps d'exécution et de scalabilité. Cette thèse propose des approches dynamiques de détection de cyberattaques liées au trafic réseau, en utilisant une ingénierie d'attributs basée sur les différentes phases de communication d'un flux réseau, couplée aux réseaux de neurones à convolution (1D-CNN) et leur feature detector. Cette double extraction permet ainsi une meilleure classification des flux réseau, une réduction du nombre d'attributs et des temps d'exécution des modèles donc une détection efficace des attaques. Les entreprises sont également confrontées à des cybermenaces qui évoluent constamment, et les attaques "zero-day", exploitant des vulnérabilités encore inconnues, deviennent de plus en plus fréquentes. La détection de ces attaques zero-day implique une veille technologique constante et une analyse minutieuse, mais coûteuse en temps, de l'exploitation de ces failles. Les solutions proposées garantissent pour la plupart la détection de certaines techniques d'attaque. Ainsi, nous proposons un framework de détection de ces attaques qui traite toute la chaîne d'attaque, de la phase de collecte des données à l'identification de tout type de zero-day, même dans un environnement en constante évolution. Enfin, face à l'obsolescence des jeux de données et techniques de génération de données existants pour la détection d'intrusion et à la nature figée, non évolutive, et non exhaustive des scénarios d'attaques récents, l'étude d'un générateur de données de synthèse adapté tout en garantissant la confidentialité des données est abordée. Les solutions proposées dans cette thèse optimisent la détection des techniques d'attaque connues et zero-day sur les flux réseau, améliorent la précision des modèles, tout en garantissant la confidentialité et la haute disponibilité des données et modèles avec une attention particulière sur l'applicabilité des solutions dans un réseau d'entreprise
The increasing complexity of cyberattacks, characterized by a diversification of attack techniques, an expansion of attack surfaces, and growing interconnectivity of applications with the Internet, makes network traffic management in a professional environment imperative. Companies of all types collect and analyze network flows and logs to ensure the security of exchanged data and prevent the compromise of information systems. However, techniques for collecting and processing network traffic data vary from one dataset to another, and static attack detection approaches have limitations in terms of efficiency and precision, execution time, and scalability. This thesis proposes dynamic approaches for detecting cyberattacks related to network traffic, using feature engineering based on the different communication phases of a network flow, coupled with convolutional neural networks (1D-CNN) and their feature detector. This double extraction allows for better classification of network flows, a reduction in the number of attributes and model execution times, and thus effective attack detection. Companies also face constantly evolving cyber threats, and "zero-day" attacks that exploit previously unknown vulnerabilities are becoming increasingly frequent. Detecting these zero-day attacks requires constant technological monitoring and thorough but time-consuming analysis of the exploitation of these vulnerabilities. The proposed solutions guarantee the detection of certain attack techniques. Therefore, we propose a detection framework for these attacks that covers the entire attack chain, from the data collection phase to the identification of any type of zero-day, even in a constantly evolving environment. Finally, given the obsolescence of existing datasets and data generation techniques for intrusion detection, and the fixed, non-evolving, and non-exhaustive nature of recent attack scenarios, the study of an adapted synthetic data generator while ensuring data confidentiality is addressed. The solutions proposed in this thesis optimize the detection of known and zero-day attack techniques on network flows, improve the accuracy of models, while ensuring the confidentiality and high availability of data and models, with particular attention to the applicability of the solutions in a company network
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Wu, Burton. « New variational Bayesian approaches for statistical data mining : with applications to profiling and differentiating habitual consumption behaviour of customers in the wireless telecommunication industry ». Thesis, Queensland University of Technology, 2011. https://eprints.qut.edu.au/46084/1/Burton_Wu_Thesis.pdf.

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This thesis investigates profiling and differentiating customers through the use of statistical data mining techniques. The business application of our work centres on examining individuals’ seldomly studied yet critical consumption behaviour over an extensive time period within the context of the wireless telecommunication industry; consumption behaviour (as oppose to purchasing behaviour) is behaviour that has been performed so frequently that it become habitual and involves minimal intentions or decision making. Key variables investigated are the activity initialised timestamp and cell tower location as well as the activity type and usage quantity (e.g., voice call with duration in seconds); and the research focuses are on customers’ spatial and temporal usage behaviour. The main methodological emphasis is on the development of clustering models based on Gaussian mixture models (GMMs) which are fitted with the use of the recently developed variational Bayesian (VB) method. VB is an efficient deterministic alternative to the popular but computationally demandingMarkov chainMonte Carlo (MCMC) methods. The standard VBGMMalgorithm is extended by allowing component splitting such that it is robust to initial parameter choices and can automatically and efficiently determine the number of components. The new algorithm we propose allows more effective modelling of individuals’ highly heterogeneous and spiky spatial usage behaviour, or more generally human mobility patterns; the term spiky describes data patterns with large areas of low probability mixed with small areas of high probability. Customers are then characterised and segmented based on the fitted GMM which corresponds to how each of them uses the products/services spatially in their daily lives; this is essentially their likely lifestyle and occupational traits. Other significant research contributions include fitting GMMs using VB to circular data i.e., the temporal usage behaviour, and developing clustering algorithms suitable for high dimensional data based on the use of VB-GMM.
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Livres sur le sujet "Profiling and Behavioral Analysis"

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Turvey, Brent E. Criminal profiling : An introduction to behavioral evidence analysis. 3e éd. Burlington, MA : Academic Press, 2008.

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Turvey, Brent E. Criminal profiling : An introduction to behavioral evidence analysis. 3e éd. Burlington, MA : Academic Press, 2008.

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Turvey, Brent E. Criminal profiling : An introduction to behavioral evidence analysis. 3e éd. Burlington, MA : Academic Press, 2008.

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Turvey, Brent E. Criminal profiling : An introduction to behavioral evidence analysis. 2e éd. London : Academic Press, 2001.

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Ainswoth, Peter B. Offender profiling and crime analysis. Cullompton : Willan Pub., 2001.

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Donna, Youngs, dir. Investigative psychology : Offender profiling and the analysis of criminal action. Chichester : John Wiley & Sons, 2009.

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Napier, Mike R. Behavior, truth and deception : applying profiling and analysis to the interview process. Boca Raton, FL : CRC Press, 2010.

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Bartol, Curt R. Criminal and behavioral profiling. Thousand Oaks, Calif : SAGE Publications, 2013.

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Groff, Elizabeth (Elizabeth R.) et Yang Sue-Ming, dir. The criminology of place : Street segments and our understanding of the crime problem. New York : Oxford University Press, 2012.

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Federspiel, Florian M., Gilberto Montibeller et Matthias Seifert, dir. Behavioral Decision Analysis. Cham : Springer International Publishing, 2024. http://dx.doi.org/10.1007/978-3-031-44424-1.

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Chapitres de livres sur le sujet "Profiling and Behavioral Analysis"

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Hlioui, Fedia, Nadia Aloui et Faiez Gargouri. « Automatic Deduction of Learners’ Profiling Rules Based on Behavioral Analysis ». Dans Computational Collective Intelligence, 233–43. Cham : Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-67074-4_23.

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Acien, Alejandro, Aythami Morales, Ruben Vera-Rodriguez et Julian Fierrez. « Keystroke Mobile Authentication : Performance of Long-Term Approaches and Fusion with Behavioral Profiling ». Dans Pattern Recognition and Image Analysis, 12–24. Cham : Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-31321-0_2.

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Shosha, Ahmed F., Joshua I. James, Alan Hannaway, Chen-Ching Liu et Pavel Gladyshev. « Towards Automated Malware Behavioral Analysis and Profiling for Digital Forensic Investigation Purposes ». Dans Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, 66–80. Berlin, Heidelberg : Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-39891-9_5.

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Fan, Xiao-Xi, Kam-Pui Chow et Fei Xu. « Web User Profiling Based on Browsing Behavior Analysis ». Dans Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications, 57–71. Cham : Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-662-44952-3_5.

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Nordahl, Christian, Veselka Boeva, Håkan Grahn et Marie Persson Netz. « Profiling of Household Residents’ Electricity Consumption Behavior Using Clustering Analysis ». Dans Lecture Notes in Computer Science, 779–86. Cham : Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-22750-0_78.

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Colombini, Clara Maria, Antonio Colella, Marco Mattiucci et Aniello Castiglione. « Network Profiling : Content Analysis of Users Behavior in Digital Communication Channel ». Dans Lecture Notes in Computer Science, 416–29. Berlin, Heidelberg : Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-32498-7_31.

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Patterson, Wayne, et Cynthia E. Winston-Proctor. « Profiling ». Dans Behavioral Cybersecurity, 35–44. First edition. | Boca Raton : CRC Press, 2021. : CRC Press, 2020. http://dx.doi.org/10.1201/9781003052029-5.

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Patterson, Wayne, et Cynthia E. Winston-Proctor. « Profiling ». Dans Behavioral Cybersecurity, 43–50. Boca Raton : Taylor & Francis, CRC Press, 2019. : CRC Press, 2019. http://dx.doi.org/10.1201/9780429461484-5.

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Barkhashree et Parneeta Dhaliwal. « Reinforcing Digital Forensics Through Intelligent Behavioural Evidence Analysis : Social Media Hate Speech Profiling ». Dans Artificial Intelligence and Speech Technology, 641–50. Cham : Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-95711-7_52.

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Khera, Varin, Anand R. Prasad et Suksit Kwanoran. « Online Tracking and Behavioral Profiling ». Dans Open Source Intelligence (OSINT) – A practical Introduction, 23–31. New York : River Publishers, 2024. http://dx.doi.org/10.1201/9788770047180-3.

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Actes de conférences sur le sujet "Profiling and Behavioral Analysis"

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Drachen, Anders, James Green, Chester Gray, Elie Harik, Patty Lu, Rafet Sifa et Diego Klabjan. « Guns and guardians : Comparative cluster analysis and behavioral profiling in destiny ». Dans 2016 IEEE Conference on Computational Intelligence and Games (CIG). IEEE, 2016. http://dx.doi.org/10.1109/cig.2016.7860423.

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Singh, Malvika, B. M. Mehtre et S. Sangeetha. « User Behavior Profiling using Ensemble Approach for Insider Threat Detection ». Dans 2019 IEEE 5th International Conference on Identity, Security, and Behavior Analysis (ISBA). IEEE, 2019. http://dx.doi.org/10.1109/isba.2019.8778466.

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Chen, Cheng-Yu, et Shun-Wen Hsiao. « IoT Malware Dynamic Analysis Profiling System and Family Behavior Analysis ». Dans 2019 IEEE International Conference on Big Data (Big Data). IEEE, 2019. http://dx.doi.org/10.1109/bigdata47090.2019.9005981.

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Xu, Kuai, Feng Wang et Bin Wang. « Behavior Profiling and Analysis in Wireless Home Networks ». Dans 2010 7th IEEE Consumer Communications and Networking Conference (CCNC). IEEE, 2010. http://dx.doi.org/10.1109/ccnc.2010.5421571.

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Shen, Xipeng, Michael L. Scott, Chengliang Zhang, Sandhya Dwarkadas, Chen Ding et Mitsunori Ogihara. « Analysis of input-dependent program behavior using active profiling ». Dans the 2007 workshop. New York, New York, USA : ACM Press, 2007. http://dx.doi.org/10.1145/1281700.1281705.

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Berube, Paul, et Jose Nelson Amaral. « Combined profiling : A methodology to capture varied program behavior across multiple inputs ». Dans 2012 IEEE International Symposium on Performance Analysis of Systems & Software (ISPASS). IEEE, 2012. http://dx.doi.org/10.1109/ispass.2012.6189227.

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Gopal, Akshay C., et Lija Jacob. « Customer Behavior Analysis Using Unsupervised Clustering and Profiling : A Machine Learning Approach ». Dans 2022 2nd International Conference on Advance Computing and Innovative Technologies in Engineering (ICACITE). IEEE, 2022. http://dx.doi.org/10.1109/icacite53722.2022.9823646.

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Neal, Tempestt, et Damon Woodard. « Mobile Biometrics, Replay Attacks, and Behavior Profiling : An Empirical Analysis of Impostor Detection ». Dans 2019 International Conference on Biometrics (ICB). IEEE, 2019. http://dx.doi.org/10.1109/icb45273.2019.8987407.

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Mao, Yilin, Caroline Godefroy et Michel Gysen. « Field Applications of Quantitative Fracture Diagnostic From Distributed Temperature Warmback Analysis ». Dans SPE Hydraulic Fracturing Technology Conference and Exhibition. SPE, 2023. http://dx.doi.org/10.2118/212380-ms.

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Abstract Fracture diagnostic on a cluster scale of multi-stage hydraulic fracturing wells remains challenging but essential to determine the quality of the stimulation operation and the completion strategies for future wells. Since the stimulation fluid is injected at a different temperature compared to the original geothermal, the considerably modified and highly heterogeneous thermal profile after stimulation presents significant potential to serve for fracture diagnostic purposes. In this work, a model to analyze the temperature signal associated with the shut-in period after hydraulic fracturing is presented, along with the pilot testing of two datasets. The model extends the scope of traditional thermal injection profiling algorithm with fracture diagnostic functions. During the development process, we incorporate the existing warmback model of conventional wells in analyzing shut-in temperature data with a newly developed stimulated region thermal model. Two main outputs of the model, the injection fluid intake and the fracture propagation extent, are estimated and tested. The model is then automated and thoroughly implemented in the software package. The primary applications of this work are injection fluid intake and fracture propagation extent of each perforation cluster in fractured wells. The spatial resolution of the injection profiling and fracture growth can reach the sub-meter scale (same as the distributed temperature sensing spatial resolution). Compared to the conventional radial warmback model, the temperature signals from the fractured well show a much faster warming trend while taking relatively larger amounts of injection fluid. This behavior can be attributed to the additional heat loss to the unstimulated region and larger contact area between clusters. On the other hand, leak-off fluids create a cooler stimulated region around the fracture plane, which makes the warmback trend slower compared to the linear flow regime model. The model developed in this study considers both behaviors to simulate the actual datasets. The inverse model estimates the fracture propagation extent in both the stimulated region as well as the fracture plane. Both estimations can jointly infer the leak-off extent of an individual cluster. As a pilot project, this model is tested on warmback temperature data from two datasets. The injection profiling results using the model are consistent with profiles obtained from other data sources, while the estimated fracture propagation extents of individual clusters present different types of fracture geometry (symmetrical, asymmetrical, double peaks, etc.). Quantitative injection profiling and fracture propagation extent estimations of an individual cluster using warmback analysis have been proven viable and reliable in this field study. It could be the first quantitative warmback analysis applied to fracture wells in the industry.
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Adil, Mohamed, Lingies Santhirasekaran, Nabilla Arief Tham et Brian Seabrook. « Injection Profiling for Intelligently Completed Wells Equipped with Fiber Optics ». Dans ADIPEC. SPE, 2022. http://dx.doi.org/10.2118/211402-ms.

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Abstract Injectors with intelligent well completions are installed in a geologically complex reservoir setting to inject fluid into multiple zones. For effective reservoir management, it is imperative to know the injection profile along the wellbore and to detect injection defects. Distributed Temperature Sensing (DTS) fiber installed along the length of the well provides high spatial resolution and high frequency temperature data. This paper presents a methodology to estimate zonal-level fluid injection volumes using these DTS measurements. When cold fluid is injected into a hotter reservoir, the region near the wellbore cools down. When injection ceases, the wellbore region slowly warms back to the far field geothermal temperature. The proposed methodology models heat transfer in the radial direction during this warmback period using 1-D energy equations. The model is tuned to DTS data from the warm-back using regression techniques applied independently at each depth. Only the middle time region (MTR) of the warmback is considered for the model since, at early times, we have thermal effects from adiabatic expansion and, at late times, the 1-D modeling assumption is no longer valid. This approach is analogous to the MTR concept often used in pressure transient analysis. Model parameters at each depth are related directly to the volume of fluid injected in the corresponding zone and their relative values can be used to allocate injected fluid volumes. The conventional use of the warm-back model looks at the relative rate that individual zones warm up during a shut-in following cooler water injection to estimate the relative volume of fluid injected into that particular zone. This conventional methodology considers all the data points from warm-back to fit the model. The improved method presented in this paper acknowledges that the early time region (ETR) and late time region (LTR) are not really addressed in the model. Rather it carves out the information by modeling the middle time region (MTR). An alternate approach presented looks at the asymptotic behavior of the middle-time warm-back to infer the cumulative injection volume in each zone. A few test cases are presented comparing the results of the various methodologies and the insights we gain from this analysis. Injection logging is an expensive, conventional method for injection profiling. With the help of fiber technologies and methodologies presented in the paper, we can achieve an accurate understanding of injection profiling without the need for logging. Additionally, we show a methodology where subsequent analysis of warmback at two or more shut-in times gives insight into the injection profile when the original geotherm is disturbed by prior injection or not well known.
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Rapports d'organisations sur le sujet "Profiling and Behavioral Analysis"

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Del Valle, Emiliano Diaz, Chaning Jang et Steve Wendel. Behavioral Systems : Combining behavioral science and systems analysis. Busara, janvier 2024. http://dx.doi.org/10.62372/fmjl3064.

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Many challenges the world faces arise from broken behavioral systems: systems with multiple levels of interacting actors in which people make the best choices they can given their limitations. However, by doing so, they generate outcomes that no one actually wants. In these systems, people are embedded in a context that shapes their behavior. Their actions then shape both how the system behaves and the very set of choices that the individuals within it face, often in non-obvious ways. Once we start looking, it is not hard to find these broken behavioral systems: they arise in everything from fisheries management to racial wealth inequality to corrosive norms of behavior on social media.
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Stevenson, Mark. Individual Profiling Using Text Analysis. Fort Belvoir, VA : Defense Technical Information Center, avril 2016. http://dx.doi.org/10.21236/ad1009417.

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Kolencik, Marian. A critical evaluation of the risk indicators of criminal conduct involving CBRN and explosive materials - Behavioural and observational analysis in crime detection and investigation. ISEM Institute, n.p.o., octobre 2023. http://dx.doi.org/10.52824/vzrb5079.

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Terrorist attacks using explosives and CBRN (Chemical, Biological, Radiological and Nuclear) materials have been present throughout history. While the frequency of CBRN terrorist attacks is relatively low compared to those with explosives and other types of weapons, it is crucial to treat the efforts of both terrorist organizations and individuals with appropriate gravity in order to avert catastrophic consequences. Identifying warning signs that indicate criminal behaviour is crucial for preventing planned crimes or terrorist attacks, and there is a need for more precise coverage of potential risk indicators related to CBRN and explosive crimes. This research aimed at examining and scrutinizing possible warning signs associated with planning and conducting terrorist attacks using CBRN and explosive materials. The research was implemented in three phases. First, comprise the systematic literature review. In the second phase, the case studies and CCTV records from past cases from Europe, USA, Australia and Asia were analysed and the aim was to create a list of risk indicators and categories for future reference by developing a methodological tool. The last phase represented a survey in which the practitioners from European Law enforcement and Intelligence Agencies critically assessed the list of risk indicators and their categories created based on the previous two steps of the research. The last goal was to gain the agreement and endorsement of law enforcement officials from different European nations regarding the validity and importance of recognized risk indicators and their categories, as well as their ranking for use in operational tasks, investigations, and training. The majority of the respondents found the identified categories and risk indicators as reliable and relevant for their operational activities and investigations. For the second research question, the survey results prioritized categories of risk indicators that are most suitable for the detection tactics of investigators and intelligence officers. The third research question examined the ease of observing identified risk indicators, with the category of technological detection/air sampling alarm risk indicators ranking as the easiest to detect. Finally, the survey found that the identified risk indicators are useful for training activities of security entities. Several final comments and recommendations from participants were also discussed, emphasizing the importance of considering multiple factors when identifying risk indicators and the value of the comprehensive list of identified risk indicators. The publication also examines some terrorist theories, the advantages, limitations, and the ongoing debate surrounding the use of profiling in protective security.
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Marinucci, Antonio. ACIP Pile Installation, Installation Monitoring, Full-scale Load Testing, and Extraction Program. Deep Foundations Institute, décembre 2017. http://dx.doi.org/10.37308/cpf-2016-acip-1.

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The Augered Cast-In-Place (ACIP) Pile Committee of the Deep Foundations Institute (DFI) performed a foundation installation, monitoring, performance and extraction program for ACIP piles in the fall of 2016. The purpose of the project was to demonstrate a fully monitored installation of instrumented 18 in (457 mm) and 24 in (610 mm) diameter ACIP piles, including automated monitoring equipment (AME); post-installation thermal integrity profiling (TIP) measurements; compression, tension, and lateral load testing (including monitoring of strain gages embedded along the compression pile shaft); and post-testing extraction of an installed pile for visual inspection. The program was initially planned by the ACIP Pile Committee, and a program site in Okahumpka, FL was selected. Initial funding was provided by the DFI Committee Project Fund with additional funds andin-kind pledges contributed from DFI members and industry partners. In the summer of 2016, the FloridaDepartment of Transportation (FDOT) and its research partners at the University of South Florida (USF)joined the program. Program details were finalized in the summer and fall of 2016. The purposes of this research effort were to demonstrate The fully monitored installation of instrumented ACIP piles, including the use of automated monitoring equipment (AME); The use and accuracy of thermal integrity profiling (TIP) methods with ACIP piles; The load-displacement behavior during compression, tension, and lateral load testing, including the use of and measurement by multiple strain gages embedded along the length of two piles; The integrity and as-constructed geometry of an ACIP pile by extracting an installed pile for visual inspection. To achieve the goals of the project, seven test piles were installed at a site in central Florida: two each for compression testing, tension testing, and lateral testing, and one pile for extraction and visual inspection. The intent of this document is to make the data and information obtained during the demonstration program available to the members of the DFI ACIP Pile Committee, Florida DOT, University of South Florida, and other possible research partners for review, analysis/interpretation, and discussion. The ultimate goals of this endeavor are to advance the overall state-of-the-practice for ACIP piles and to develop documentation for review and use; installation, monitoring, and testing methods; and reporting procedures to allow for both the use of ACIP piles for structural support of bridges and the inclusion of ACIP piles in DOT and other agency specifications in the state of Florida and elsewhere. All of the data presented and discussed herein can be made available in electronic format for additional analysis. Pertinent findings of the demonstration project include the following: The procedures and testing results described in the report highlight the successful installation, monitoring, and load carrying resistance provided by ACIP piles for structural support of bridges per the Florida DOT. The data can be used by the FL DOT as it develops a section for ACIP Piles for Bridges and Major Structures in its Standard Specifications; Grout volumes, as measured by an electromagnetic flowmeter and via manual counting of grout strokes, were in good agreement with each other; The overall grout volume of the extracted pile, when adjusted for the volume of grout observed flowing out of the top of the pile, was in good agreement with the volume calculated by manually measuring the circumference of the extracted pile at 1 ft (305 mm) intervals; Additional research into non-destructive testing (NDT) methods for ACIP piles, in particular Thermal Integrity Profiling, should produce a means to provide additional verification of pile integrity.
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Brauer, Douglas C., Daniel Henry et George A. Matzkanin. ACE/AACE Inspection and Analysis Handbook. Part 3. Profiling. Fort Belvoir, VA : Defense Technical Information Center, juin 1985. http://dx.doi.org/10.21236/ada210049.

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Acemoglu, Daron, et Martin Kaae Jensen. Equilibrium Analysis in the Behavioral Neoclassical Growth Model. Cambridge, MA : National Bureau of Economic Research, décembre 2018. http://dx.doi.org/10.3386/w25363.

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Petry, Nancy, et Warren Bickel. A Behavioral Economic Analysis of Polydrug Abuse in Heroin Addicts. Cambridge, MA : National Bureau of Economic Research, février 1998. http://dx.doi.org/10.3386/w6415.

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Silverman, Kenneth, et Elias Robles. Employment as a Drug Abuse Treatment Intervention : A Behavioral Economic Analysis. Cambridge, MA : National Bureau of Economic Research, février 1998. http://dx.doi.org/10.3386/w6402.

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Coker, Ray. Toward a behavioral analysis of attentiveness as a style of communication. Portland State University Library, janvier 2000. http://dx.doi.org/10.15760/etd.3227.

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Bernheim, B. Douglas, et Antonio Rangel. Behavioral Public Economics : Welfare and Policy Analysis with Non-Standard Decision-Makers. Cambridge, MA : National Bureau of Economic Research, août 2005. http://dx.doi.org/10.3386/w11518.

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