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FINTZY, ROBERT T. "Criminal Profiling: An Introduction to Behavioral Evidence Analysis." American Journal of Psychiatry 157, no. 9 (September 2000): 1532–34. http://dx.doi.org/10.1176/appi.ajp.157.9.1532.
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Martineau, Melissa, Elena Spiridon, and Mary Aiken. "A Comprehensive Framework for Cyber Behavioral Analysis Based on a Systematic Review of Cyber Profiling Literature." Forensic Sciences 3, no. 3 (July 22, 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 (May 10, 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, and Jiaxi Xu. "Classifying and Profiling Sports Lottery Gamblers: A Cluster Analysis Approach." Social Behavior and Personality: an international journal 43, no. 8 (September 18, 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, and Agnishwar Girigoswami. "Niosomal Bupropion: Exploring Therapeutic Frontiers through Behavioral Profiling." Pharmaceuticals 17, no. 3 (March 12, 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, and Hilal POLAT. "CUSTOMER SEGMENTATION AND PROFILING WITH RFM ANALYSIS." TURKISH JOURNAL OF MARKETING 5, no. 1 (April 25, 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, and Johannes Bohacek. "Big behavior: challenges and opportunities in a new era of deep behavior profiling." Neuropsychopharmacology 46, no. 1 (June 29, 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, and E. O. Omidiora. "A comparative analysis of selected clustering algorithms for criminal profiling." Nigerian Journal of Technology 39, no. 2 (July 16, 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 (October 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, and Zainab Jamal. "Crumbs of the Cookie: User Profiling in Customer-Base Analysis and Behavioral Targeting." Marketing Science 35, no. 3 (May 2016): 405–26. http://dx.doi.org/10.1287/mksc.2015.0956.
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Marbach, Moritz, and Dominik Hangartner. "Profiling Compliers and Noncompliers for Instrumental-Variable Analysis." Political Analysis 28, no. 3 (January 24, 2020): 435–44. http://dx.doi.org/10.1017/pan.2019.48.
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Instrumental-variable (IV) estimation is an essential method for applied researchers across the social and behavioral sciences who analyze randomized control trials marred by noncompliance or leverage partially exogenous treatment variation in observational studies. The potential outcome framework is a popular model to motivate the assumptions underlying the identification of the local average treatment effect (LATE) and to stratify the sample into compliers, always-takers, and never-takers. However, applied research has thus far paid little attention to the characteristics of compliers and noncompliers. Yet, profiling compliers and noncompliers is necessary to understand what subpopulation the researcher is making inferences about and an important first step in evaluating the external validity (or lack thereof) of the LATE estimated for compliers. In this letter, we discuss the assumptions necessary for profiling, which are weaker than the assumptions necessary for identifying the LATE if the instrument is randomly assigned. We introduce a simple and general method to characterize compliers, always-takers, and never-takers in terms of their covariates and provide easy-to-use software in R and STATA that implements our estimator. We hope that our method and software facilitate the profiling of compliers and noncompliers as a standard practice accompanying any IV analysis.
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Jiao, Yun, Alan Faden, Boris Sabirzhanov, Bogdan Stoica, Gregory L. Szeto, and Jennie Leach. "Transcriptional profiling predicts behavioral performance in experimental mouse model of traumatic brain injury (TBI)." Journal of Immunology 204, no. 1_Supplement (May 1, 2020): 75.17. http://dx.doi.org/10.4049/jimmunol.204.supp.75.17.
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Abstract Traumatic brain injury (TBI) is a prevailing cause of disability and death. There are no curative therapies or robust predictors of long-term neurodegenerative disease. Treatment is challenging due to poor understanding of the cellular responses and mechanisms underlying TBI. We linked transcriptional profiling, cytokine profiling, and behavioral scoring in experimental TBI to discover new insights into immune-mediated mechanisms of TBI. Mice received ipsilateral moderate controlled cortical impaction. Luminex analyses showed upregulation of inflammatory cytokines in injured cortex, hippocampus, and spinal cord. Neurobehavioral evaluations were performed, then hippocampi isolated at 28d post-TBI for RNAseq. Pathway analyses of upregulated genes were functionally enriched for glial activation, proliferation, and neuronal development. Genes involved in synaptic transmission, glutamate receptor signaling, and neuronal migration were downregulated. Partial least squares (PLS) regression successfully modeled the relationship between differentially expressed genes and behavioral scores (R2=0.94). A core 10-gene signature predicted TBI severity and behavioral score. PLS discriminant analysis (PLSDA) classified TBI severity. VIP scores were used to define a 20-gene signature in TBI based on high VIP score, high fold change, and contribution to biological function. A PLSDA model using only these 20 genes was cross-validated by bootstrap method (AUROC=0.93), indicating that these genes may identify the critical TBI-altered processes. Altogether, our analyses revealed TBI-related biological pathways, potential therapeutic targets, and gene signatures as biomarkers for TBI severity and behavioral outcomes.
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Hamezah, Hamizah Shahirah, Lina Wati Durani, Nor Faeizah Ibrahim, Daijiro Yanagisawa, Tomoko Kato, Suzana Makpol, Hanafi Ahmad Damanhuri, and Ikuo Tooyama. "P3-135: BRAIN IMAGING, BEHAVIORAL EVALUATIONS, BIOCHEMICAL ANALYSIS, AND PROTEOMES PROFILING IN AGED RATS." Alzheimer's & Dementia 14, no. 7S_Part_21 (July 1, 2006): P1119—P1120. http://dx.doi.org/10.1016/j.jalz.2018.06.1492.
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Silke, Andrew. "Criminal Profiling: An Introduction to Behavioural Evidence Analysis." Crime Prevention and Community Safety 3, no. 2 (April 2001): 81–82. http://dx.doi.org/10.1057/palgrave.cpcs.8140092.
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Hamza, Muhammad, Syed Mashhad M. Geelani, Qamar Nawaz, Asif Kabir, and Isma Hamid. "Clustering of IoT Devices Using Device Profiling and Behavioral Analysis to Build Efficient Network Policies." April 2021 40, no. 2 (April 1, 2021): 335–45. http://dx.doi.org/10.22581/muet1982.2102.08.
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The Internet of Things (IoT) has emerged as a new paradigm, and billions of devices are connected with the internet. IoT is being penetrated in major domains of daily life like health care, agriculture, industry, smart homes and monitoring of the environment. The operator of such complex, huge and diverse heterogeneous networks may not even be fully aware of their IoT devices working, activity, behavior and resource utilization etc. The efficient management of IoT devices becomes a challenge for network managers to ensure smooth network operation. Network traffic analysis of IoT devices is a necessary and rudimentary tool to understand the behavior of devices. In this paper firstly, we identify insights of device network traffic, discuss the activity patterns of some IoT devices and present a visual description of the pattern of IoT devices. Secondly, after analyzing the device's behavior, we build and demonstrate a profile of each device based on its activity cycle and traffic patterns information. Thirdly, the K-Means clustering algorithm is used to make clusters of IoT devices using their profile information. The clustering algorithm groups similar devices in a single group. The obtained results clearly describe the patterns of devices which help the network managers to make appropriate network policies for efficient secure network management.
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Koh, Shao Wei, Adriana Shamsudin, Thanasilan Ong, Alea Nurhazli, Farhanah Muhamad, and Yusma Fariza Yasin. "DEMOGRAPHIC AND BEHAVIORAL PROFILING OF E-WALLET USERS: A COMPARATIVE ANALYSIS OF E-WALLET PLATFORMS." Journal of Information System and Technology Management 9, no. 35 (June 23, 2024): 01–20. http://dx.doi.org/10.35631/jistm.935001.
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The revolution of the internet has given rise to the development of electronic wallets (E-Wallets). This digital version of the physical wallet has gained popularity due to its convenience, security, and ease of use. The Malaysian government has launched many campaigns and initiatives to support the transformation of traditional payment methods to cashless payment methods resulting in competitive markets within the total 42 E-wallet providers. In this study, we identify and contrast the specific demographic and behavioral profiles of users across different popular e-wallet platforms. This study was carried out quantitatively by analyzing the Google form survey data obtained from 180 Malaysian respondents based on different platforms. The analysis shows that overall Touch N Go has recorded the highest usage among the users at 51.11% followed by MAE and other platforms at 28.33% and 20.56% respectively. This result is consistent with the demography on gender, location, employment, income, and education level except in demography on age, rating of e-wallet usage purpose, and perception of the e-wallet. Our finding also addressed that a sample size of 180 respondents was not sufficient to fully represent the entire population of Malaysia. Therefore, the adoption of a stratified sampling method consisting of all states within Malaysia is more appropriate.
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Podzolkova, Tetiana. "THE USE OF THE PROFILING METHOD IN THE INVESTIGATION OF CRIMINAL OFFENSES RELATED TO AIR TRANSPORT SECURITY BREACHES." Archives of Criminology and Forensic Sciences 7, no. 1 (June 18, 2022): 152–57. http://dx.doi.org/10.32353/acfs.7.2023.14.
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This scientific article is devoted to the study of the problem of air transport security and the investigation of crimes related to its violation. Crimes related to air transport security can have serious consequences and threaten people’s lives. The authors of the article note that effective investigation and identification of criminals are crucial in such situations.
One of the innovative approaches explored in the article is criminal profiling. This method of crime research is based on the analysis of behavioral, psychological and other characteristics of criminals. The use of criminal profiling can be extremely valuable in the investigation of criminal offenses aimed at violating air transport security.
The article examines the structure of criminal profiling, which consists of three levels of analysis: operational, tactical and strategic.
The importance of ensuring the safety of air transport and the need for effective investigation of crimes related to it are emphasized. The use of criminal profiling, in particular through operational, tactical and strategic analysis, can be a valuable tool for the detection and prevention of criminal offenses that threaten the safety of air transport.
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Suh, Jong Hwan. "Multi-Label Prediction-Based Fuzzy Age Difference Analysis for Social Profiling of Anonymous Social Media." Applied Sciences 14, no. 2 (January 17, 2024): 790. http://dx.doi.org/10.3390/app14020790.
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Age is an essential piece of demographic information for social profiling, as different social and behavioral characteristics are age-related. To acquire age information, most of the previously conducted social profiling studies have predicted age information. However, age predictions in social profiling have been very limited, because it is difficult or impossible to obtain age information from social media. Moreover, age-prediction results have rarely been used to study human dynamics. In these circumstances, this study focused on naver.com, a nationwide social media website in Korea. Although the social profiles of news commenters on naver.com can be analyzed and used, the age information is incomplete (i.e., partially open to the public) owing to anonymity and privacy protection policies. Therefore, no prior research has used naver.com for age predictions or subsequent analyses based on the predicted age information. To address this research gap, this study proposes a method that uses a machine learning approach to predict the age information of anonymous commenters on unlabeled (i.e., with age information hidden) news articles on naver.com. Furthermore, the predicted age information was fused with the section information of the collected news articles, and fuzzy differences between age groups were analyzed for topics of interest, using the proposed correlation–similarity matrix and fuzzy sets of age differences. Thus, differentiated from the previous social profiling studies, this study expands the literature on social profiling and human dynamics studies. Consequently, it revealed differences between age groups from anonymous and incomplete Korean social media that can help in understanding age differences and ease related intergenerational conflicts to help reach a sustainable South Korea.
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Rodrigues, Ana Carolina Cavalcante, Caroline Vitória de Lima Moreira, Camila Carlos Prado, Luan Silvestro Bianchini Silva, Rafael Fernandes Costa, Adesina Paul Arikawe, Gustavo Rodrigues Pedrino, et al. "A comparative analysis of depressive-like behavior: Exploring sex-related differences and insights." PLOS ONE 18, no. 11 (November 29, 2023): e0294904. http://dx.doi.org/10.1371/journal.pone.0294904.
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Profiling the variability related to the estrous cycle is essential for assessing depressive-like behavior and screening drugs. This study compares circulating plasma corticosterone levels [CORT] and behavioral alterations in mice exposed to sucrose preference, forced swimming, and tail suspension tests (SPT, FST, and TST, respectively). While SPT exposure did not significantly alter [CORT], FST and TST showed notable changes. Mice in the TST exhibited increased movement and decreased immobility time compared to FST, suggesting a lower likelihood of depressive-like behavior in male mice. Notably, during the proestrus phase, female mice displayed the highest tendency for depressive-like behavior and elevated [CORT], but similar response to antidepressants (imipramine and fluoxetine). The inherent stress of the FST and TST tasks appears to influence [CORT] as well as depressant and antidepressant effects. These comparisons provide valuable insights for further behavioral phenotyping, model sensitivity assessment, and deepen our neurobiological understanding of depression in the context of drug screening.
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Radder, Laetitia, and Xiliang Han. "Segmenting And Profiling South African Minibus Taxi Commuters: A Factor-Cluster-Tabulation Analysis Approach." International Business & Economics Research Journal (IBER) 10, no. 12 (November 23, 2011): 127. http://dx.doi.org/10.19030/iber.v10i12.6656.
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Privately-owned minibus taxis provide public transportation to 65% of South African households. However, relatively little is known about the characteristics and expectations of these commuters. This research identified the underlying dimensions of minibus taxi commuters expectations, documented market segments based on these dimensions and reports the differences between the segments with respect to their demographic and behavioral characteristics. Following a factor-cluster-tabulation analysis, three sets of expectations, namely, safety, suitability and substantiality and three segments, namely, anxious users, concerned users and apprehensive users were identified. This study showed that expectations, a less common segmentation base, is effective in dividing the market and provides knowledge of consumer identification that can serve as a source of better customer service.
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Rokhilawati, Yeny, Rachmasari Pramita Wardhani, and Syamsu Rijal. "A Bibliometric Exploration of Behavioral Finance: Trends, Influental Authors, Research Themes, and Emerging Concepts." International Journal of Business, Law, and Education 5, no. 1 (February 6, 2024): 501–9. http://dx.doi.org/10.56442/ijble.v5i1.413.
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This bibliometric exploration delves into the evolving landscape of behavioral finance, employing a systematic analysis of scholarly publications from the past decade. The study maps key trends, influential authors, research themes, and emerging concepts within the interdisciplinary realm of behavioral finance, blending insights from psychology and economics. Through rigorous data collection and analysis using VOS Viewer, the research addresses four critical questions: identifying trends, profiling influential authors, categorizing research themes, and exploring potential future directions. The study reveals a dynamic field with a focus on psychological factors influencing financial decision-making. Key findings include influential authors such as Hirshleifer and Statman, thematic clusters encompassing market efficiency and investor sentiment, and emerging areas of interest like the impact of COVID-19 on financial behavior. The implications of this research extend to academia, practice, and policy, providing a valuable resource for navigating the complex landscape of behavioral finance.
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Chakravarty, Sumana, and Arvind Kumar. "Insight into Cocaine-Induced Neural and Behavioral Adaptations Using Genome-Wide Expression Profiling and Epigenomic Analysis." Current Psychopharmacology 1, no. 4 (September 1, 2012): 332–43. http://dx.doi.org/10.2174/2211556011201040332.
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Sanders, Lindsey, William Dudley, Jeffrey Milroy, and David Wyrick. "Profiling of Student-Athletes using Protective Behavioral Strategies and Alcohol Use Based on Cluster Analysis Assignment." Social Work and Social Sciences Review 20, no. 2 (November 3, 2019): 113–30. http://dx.doi.org/10.1921/swssr.v20i2.1246.
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An estimated 2 in 3 college students report consuming alcohol in the past month and 44% of students report engaging in high risk or heavy episodic drinking at least once in the previous 2 weeks. Despite evidence suggesting that participation in sports may be a protective factor for the use of alcohol, recent data from the National Collegiate Athletic Association (NCAA), finds that 77% college student-athletes report use. Though overall prevalence rates of alcohol consumption are similar among college student-athletes and non-athletes, student-athletes are more likely to engage in binge or high-risk drinking as compared to their non-athlete peers. An overwhelming majority of studies found that protective behavioral strategy (PBS) use was associated with less drinking and alcohol-related problems. There are sport-related factors that have been assessed to determine their association with use of alcohol-related PBS. With known factors in mind, prevention programs are typically developed to effect distal outcomes by way of these, more proximal, intermediate constructs that are thought to be related to the health problem of interest. The purpose of the current study was to examine the structural features that influence whether a given student-athlete will be categorized into one of three groups; a) high-risk drinking behaviors, b) moderate risk drinking behaviors, or c) low risk drinking behaviors.
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Condomitti, Ulisses. "Criminal Profiling: Application of The FBI’s Typology in Homicides Occurred in the City of São Paulo." Brazilian Journal of Forensic Sciences, Medical Law and Bioethics 10, no. 3 (June 30, 2021): 441–58. http://dx.doi.org/10.17063/bjfs10(3)y2021441-458.
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The criminal profiling technique, developed in the second half of the last century, has proved to be a useful resource as an investigative technique, especially when conventional techniques have not been productive and is closely associated with the Behavioral Sciences and with Forensic Criminology, being used to direct to investigate by reducing the number of suspects in a crime. Among the various methodologies available, the Crime Scene Analysis stands out, popularly known as the “FBI Method”, developed by agents from the Behavioral Science Unit (BSU - Behavioral Science Unit) of the FBI (Federal Bureau of Investigation, an organ American investigation agency of federal autarchy, which has certain similarities to the Federal Police of Brazil) from the 1980s. In this article, the application of such methodology for the initial characterization of the criminal profile of homicide suspects ant authors in the city of São Paulo through the study of real cases in which the author worked, performing the examination of the crime scene.
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Karakoyun, Ferit, and Bülent Başaran. "Profiling University Students’ Technology Acceptance Through UTAUT." Malaysian Online Journal of Educational Technology 12, no. 2 (May 30, 2024): 78–92. http://dx.doi.org/10.52380/mojet.2024.12.2.550.
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Several studies have been conducted on e-learning acceptance among university students. Most of these studies examined various factors and individual characteristics as predictors of actual use and behavioral intention for e-learning systems. However, latent profile analysis was used in the present study, adopting a person-centered approach. Accordingly, the study’s primary purpose was to define LMS acceptance profiles by grouping university students based on gender according to four main UTAUT predictor variables. The secondary purpose was to examine the extent to which LMS acceptance profiles had a relationship with the students' online self-regulation and engagement in online learning environments. The participants in the study were 397 students from a state university in Turkey who continued their distance education. Student Engagements Scale, Online Self-regulation Questionnaire, and Learning Management System Acceptance Scale were used to collect data. The obtained data were analyzed using latent profile analysis. The results obtained in the study revealed that there were three different student profiles: "very low LMS acceptance", "low LMS acceptance", and "high LMS acceptance". According to another result, it was seen that low online self-regulation and engagement had a relationship with a student profile with very low LMS acceptance and that high online self-regulation and engagement had a relationship with a student profile with high LMS acceptance. Based on the findings, various implications were made about increasing students' LMS acceptance.
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Sunday, Nworie Felix, and Onele Monday. "Prioritizing and Optimizing Sustainable Measures for Municipal Solid Waste Prevention and Management Through Online and Distance Learning Approaches." Journal of Solid Waste Technology and Management 48, no. 1 (February 1, 2022): 34–46. http://dx.doi.org/10.5276/jswtm/2022.34.
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Waste prevention and management especially in Africa has for decades posited serious environmental challenges such as water, land and air pollution. This research seeks to address a scenario of profiling waste types and design intervention stimulating behavioral change and designs solid municipal waste prevention programme with limited economic resources in mind to arrive at the maximum environmental impact prevention within the municipal solid waste life cycle. A methodology employing cross-sectional and multi-stage simple random sampling technique was proposed. Data was collected by use of structured questionnaire. Classical statistical analyses were processed using SPSS19.0 software. The proposed method was helpful profiling households' attitude and measures that should be prioritized as high environmental impact. The impact of online and distance learning programme on the behavioral and municipal waste generation and prevention was profiled. Result indicated that online and distance learning programmes enhance households' knowledge of waste prevention and management.
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Carlyle, Becky C., Alvaro Duque, Robert R. Kitchen, Kelly A. Bordner, Daniel Coman, Eliza Doolittle, Xenophonios Papademetris, Fahmeed Hyder, Jane R. Taylor, and Arthur A. Simen. "Maternal separation with early weaning: A rodent model providing novel insights into neglect associated developmental deficits." Development and Psychopathology 24, no. 4 (October 15, 2012): 1401–16. http://dx.doi.org/10.1017/s095457941200079x.
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AbstractChild neglect is the most prevalent form of child maltreatment in the United States, and poses a serious public health concern. Children who survive such episodes go on to experience long-lasting psychological and behavioral problems, including higher rates of post-traumatic stress disorder symptoms, depression, alcohol and drug abuse, attention-deficit/hyperactivity disorder, and cognitive deficits. To date, most research into the causes of these life-long problems has focused on well-established targets such as stress responsive systems, including the hypothalamus–pituitary–adrenal axis. Using the maternal separation and early weaning model, we have attempted to provide comprehensive molecular profiling of a model of early-life neglect in an organism amenable to genomic manipulation: the mouse. In this article, we report new findings generated with this model using chromatin immunoprecipitation sequencing, diffuse tensor magnetic resonance imaging, and behavioral analyses. We also review the validity of the maternal separation and early weaning model, which reflects behavioral deficits observed in neglected humans including hyperactivity, anxiety, and attentional deficits. Finally, we summarize the molecular characterization of these animals, including RNA profiling and label-free proteomics, which highlight protein translation and myelination as novel pathways of interest.
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Turvey, B., and Karen Ward. "Book Review: Criminal Profiling: An Introduction to Behavioural Evidence Analysis." Australian & New Zealand Journal of Criminology 33, no. 3 (December 2000): 371–73. http://dx.doi.org/10.1177/000486580003300310.
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Terekhov, Stanislav S., Ivan V. Smirnov, Maja V. Malakhova, Andrei E. Samoilov, Alexander I. Manolov, Anton S. Nazarov, Dmitry V. Danilov, et al. "Ultrahigh-throughput functional profiling of microbiota communities." Proceedings of the National Academy of Sciences 115, no. 38 (September 4, 2018): 9551–56. http://dx.doi.org/10.1073/pnas.1811250115.
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Microbiome spectra serve as critical clues to elucidate the evolutionary biology pathways, potential pathologies, and even behavioral patterns of the host organisms. Furthermore, exotic sources of microbiota represent an unexplored niche to discover microbial secondary metabolites. However, establishing the bacterial functionality is complicated by an intricate web of interactions inside the microbiome. Here we apply an ultrahigh-throughput (uHT) microfluidic droplet platform for activity profiling of the entire oral microbial community of the Siberian bear to isolate Bacillus strains demonstrating antimicrobial activity against Staphylococcus aureus. Genome mining allowed us to identify antibiotic amicoumacin A (Ami) as responsible for inhibiting the growth of S. aureus. Proteomics and metabolomics revealed a unique mechanism of Bacillus self-resistance to Ami, based on a subtle equilibrium of its deactivation and activation by kinase AmiN and phosphatase AmiO, respectively. We developed uHT quantitative single-cell analysis to estimate antibiotic efficacy toward different microbiomes and used it to determine the activity spectra of Ami toward human and Siberian bear microbiota. Thus, uHT microfluidic droplet platform activity profiling is a powerful tool for discovering antibiotics and quantifying external influences on a microbiome.
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Lei, Zhang, and Nor Shahniza Kamal Bashah. "Internet behavioral models for improving internet quality of service or user profiling: a systematic literature review." International Journal of Electrical and Computer Engineering (IJECE) 14, no. 4 (August 1, 2024): 4352. http://dx.doi.org/10.11591/ijece.v14i4.pp4352-4364.
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Internet behavior models have found applications across diverse domains, notably in internet addiction, customer satisfaction analysis, user purchasing behavior prediction, and optimizing internet of things (IoT) sensor performance. However, a notable gap exists in exploring these models in enhancing internet quality of service (QoS), specifically in campus settings, intricately linked to the nuances of students' online behavior. This study elucidates the strategic utilization of internet behavioral models for augmenting internet QoS and facilitating user behavior analysis. Creating datasets grounded in internet users' access behavior represents a pivotal phase, with explicit, implicit, and mixed methods emerging as the prevailing approaches. In this comprehensive literature review, we systematically scrutinized the methods, techniques, and inherent characteristics of constructing internet behavior models according to a systematic literature review process. The qualitative findings extracted from the systematic review encapsulated 1,046 articles, meticulously classified according to predefined inclusion and exclusion criteria. Subsequently, 35 articles were judiciously selected for in-depth analysis. This study culminated in identifying the most pertinent methodologies and salient features pivotal to construct robust internet behavior model for improving internet QoS and user experience.
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Frydecka, Dorota, Małgorzata Krzystek-Korpacka, Alba Lubeiro, Filip Stramecki, Bartłomiej Stańczykiewicz, Jan Aleksander Beszłej, Patryk Piotrowski, et al. "Profiling inflammatory signatures of schizophrenia: A cross-sectional and meta-analysis study." Brain, Behavior, and Immunity 71 (July 2018): 28–36. http://dx.doi.org/10.1016/j.bbi.2018.05.002.
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Kaliuha, K. "SOME ASPECTS OF THE HISTORY OF THE APPLICATION OF THE PROFILING METHOD." Criminalistics and Forensics, no. 65 (May 18, 2020): 308–16. http://dx.doi.org/10.33994/kndise.2020.65.29.
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The article is devoted to the analysis of the origins of the method of profiling the identity of an unknown criminal. The development of the application of the possibilities of profiling the personality of a criminal and the practice of its application in the activities of law enforcement agencies in the investigation of crimes are investigated. Based on the concept of profiling, as from English. Profile is an integrated crime prevention technique by highlighting the characteristics of persons who committed a crime or are preparing to make it on the basis of psychological, criminological, criminalistic and sociological knowledge; a set of methods and techniques for assessing and predicting human behavior based on the analysis of the most informative signs, forensic portrait of a person, characteristics of appearance, non-verbal and verbal behavior, location, etc. We noted that there is a lot of research by foreign and Ukrainian scientists on the problems of using profiling technology, but not enough attention has been paid to the history of the practice of applying the profiling method. The main names of scientists and the features of their teachings were listed in the abstract, as the stages of development of the introduction of the profiling method in the practice of disclosing and investigating crimes by law enforcement agencies. We said that now the technology of the profiling method is not used as a mandatory measure in the investigation and disclosure of crimes. There are fundamentals of such activities, but it is too early to talk about the widespread use of profiling. At the same time, it can be noted that profiling was successfully used in the disclosure of some resonant crimes related to serial killings. We agreed with individual authors that research on forensic profiling and the behavioral aspects of crimes in Ukraine are in the early stages of development. We noted that since profiling is a young science, it is constantly evolving, and its fields of application are expanding. Today, profiling techniques are used in the field of preventive medicine to correct and prevent the emergence of diseases of psychosomatic etiology. There is also the so-called family profiling, with the help of which specialists try to help family members in solving their family problems. In addition to forensic, criminal and criminological, there is aviation, anti-terrorist, research, psychological, information security profiling, typological. Also, transport, hotel business profiling, personnel, banking and the like. We concluded that profiling technology is a universal comprehensive and modern tool that is advisable to use in law enforcement agencies in investigative, operational, personnel and administrative activities, etc. The history of its development is only gaining momentum. However, today, in law enforcement agencies, not only the profiling technique is not widely used. They do not use this term at all.
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Khafizova, G. V., O. Y. Naumova, A. L. Lopez, and E. L. Grigorenko. "Experimental Design and Behavioral Testing Protocol for the Evaluation of Cognitive Abilities and Social Behavior in Mice Following Early Life Stress." Современная зарубежная психология 13, no. 1 (April 27, 2024): 78–91. http://dx.doi.org/10.17759/jmfp.2024130107.
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<p style="text-align: justify;">This manuscript presents a protocol designed for the comprehensive investigation of early life stress (ELS) outcomes and a feasibility study conducted with this protocol. ELS alters normal development by interfering at various levels: hormonal changes, brain cellular architecture, epigenome, and chromosomal structural elements. The protocol combines classic behavioral tests with advanced molecular techniques to obtain comprehensive data and thus uncover the underlying mechanisms of ELS. In this protocol, the main source of stress is maternal separation. Briefly, a group of C57Bl/6 mice undergoes maternal separation; then, mice perform the radial maze test and the resident-intruder test. As a control, another group of mice stays undisturbed and performs the same behavioral tests in the same timeframe. After the behavioral tests, biosamples are collected, including urine for corticosterone measurements, peripheral blood, hippocampus, amygdala, and prefrontal cortex tissues for DNA isolation and its downstream analyses (DNA methylation profiling and telomere length measuring), and whole brains for immunohistochemistry analysis of the glucocorticoid receptor density. This protocol was successfully tested as a feasibility study for a large-scale investigation that addresses potential flaws to establish a robust methodology. This paper reports on a comprehensive approach to examining multiple aspects of development that interrogates a holistic analysis of multilayer and multidimensional data and may contribute valuable insights for both animal and human studies.</p>
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Xie, Guanbo, Yihan Qin, Ning Wu, Xiao Han, and Jin Li. "Single-Nucleus Transcriptome Profiling from the Hippocampus of a PTSD Mouse Model and CBD-Treated Cohorts." Genes 15, no. 4 (April 21, 2024): 519. http://dx.doi.org/10.3390/genes15040519.
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Post-traumatic stress disorder (PTSD) is the most common psychiatric disorder after a catastrophic event; however, the efficacious treatment options remain insufficient. Increasing evidence suggests that cannabidiol (CBD) exhibits optimal therapeutic effects for treating PTSD. To elucidate the cell-type-specific transcriptomic pathology of PTSD and the mechanisms of CBD against this disease, we conducted single-nucleus RNA sequencing (snRNA-seq) in the hippocampus of PTSD-modeled mice and CBD-treated cohorts. We constructed a mouse model by adding electric foot shocks following exposure to single prolonged stress (SPS+S) and tested the freezing time, anxiety-like behavior, and cognitive behavior. CBD was administrated before every behavioral test. The PTSD-modeled mice displayed behaviors resembling those of PTSD in all behavioral tests, and CBD treatment alleviated all of these PTSD-like behaviors (n = 8/group). Three mice with representative behavioral phenotypes were selected from each group for snRNA-seq 15 days after the SPS+S. We primarily focused on the excitatory neurons (ExNs) and inhibitory neurons (InNs), which accounted for 68.4% of the total cell annotations. A total of 88 differentially upregulated genes and 305 differentially downregulated genes were found in the PTSD mice, which were found to exhibit significant alterations in pathways and biological processes associated with fear response, synaptic communication, protein synthesis, oxidative phosphorylation, and oxidative stress response. A total of 63 overlapping genes in InNs were identified as key genes for CBD in the treatment of PTSD. Subsequent Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses revealed that the anti-PTSD effect of CBD was related to the regulation of protein synthesis, oxidative phosphorylation, oxidative stress response, and fear response. Furthermore, gene set enrichment analysis (GSEA) revealed that CBD also enhanced retrograde endocannabinoid signaling in ExNs, which was found to be suppressed in the PTSD group. Our research may provide a potential explanation for the pathogenesis of PTSD and facilitate the discovery of novel therapeutic targets for drug development. Moreover, it may shed light on the therapeutic mechanisms of CBD.
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Addo, Isaac B., Martin C. Thoms, and Melissa Parsons. "Barriers and Drivers of Household Water-Conservation Behavior: A Profiling Approach." Water 10, no. 12 (December 6, 2018): 1794. http://dx.doi.org/10.3390/w10121794.
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Factors that influence behavioral response (barriers and drivers) are important for household water-conservation practices. These factors either support or inhibit sustainable behavior. In this research, a latent profile analysis (LPA) was used within the capability-, opportunity-, and motivation-behavior (COM-B) framework to identify key barriers and drivers of household water-conservation behaviors. Participants (N = 510, mean age = 56.08 years, SD = 14.71) completed measures of psycho-social constructs related to barriers and drivers of water-conservation behavior. An LPA yielded a 3-profile statistical solution: capability (35.8%), opportunity (23.2%), and motivation (41.0%) conceptualizing levels of barriers and drivers of water-conservation behavior. Major identified barriers and drivers associated with these profile groupings were time constraints, acuity of water-efficient devices, lack of skills to adopt conservation practices, and availability of incentives/disincentives for water-saving devices. Validation analyses showed that the three COM-B groups diverged considerably based on socio-demographic status and actual water-conservation behavior. Results are pertinent to water authorities in identifying interventions to reduce barriers and promote drivers of positive household water-conservation behaviors by altering and directing appropriate COM-B dimensions to individual water consumers.
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Zheng, Yujia, Yuhang Fang, Yan Jin, Xiayun Zuo, Qiguo Lian, Chaohua Lou, Chunyan Yu, Xiaowen Tu, Lihe Li, and Ping Hong. "Parenting Practice Profiling and Its Associated Factors among Secondary Vocational School Students in China." International Journal of Environmental Research and Public Health 19, no. 12 (June 18, 2022): 7497. http://dx.doi.org/10.3390/ijerph19127497.
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Background: Parenting styles have a tremendous influence on a child’s development and behavior. Studies on parenting styles using latent profile analysis have been increasing in recent years. However, there are few such studies conducted in China, especially concerning joint parenting styles (that simultaneously characterize maternal and paternal practices), which are held over the age group of secondary vocational school students. This study aimed to identify the profiles of parenting styles and their associated factors among the parents of secondary vocational school students in China, based on natural samples and not a predetermined model. Method: Data were drawn from a cross-sectional study conducted among 3180 students from six secondary vocational schools in Shanghai Municipality and Shaanxi Province. A total of 2392 students who have lived with their parents for most of their lifetime were included in the study. Latent profile analysis was used to identify the profiles of parenting styles of the respondent’s parents. Multinominal logistic regression models were used to examine the association between parenting style and demographic characteristics and family background and adolescent outcomes. Results: We identified five latent profiles: “free-range parenting” (27.05%), “behavioral monitoring parenting” (33.65%), “authoritative parenting” (11.75%), “psychological control parenting” (14.38%) and “tiger parenting” (13.17%). The associations between these profiles and adolescent outcomes indicated that these profiles were rational. Participants’ gender, grade, residential area, family economic level, parental marital relationship, and parental educational level were predictive factors for parenting styles. Conclusions: The parenting styles held over secondary vocational school students were somewhat different from Baumrind’s parenting style model. A considerable number of students received a parenting style that might predispose them to behavioral and mental health outcomes and merit a tailored intervention using the predictive factors of parenting styles.
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Pashupatimath, Anand. "Novel Approach to Detect APT (Advanced Persistent Threat)." International Journal for Research in Applied Science and Engineering Technology 12, no. 4 (April 30, 2024): 2440–45. http://dx.doi.org/10.22214/ijraset.2024.60342.
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Abstract: In cyber security, APT stands for Advanced Persistent Threat. It refers to advanced and long-term cyber-attacks where an attacker gains unauthorized access to a network and remains invisible for a long period of time. APTs are difficult to detect and require a comprehensive security strategy that includes threat intelligence, technical intelligence, and continuous monitoring to effectively mitigate risk. This paper introduces a different approach to APT prevention by integrating advanced threat intelligence, machine learning algorithms, and proactive defense mechanisms. Our approach uses real-time data analysis, anomaly detection and behavioral profiling to identify potential threats early in their lifecycle
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Basarudin, Noor Ashikin, and Ridwan Adetunji Raji. "Implication of Personalized Advertising on Personal Data: A Legal Analysis of the EU General Data Protection Regulation." Environment-Behaviour Proceedings Journal 7, no. 22 (November 30, 2022): 109–14. http://dx.doi.org/10.21834/ebpj.v7i22.4160.
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The accelerating emergence of personalised advertising is mostly driven by data. Accordingly, algorithmic profiling has become a constant experience for every online user in predicting preference and interest. The profiling process raises several issues of human privacy and personal data invasion. Therefore, this study adopts the doctrinal legal method through the analysis of International Instruments and the European Union General Data Protection Regulation as legal avenue to safeguard and protect online activities of the data subjects. The findings of this paper discuss the main principles to be observed by the data controller in ensuring the legality of personal data profiling. This paper suggests the profiling process to be design-based security due to unavailability of system procedure to human knowledge. Keywords: Personalised Advertising; Algorithmic Targeting; Personal Data Profiling; EU General Data Protection Regulation eISSN: 2398-4287 © 2022. The Authors. Published for AMER ABRA cE-Bs by e-International Publishing House, Ltd., UK. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). Peer–review under responsibility of AMER (Association of Malaysian Environment-Behaviour Researchers), ABRA (Association of Behavioural Researchers on Asians/Africans/Arabians) and cE-Bs (Centre for Environment-Behaviour Studies), Faculty of Architecture, Planning & Surveying, Universiti Teknologi MARA, Malaysia. DOI: https://doi.org/10.21834/ebpj.v7i22.4160
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GOKOOL, SUZANNE, C. F. CURTIS, and DEBORAH F. SMITH. "Analysis of mosquito bloodmeals by DNA profiling." Medical and Veterinary Entomology 7, no. 3 (July 1993): 208–15. http://dx.doi.org/10.1111/j.1365-2915.1993.tb00678.x.
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Addisu Worku, Teshome, and Worku Martha Degefu. "Profiling children with cerebral visual impairment in a tertiary eye care center." International Journal of Clinical and Experimental Ophthalmology 6, no. 1 (April 7, 2022): 007–12. http://dx.doi.org/10.29328/journal.ijceo.1001043.
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Background: Cerebral visual impairment (CVI) is a bilateral visual impairment that affects children in all industrialized countries. It has become more common in low-income countries as a result of the increased survival rates of children who suffer from severe neurological conditions during the perinatal period. The purpose of this study was to determine the characteristics of children with CVI in a tertiary children’s eye care center population. Methods: From October 2020 to September 2021, a cross-sectional study was conducted to select all consecutive patients with a diagnosis of cerebral visual impairment aged 6 months to 16 years. On the neurological deficit, information was gathered from the patient’s referral: parental interviews, observations, and direct assessment were used for functional vision characteristics, and an ophthalmic examination was performed for eye findings. The interviewees’ responses were matched to the ten specific behavioral characteristics shared by children with CVI. Cortical visual impairment was diagnosed using three criteria: [the vision loss is not explained by abnormalities found on the eye examination, a neurological medical diagnosis, and the child exhibits one of the unique visual and behavioral characteristics described by Roman Lantz]. A descriptive statistical analysis (frequency, mean, and range) was calculated. Results: Forty children with CVI (1.96% of total children) were seen. The mean age was 2.56 ( 1.98) years. There were 24 (60%) males. On a referral paper of 28, hypoxic-ischemic encephalopathy was the commonest cause mentioned (70.0%). Seizures were the most frequent neurological deficit at presentation. Ophthalmic and neurologic impairments were found in 42.5% of children with CVI. Based on Roman-Lantzy’s three phases of the CVI Range, 90% of children with CVI at the test time had Phase I or Phase II vision. Conclusion: According to the findings of this study, visual impairment is critical in the diagnosis of CVI. The prevalence of CVI as a cause of childhood vision impairment is significant. Hypoxic-ischemic encephalopathy is the most common cause of CVI. All children with CVI have serious neurological issues, and the majority have associated ophthalmic abnormalities.
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Sukhodolov, Alexander, Marina Kaluzhina, Boris Spasennikov, and Viktor Kolodin. "Digital Criminology: the Mmethod of Digital Profiling of an Unidentified Criminal's Behavior." Russian Journal of Criminology 13, no. 3 (July 4, 2019): 385–94. http://dx.doi.org/10.17150/2500-4255.2019.13(3).385-394.
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The authors examine the specific features of the digital environment to analyze contemporary approaches to the system of instruments of studying illegal actions in cyberspace. They state that law enforcement bodies should adapt key characteristics of the digital environment to the accomplishment of investigation tasks. The authors analyze the possibilities offered by digital profiling and modeling of the digital profile (portrait) of an unidentified criminal through mathematical methods of modeling and prediction in investigating and solving serial crimes, including cybercrimes. An extensive review of Russian and foreign publications is used to study the evolution of scientific ideas regarding the profiling method, which is the basis for the digital profiling of the behavioral model of an unidentified criminal in the digital environment. It is stated that none of the branches of criminal law, including criminology and criminalistics, could alone solve the interdisciplinary problem of the investigation and detection of crimes in the digital environment. The authors prove that it is necessary to integrate the knowledge of these branches and to conduct interdisciplinary research involving experts, i.e. to duly streamline the organization of those activities that together make up the investigation and detection of crimes. Based on the content of the concept «modus operandi», which lies at the heart of building an abstract model of criminal behavior, they conclude that it could be used to investigate and solve crimes in the digital environment and determine the specific features of the content of its structural elements. The comparative analysis of the contents of the key stages of profiling is used to prove the expediency of employing the whole range of logical and mathematical methods of analysis to process and analyze criminological information, which leads to the necessity of both critically reviewing them and finding ways to go beyond the traditional approaches. The authors describe the essence of the mathematical extrapolation method, which is most commonly used in criminology for the quantitative analysis of knowledge regarding objects, phenomena, processes, as well as the possibility of using it in digital profiling. As a result of this research based on the systemic approach, the authors state the objective character of links between the traditional and the digital profiling, point out the existing links and regularities, which allow them to reduce the essence of the examined phenomena to building a model through the recreation, in the process of investigation, of the mental trace pattern and then using it to find the guilty person.
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Wang, Bingyao. "Psychological AI: A critical analysis of capabilities, limitations, and ramifications." Applied and Computational Engineering 53, no. 1 (March 28, 2024): 205–12. http://dx.doi.org/10.54254/2755-2721/53/20241373.
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As artificial intelligence (AI) continues to advance, machine learning and natural language processing (NLP) offer new possibilities in various areas of psychology, such as therapy, diagnostics, treatment planning, demographic profiling, sentiment analysis, and consumer psychology. However, AI research in psychology is still lacking. This study aims to explore the specific applications of AI in the field of psychology. Firstly, the article delves into the efficacy and cost-effectiveness of chatbots in delivering cognitive behavioral therapy (CBT). Next, the article explores the current state of AI in detecting mental health disorders, highlighting the use of digital footprints as a diagnostic tool. Furthermore, the research investigates how AI can assist medical professionals in developing focused treatment plans. It analyzes studies that aim to optimize treatment strategies using AI technologies. The article also examines the influence of demographic characteristics on our understanding and application of psychology. Lastly, the article touches on the use of AI in analyzing sentiment to understand and predict consumer behavior. Ethical implications of using AI-driven psychological assessments are also discussed. It concludes with a summary of key findings and offers a glimpse into potential future developments in this field.
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Sofyan, Afriyadi, Nur Hidayah, M. Ramli, Siti Aminah, and Sisca Folastri. "Profiling Preferences of the Counseling Paradigm by School Counselors in Indonesia." KONSELOR 12, no. 3 (December 31, 2023): 211–21. http://dx.doi.org/10.24036/0202312349-0-86.
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This study aims to obtain an overview of the paradigm tendencies owned and practiced by school counselors in Indonesia. The study involved 233 school counselors in Indonesia on Sumatra, Java, and Bali islands. The research instrument reveals the counseling model that respondents use in providing counseling services (individual/group) and the reasons for its use. Statistics such as frequencies and percentages are used for quantitative data analysis. Qualitative data for reasons for specific counseling models were analyzed using Miles and Huberman data analysis. The results of this study show that school counselors most widely use behavior counseling models because they are effective in overcoming student behavior problems. This approach suits general needs and concerns and is easily understood with its techniques. The rational-emotive behavior therapy counseling model was chosen because it helps change mindsets to be more realistic and mature. This technique follows the needs and problems that arise and the development of adolescents who often act without consideration. Referring to Cotton's opinion, both models are counseling models that fall into the psychological paradigm. The tendency of school counselors to use psychological paradigms may be due to the psychology-focused counselor education curriculum, lack of resources or knowledge of other paradigms, and limitations of the school environment that encourage the use of traditional psychological approaches. School counselors must work with other school staff to integrate counseling approaches into the school program, which is essential. Professional organizations are expected to encourage training in behavioral counseling and REBT, supporting students' holistic education that includes academic, social, and emotional aspects.
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Kahla, Louis Zvikomborero. "Leveraging Artificial Intelligence for Crime Detection and Prevention." INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 08, no. 05 (May 17, 2024): 1–5. http://dx.doi.org/10.55041/ijsrem34207.
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This paper sheds light on how Artificial Intelligence (AI) is reshaping the landscape of crime detection and prevention, bringing about a significant change in traditional law enforcement methods. With society increasingly embracing AI-driven solutions, it's crucial to understand how they contribute to public safety. We'll dive into various aspects of AI, such as predictive policing, video surveillance analysis, forensic science, and criminal profiling, to see how they enhance law enforcement capabilities and streamline crime resolution processes.Starting with predictive policing, AI algorithms sift through massive datasets to identify patterns and predict future criminal activity, empowering law enforcement to take proactive measures. Similarly, AI-powered video surveillance systems enhance real-time monitoring and anomaly detection, allowing for quick identification of suspicious behavior in urban environments.Moving on, we'll explore AI's impact on forensic analysis, where it expedites processes like DNA sequencing, fingerprint recognition, and ballistics analysis, speeding up the resolution of cold cases. Additionally, we'll delve into AI's role in criminal profiling, highlighting its ability to decipher behavioral patterns and predict criminal motivations, though ethical considerations remain paramount.We'll also address ethical concerns surrounding AI deployment in law enforcement, including privacy issues and algorithmic biases. Emphasizing the need for transparency and accountability, we advocate for responsible use of AI-powered crime detection systems to uphold ethical standards and protect individual rights.
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Zanusso, Francesca, Barbara Contiero, Simona Normando, Flaviana Gottardo, and Giulia Maria De Benedictis. "Qualitative behavioral assessment of dogs with acute pain." PLOS ONE 19, no. 6 (June 21, 2024): e0305925. http://dx.doi.org/10.1371/journal.pone.0305925.
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Free Choice Profiling (FCP) methodology allows observers to qualitatively assess animal behavior using their own vocabulary. This study aims to investigate the ability of 3 different observer groups to recognize pain-related emotions in 20 dogs using FCP methodology, and to compare FCP data with the Glasgow Composite Pain Scale-Short Form (GCPS- SF) scores. The observer groups consisted of 10 dog owners, 10 veterinary students and 10 veterinarians. Ten healthy (“healthy”) dogs and 10 dogs showing clinical signs of pain (“pain”) were filmed, and the resulting 20 footages were shown to observers who were blind to the pain-related nature of the study. All observers described and scored animals’ emotional expression using FCP; then, students and veterinarians scored all dogs using GCPS- SF. FCP data were analyzed using Generalized Procrustes Analysis (GPA). Spearman correlation coefficient (ρ) was used to determine the correlation among observer groups’ FCP scores of the first two FCP dimensions (DIM1 and DIM2), and to compare GCPS-SF scores with FCP scores for the students and veterinarian observer groups. Each observer group reached a significant (p < 0.001) good consensus profile. “Healthy” dogs were mainly described as “quiet” and “lively”, while the majority of “pain” dogs were considered “in pain” and “suffering”. The correlation among FCP scores was high between owners’ DIM1 and students’ DIM1 (ρ = -0.86), owners’ DIM2 and students’ DIM2 (ρ = 0.72) and students’ DIM2 and vets’ DIM1 (ρ = 0.70). The correlation between GCPS-SF scores and FCP scores was high for students’ DIM2 (ρ = 0.77) and for veterinarians’ DIM1 (ρ = 0.92). Qualitative methods such as FCP could be used in association with semi-quantitative methods to evaluate the effect of pain on animal emotional expression. Observers’ cultural background and personal experience did not substantially affect qualitative behavioral assessment in dogs with acute somatic pain.
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Termignoni-Garcia, Flavia, Matthew I. M. Louder, Christopher N. Balakrishnan, Lauren O’Connell, and Scott V. Edwards. "Prospects for sociogenomics in avian cooperative breeding and parental care." Current Zoology 66, no. 3 (December 4, 2019): 293–306. http://dx.doi.org/10.1093/cz/zoz057.
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Abstract For the last 40 years, the study of cooperative breeding (CB) in birds has proceeded primarily in the context of discovering the ecological, geographical, and behavioral drivers of helping. The advent of molecular tools in the early 1990s assisted in clarifying the relatedness of helpers to those helped, in some cases, confirming predictions of kin selection theory. Methods for genome-wide analysis of sequence variation, gene expression, and epigenetics promise to add new dimensions to our understanding of avian CB, primarily in the area of molecular and developmental correlates of delayed breeding and dispersal, as well as the ontogeny of achieving parental status in nature. Here, we outline key ways in which modern -omics approaches, in particular genome sequencing, transcriptomics, and epigenetic profiling such as ATAC-seq, can be used to add a new level of analysis of avian CB. Building on recent and ongoing studies of avian social behavior and sociogenomics, we review how high-throughput sequencing of a focal species or clade can provide a robust foundation for downstream, context-dependent destructive and non-destructive sampling of specific tissues or physiological states in the field for analysis of gene expression and epigenetics. -Omics approaches have the potential to inform not only studies of the diversification of CB over evolutionary time, but real-time analyses of behavioral interactions in the field or lab. Sociogenomics of birds represents a new branch in the network of methods used to study CB, and can help clarify ways in which the different levels of analysis of CB ultimately interact in novel and unexpected ways.
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Shao, Yong, Hang-Yu Tian, Jing-Jing Zhang, Hamed Kharrati-Koopaee, Xing Guo, Xiao-Lin Zhuang, Ming-Li Li, et al. "Genomic and Phenotypic Analyses Reveal Mechanisms Underlying Homing Ability in Pigeon." Molecular Biology and Evolution 37, no. 1 (September 10, 2019): 134–48. http://dx.doi.org/10.1093/molbev/msz208.
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Abstract The homing pigeon was selectively bred from the domestic pigeon for a homing ability over long distances, a very fascinating but complex behavioral trait. Here, we generate a total of 95 whole genomes from diverse pigeon breeds. Comparing the genomes from the homing pigeon population with those from other breeds identifies candidate positively selected genes, including many genes involved in the central nervous system, particularly spatial learning and memory such as LRP8. Expression profiling reveals many neuronal genes displaying differential expression in the hippocampus, which is the key organ for memory and navigation and exhibits significantly larger size in the homing pigeon. In addition, we uncover a candidate gene GSR (encoding glutathione-disulfide reductase) experiencing positive selection in the homing pigeon. Expression profiling finds that GSR is highly expressed in the wattle and visual pigment cell layer, and displays increased expression levels in the homing pigeon. In vitro, a magnetic field stimulates increases in calcium ion concentration in cells expressing pigeon GSR. These findings support the importance of the hippocampus (functioning in spatial memory and navigation) for homing ability, and the potential involvement of GSR in pigeon magnetoreception.
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Geurts, Karolien, Geert Wets, Tom Brijs, and Koen Vanhoof. "Profiling of High-Frequency Accident Locations by Use of Association Rules." Transportation Research Record: Journal of the Transportation Research Board 1840, no. 1 (January 2003): 123–30. http://dx.doi.org/10.3141/1840-14.
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In Belgium, traffic safety is one of the government's highest priorities. The identification and profiling of black spots and black zones (geographical locations with high concentrations of traffic accidents) in terms of accident-related data and location characteristics must provide new insights into the complexity and causes of road accidents, which, in turn, provide valuable input for governmental actions. Association rules were used to identify accident-related circumstances that frequently occur together at high-frequency accident locations. Furthermore, these patterns were analyzed and compared with frequently occurring accident-related characteristics at low-frequency accident locations. The strength of this approach lies with the identification of relevant variables that make a strong contribution toward obtaining a better understanding of accident circumstances and the discerning of descriptive accident patterns from more discriminating accident circumstances to profile black spots and black zones. This data-mining algorithm is particularly useful in the context of large data sets for road accidents, since data mining can be described as the extraction of information from large amounts of data. The results showed that human and behavioral aspects are of great importance in the analysis of frequently occurring accident patterns. These factors play an important role in identifying traffic safety problems in general. However, the accident characteristics that were the most discriminating between high-frequency and low-frequency accident locations are mainly related to infrastructure and location.
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Kasote, Deepak, Tasneem Suleman, Weiyang Chen, Maxleene Sandasi, Alvaro Viljoen, and Sandy van Vuuren. "Chemical profiling and chemometric analysis of South African propolis." Biochemical Systematics and Ecology 55 (August 2014): 156–63. http://dx.doi.org/10.1016/j.bse.2014.03.012.
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You, Samantha, Alder M. Yu, Mary A. Roberts, Ivanna J. Joseph, and F. Rob Jackson. "Circadian regulation of the Drosophila astrocyte transcriptome." PLOS Genetics 17, no. 9 (September 20, 2021): e1009790. http://dx.doi.org/10.1371/journal.pgen.1009790.
Full textAbstract:
Recent studies have demonstrated that astrocytes cooperate with neurons of the brain to mediate circadian control of many rhythmic processes including locomotor activity and sleep. Transcriptional profiling studies have described the overall rhythmic landscape of the brain, but few have employed approaches that reveal heterogeneous, cell-type specific rhythms of the brain. Using cell-specific isolation of ribosome-bound RNAs in Drosophila, we constructed the first circadian “translatome” for astrocytes. This analysis identified 293 “cycling genes” in astrocytes, most with mammalian orthologs. A subsequent behavioral genetic screen identified a number of genes whose expression is required in astrocytes for normal sleep behavior. In particular, we show that certain genes known to regulate fly innate immune responses are also required for normal sleep patterns.