Relevant bibliographies by topics / Abuse detection

Academic literature on the topic 'Abuse detection'

Author: Grafiati
Published: 7 July 2024
Last updated: 7 July 2024

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Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Journal articles on the topic "Abuse detection":

1

Kiyohara, Sheri M. "Child Abuse Detection." Journal of Child Sexual Abuse 4, no. 2 (September 1995): 105–8. http://dx.doi.org/10.1300/j070v04n02_07.

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2

A. Harries, Priscilla, Miranda L. Davies, Kenneth J. Gilhooly, Mary L.M. Gilhooly, and Deborah Cairns. "Detection and prevention of financial abuse against elders." Journal of Financial Crime 21, no. 1 (December 20, 2013): 84–99. http://dx.doi.org/10.1108/jfc-05-2013-0040.

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Purpose – This paper reports on banking and finance professionals' decision making in the context of elder financial abuse. The aim was to identify the case features that influence when abuse is identified and when action is taken. Design/methodology/approach – Banking and finance professionals (n=70) were shown 35 financial abuse case scenarios and were asked to judge how certain they were that the older person was being abused and the likelihood of taking action. Findings – Three case features significantly influenced certainty of financial abuse: the nature of the financial problem presented, the older person's level of mental capacity and who was in charge of the client's money. In cases where the older person was more confused and forgetful, there was increased suspicion that financial abuse was taking place. Finance professionals were less certain that financial abuse was occurring if the older person was in charge of his or her own finances. Originality/value – The research findings have been used to develop freely available online training resources to promote professionals' decision making capacity (www.elderfinancialabuse.co.uk). The resources have been advocated for use by Building Societies Association as well as CIFAS, the UK's Fraud Prevention Service.
3

de la Parte-Serna, Alejandro Carlos, Gonzalo Oliván-Gonzalvo, Cosmina Raluca Fratila, Mariona Hermoso-Vallespí, Andrea Peiró-Aubalat, and Ricardo Ortega-Soria. "The dark side of Paediatric dentistry: Child abuse." Iberoamerican Journal of Medicine 2, no. 3 (April 5, 2020): 194–200. http://dx.doi.org/10.53986/ibjm.2020.0035.

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Background: Children who have been abused could exhibit lesions and diseases in their oral cavity and develop psychological consequences towards the dentist-patient relationship. Objectives: Analyse the oral lesions and diseases, the psychological consequences and understand the role of the dentist in the detection and notification of child abuse. Methods: Systematic review, according to PRISMA statement, with two search strategies in the MEDLINE/PubMed database. 19 publications were included after the application of selection and eligibility criteria. Results: Physical-abuse-related lesions and Münchausen syndrome are not pathognomonic; this requires the detection of indicators of suspicion. Physical-neglect diseases usually have associated other chronic health problems. Specifically, diseases related to sexual abuse are the oral infection caused by Treponema pallidum and Neisseria gonorrhoeae; while other lesions and diseases might only suggest abuse. The most frequent psychological sign of child abuse in the dentist-patient relationship is dental phobia. Typically, when detecting and notifying, dentist face the following barriers: insufficient information; fear of wrong suspicion; impact in the professional practice; fear of consequences on the minor; fear of violence against the dentist; lack of knowledge of necessary documents/procedures; fear of judicial statement. Conclusions: Child-abuse-related lesions and diseases often appear in the oral region. Dentists play a fundamental role in the detection and notification of those. It is essential to establish training and action protocols as well as reliance strategies in the patient-dentist relationship.
4

Marlinda, Evy, Syamsul Firdaus, and Haitami Haitami. "DILAN (DETEKSI DINI-LANJUT) NARKOBA PELAJAR SMPN-3 KECAMATAN CEMPAKA KOTA BANJARBARU." Jurnal Rakat Sehat : Pengabdian Kepada Masyarakat 1, no. 1 (April 22, 2022): 14–19. http://dx.doi.org/10.31964/jrs.v1i1.5.

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Drug abuse in students are increase. Banjarbaru City shows 305 case drug abuse in 65% students in the range 10-19 years old covers third highest district are Cempaka district, Landasan Ulin district and Banjarbaru district. Objective : supportive knowledge early teenage traits of drug abuser, how to prevent drug abuse by reinforcement of assertive behavior and self concept. Method : screening drug abuse randomly to 100 students, leaflet distribution, practical simulation and health education to 55 participants of community school. Result : urine test to 95 students show negative, health promotion by DILAN drug abuse shows difference between pre and post test. Training introduction of DILAN drug abuse will help community school to care with drug abuse. Getting early to know potential deviation will be easy to early detection and prevention by teacher and family in school level. Recommendation : the need to continuity of program by monitoring aplication and tools by online program. Keyword : early detection, drug abuse, students
5

Coyne, John F., David King, Steven Garin, and Allen Fred Fielding. "Detection of child abuse." British Journal of Oral and Maxillofacial Surgery 35, no. 6 (December 1997): 448. http://dx.doi.org/10.1016/s0266-4356(97)90755-5.

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Rohringer, Taryn J., Tony E. Rosen, Mihan R. Lee, Pallavi Sagar, and Kieran J. Murphy. "Can diagnostic imaging help improve elder abuse detection?" British Journal of Radiology 93, no. 1110 (June 2020): 20190632. http://dx.doi.org/10.1259/bjr.20190632.

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Elder abuse is an underdetected, under-reported issue with severe consequences. Its detection presents unique challenges based on characteristics of this vulnerable population, including cognitive impairment, age-related deconditioning, and an increased number of co-morbidities, all of which predispose to increase vulnerability to injury. While radiologists play a critical role in detection of child abuse, this role is currently not paralleled in detection of elder abuse. We conducted a thorough review of the literature using MEDLINE to describe the current knowledge on injury patterns and injury findings seen in elder abuse, as well as barriers to and recommendations for an increased role of diagnostic imaging in elder abuse detection. Barriers limiting the role of radiologists include lack of training and paucity of rigorous systematic research delineating distinctive imaging findings for physical elder abuse. We outline the current ways in which imaging can help raise clinical suspicion for elder abuse, including inconsistencies between purported mechanism of injury and imaging findings, injury location, multiple injuries at differing stages of healing, and particular patterns of injury likely to be intentionally inflicted. We additionally outline the mechanism by which medical education and clinical workflow may be modified to increase the role for imaging and radiologist participation in detecting abuse in older adult patients, and identify potential future directions for further systematic research.
7

Bahrami, Pouneh Nikkhah, Umar Iqbal, and Zubair Shafiq. "FP-Radar: Longitudinal Measurement and Early Detection of Browser Fingerprinting." Proceedings on Privacy Enhancing Technologies 2022, no. 2 (March 3, 2022): 557–77. http://dx.doi.org/10.2478/popets-2022-0056.

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Abstract Browser fingerprinting is a stateless tracking technique that aims to combine information exposed by multiple different web APIs to create a unique identifier for tracking users across the web. Over the last decade, trackers have abused several existing and newly proposed web APIs to further enhance the browser fingerprint. Existing approaches are limited to detecting a specific fingerprinting technique(s) at a particular point in time. Thus, they are unable to systematically detect novel fingerprinting techniques that abuse different web APIs. In this paper, we propose FP-Radar, a machine learning approach that leverages longitudinal measurements of web API usage on top-100K websites over the last decade for early detection of new and evolving browser fingerprinting techniques. The results show that FP-Radar is able to early detect the abuse of newly introduced properties of already known (e.g., WebGL, Sensor) and as well as previously unknown (e.g., Gamepad, Clipboard) APIs for browser fingerprinting. To the best of our knowledge, FP-Radar is the first to detect the abuse of the Visibility API for ephemeral fingerprinting in the wild.
8

Xu, Shujuan, Biao Ma, Jiali Li, Wei Su, Tianran Xu, and Mingzhou Zhang. "Europium Nanoparticles-Based Fluorescence Immunochromatographic Detection of Three Abused Drugs in Hair." Toxics 11, no. 5 (April 29, 2023): 417. http://dx.doi.org/10.3390/toxics11050417.

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Drug abuse is becoming increasingly dangerous nowadays. Morphine (MOP), methamphetamine (MET) and ketamine (KET) are the most commonly abused drugs. The abuse of these drugs without supervision can cause serious harm to the human body and also endanger public safety. Developing a rapid and accurate method to screen drug suspects and thus control these drugs is essential to public safety. This paper presents a method for the simultaneous quantitative detection of these three drugs in hair by a europium nanoparticles-based fluorescence immunochromatographic assay (EuNPs−FIA). In our study, the test area of the nitrocellulose membrane was composed of three equally spaced detection lines and a quality control line. The test strip realized the quantitative analysis of the samples by detecting the fluorescence brightness of the europium nanoparticles captured on the test line within 15 min. For the triple test strip, the limits of detection of MOP, KET and MET were 0.219, 0.079 and 0.329 ng/mL, respectively. At the same time, it also showed strong specificity. The strip was stable and could be stored at room temperature for up to one year, and the average recovery rate was 85.98–115.92%. In addition, the EuNPs−FIA was validated by high-performance liquid chromatography (HPLC) analysis, and a satisfactory consistency was obtained. Compared to the current immunochromatographic methods used for detecting abused drugs in hair, this method not only increased the number of detection targets, but also ensured sensitivity, improving detection efficiency to a certain extent. The approach can also be used as an alternative to chromatography. It provides a rapid and accurate screening method for the detection of abused drugs in hair and has great application prospects in regard to public safety.
9

Brown, Sarah D., Greg Brack, and Frances Y. Mullis. "Traumatic Symptoms in Sexually Abused Children: Implications for School Counselors." Professional School Counseling 11, no. 6 (August 2008): 2156759X0801100. http://dx.doi.org/10.1177/2156759x0801100603.

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School counselors have a duty to formulate strategies that aid in the detection and prevention of child sexual abuse (American School Counselor Association, 2003). School counselors are charged with helping sexually abused children by recognizing sexual abuse indicators based on a child's symptomotology and/or behavior, and understanding how this trauma may affect children in the school setting. Mandated reporting issues, talking with children and adolescents about sexual abuse suspicions, and understanding trauma symptoms and their contribution to the difficulties that sexually abused children have in school are highlighted. In addition, how school counselors can collaborate with clinicians treating sexually abused children through role-appropriate advocacy, intervention, and aftercare strategies is described.
10

S, Srividya M., Anala M. R, and Chetan Tayal. "Deep learning techniques for physical abuse detection." IAES International Journal of Artificial Intelligence (IJ-AI) 10, no. 4 (December 1, 2021): 971. http://dx.doi.org/10.11591/ijai.v10.i4.pp971-981.

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<span>Physical abuse has become a societal problem. Mostly children, women and old age people are vulnerable to it especially in cases of domestic violence or workplace aggression. Reporting it is in itself a challenge especially if there is a pre-existing relationship between the abuser and victim. In this paper we propose a deep learning technique for human action recognition and human pose identification to tackle physical abuse by detecting it in real time. 3D convolution neural network (CNN) architecture is built using 3D convolution feature extractors which extract both temporal and spatial data in the video. With multiple convolution layer and subsampling layer, the input video has been converted into feature vector. Human pose estimation is done using the detection of key points on the body. Using these points and tracking them from one frame to another gives spatial-temporal features to feed into neural network (NN). We present metrics to measure the accuracies of such systems where real time reporting and fault tolerance capabilities are of utmost importance. Weighted metrics shows accuracy of about 89.42% with precision of about 85.82% and thus shows the effectiveness of the system.</span>
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Journal articles Dissertations / Theses Books

Dissertations / Theses on the topic "Abuse detection":

1

Abbott, R. W. "HPLC of drugs of abuse with chemiluminescence detection." Thesis, University of Hull, 1987. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.384671.

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Lamping, Sarah Louise. "Study of SERS for the detection of drugs of abuse." Thesis, University of Strathclyde, 2008. http://oleg.lib.strath.ac.uk:80/R/?func=dbin-jump-full&object_id=21989.

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A study of the use of Surface Enhanced Raman Spectroscopy (SERS) for the detection of illicit drugs in oral fluid using metal enhancement mechanisms was undertaken. Initial work investigated ecstasy tablet composition using Raman to identify what drugs and excipients might be present in oral fluid samples obtained from users. Overall, it is possible to identify the presence of phenethylamines and excipients in the seized tablets but not categorically distinguish between the phenethylamine derivative(s) especially when in a mixture. Comparison of the overall batch average peak positions and peak responses of the phenethylamine derivatives and excipients shows variability across the batches and reveals trends within the sub-batches. The Raman spectra appear to reflect the findings of the GUMS analysis tentatively, implying this technique could be used for initial intelligence gathering applications whilst confirmatory analysis results are awaited. Initial SERS research focused on achieving enhancement of aqueous drug solutions with silver and gold colloid. Overall a lack of reproducibility was observed. Therefore, alternative SERS enhancement mechanisms were sought. Ag/Ti0₂ substrates demonstrated low limits of detection and the possibility of detecting SERS enhancement of aqueous amphetamine solution at levels below 8x10⁻² M. The work also showed that cotton swabs for sample application onto the surface of the substrate are a viable practical option for both experimental and field analysis. Successful detection of methadone and buprenorphine, used to treat heroin addiction, was achieved with Ag/Ti0₂ substrates at concentrations associated with therapeutic use, representing lower concentration drugs. The detection of MDMA in oral fluid following ecstasy use, not only showed promise for the detection of illicit drugs, but did so at the analytical cut-off concentration detailed in the draft type approval specification for roadside drug screening devices. This work confirms that SERS has a role for drug detection in oral fluid samples.
3

Faulds, Karen Jade. "Detection of drugs of abuse by surface enhanced Raman scattering (SERS)." Thesis, University of Strathclyde, 2004. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.288636.

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Badiru, Shewu Oladapo. "Chromatographic studies on the detection of some basic drugs of abuse." Thesis, University of Bath, 1989. https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.234086.

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Mansell, Sheila L. "Sexual abuse detection, sequelae, and therapy accommodations for people with developmental disabilities." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 1997. http://www.collectionscanada.ca/obj/s4/f2/dsk3/ftp04/nq23027.pdf.

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Wang, Ling. "Applications of Paper Microfluidic Systems in the Field Detection of Drugs of Abuse." FIU Digital Commons, 2017. http://digitalcommons.fiu.edu/etd/3381.

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Over the years, colorimetric reagents and immunology have been widely used in screening tests for illicit drugs; however, the test kits are not always convenient for field use and often require the user to mix and develop a specific set of reagents. In our project, we have been working on alternative platforms based on paper microfluidic devices (uPADs) for field testing. These devices utilize wax channels printed on paper to direct the analyte towards a specific set of chemical reagents. Using the procedure, we have developed a six-channel chip that adapts known colorimetric reagents targeting cocaine, opiates, amphetamines and ketamine for multiplex detection. For more sensitive and specific determinations than the colorimetric reagents, we have also developed a paper device that utilizes the interaction between gold nanoparticles and drug specific aptamers. The µPADs using colorimetric reagent are designed as a six-channel multiplexed system. Sequences of different reagents applied to each channel to produce a series of reactions and the color changes appear at the end of each channel. The entire process takes less than five minutes. The adjusted reagents produce specific color changes for seized drugs on the paper microfluidic devices. Procedures have been developed for the detection of cocaine, ketamine, codeine, ephedrine, morphine, amphetamine, methamphetamine, and MDMA. These devices have been tested for sensitivity, specificity and stability against a variety of potential interferences and test conditions. Gold nanoparticles (AuNPs)/ aptamers µPADs were developed to detect cocaine. The presence of cocaine cause the binding with aptamers, and the gold nanoparitcles produced a salt-indicated aggregations and gave a color change of AuNPs from red to black. The absence of cocaine allowed the aptamers freely to bind gold nanoparticles, and no color change occured. The device had a preliminary validation of sensitvity and specificity against a variety of potential interferences. The use of paper microfluidic devices permits the development of rapid, inexpensive and easily operated tests for drug samples in the field. They present a safe and convenient presumptive tool that can be used in the field.
7

Cécillon, Noé. "Combining Graph and Text to Model Conversations : An Application to Online Abuse Detection." Electronic Thesis or Diss., Avignon, 2024. http://www.theses.fr/2024AVIG0100.

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Les comportements abusifs en ligne peuvent avoir des conséquences dramatiques sur les utilisateurs et les communautés. Avec l'avènement d'internet et des réseaux sociaux, personne n'est à l'abri de ce genre de comportement. Ces dernières années, de nombreux pays ont mis en place des lois visant à réduire ce type d'abus. Une détection et un traitement rapide des cas abusifs est un facteur important afin de réduire leur impact et leur nombre. Cette tâche de modération impliquant d'importants coûts humains et financiers, les entreprises ont un gros intérêt à l'automatiser. La détection automatique de contenu abusif se révèle assez complexe. Pour contrer ce problème, il a été montré que prendre en compte le contexte dans lequel un message est posté permet d'améliorer la détection. Cependant la méthode la plus courante dans la littérature consiste à traiter des messages individuels, pris en dehors de leur contexte. Dans ce manuscrit, on s'intéresse plus particulièrement à la combinaison du contenu et de la structure pour la détection de contenu abusif. Utiliser le contenu textuel des messages est l'approche la plus courante dans la littérature. Cette méthode présente l'avantage d'être facile à mettre en place, mais elle est aussi très vulnérable aux attaques basées sur le texte, notamment aux techniques d'obfuscation. La structure de la conversation, représentant le contexte, est beaucoup moins étudiée car elle est plus complexe à manipuler. Pourtant, elle permet d'introduire une notion de contexte qui permet de détecter des cas abusifs là où le texte seul n'en est pas capable. Ce contexte peut être modélisé sous la forme d'un graphe conversationnel représentant la conversation contenant le message étudié. En comparant deux méthodes construites à partir d'un procédé d'extraction de caractéristiques (feature engineering), nous avons montré qu'une méthode n'utilisant que des graphes conversationnels et ignorant le contenu textuel des messages était capable d'obtenir de meilleures performances. Des auteurs dans la littérature suggèrent que combiner plusieurs modalités d'information permet d'améliorer la détection de messages abusifs. À cet effet, nous proposons plusieurs stratégies pour combiner le contenu et la structure des conversations et par nos expériences, nous prouvons que cela est en effet bénéfique pour la détection. Une limitation de ces méthodes basées sur un ensemble de mesures est qu'elles sont assez coûteuses tant en ressources informatiques qu'en temps de conception. Les méthodes d'apprentissage de représentations peuvent être une solution à ce problème, en permettant d'apprendre automatiquement la représentation de ces données. Pour les graphes, nous avons démontré que considérer les attributs des liens, à savoir la direction, le poids et le signe, permet d'améliorer les performances. La littérature ne proposant aucune méthode de plongement de graphe entier signé, nous comblons ce vide en développant deux méthodes de ce type. Nous les évaluons sur un benchmark nouvellement créé et constitué de trois jeux de données de graphes signés, et prouvons qu'ils obtiennent de meilleurs résultats que leurs équivalents ne prenant pas en compte les signes. Finalement, nous menons une étude comparative de plusieurs méthodes de plongement lexical et de graphes pour la détection de messages abusifs en les appliquant à un jeu de données de conversations. Nos résultats montrent qu'elles sont plus efficaces que les méthodes se basant sur un ensemble de mesures pour le texte, et légèrement moins efficaces pour les graphes. Cependant, ces résultats restent très encourageants car ces méthodes possèdent de nombreux autres avantages tels qu'être complètement indépendantes de la tâche, plus faciles à adapter à d'autres environnements d'utilisation, et beaucoup plus efficaces en termes de temps
Online abusive behaviors can have devastating consequences on individuals and communities. With the global expansion of internet and the social networks, anyone can be confronted with these behaviors. Over the past few years, laws and regulations have been established to regulate this kind of abuse but the responsibility ultimately lies with the platforms that host online communications. They are asked to monitor their users in order to prevent the proliferation of abusive content. Timely detection and moderation is a key factor to reduce the quantity and impact of abusive behaviors. However, due to the sheer quantity of online messages posted every day, platforms struggle to provide adequate resources. Since this implies high human and financial costs, companies have a keen interest in automating this process. Although it may seem a relatively simple task, it turns out to be quite complex. Indeed, malicious users have developed numerous techniques to bypass the standard automated methods. Allusions or implied meaning are other examples of strategies that automatic methods struggle to detect. While usually performed on individual messages taken out of their context, it has been shown that automatic abuse detection can benefit from considering the context in which the message was posted. In this thesis, we want to focus on the combination of content and structure of conversations to tackle the abuse detection task. Using the textual content of messages is the standard approach which was first developed in the literature. It has the advantage of being easy to set up, but on the other hand, it is vulnerable to text-based attacks such as obfuscation. The structure of the conversation which represent the context is less frequently used as it is more complicated to manipulate. Yet it allows to introduce a contextual aspect which helps detecting abuse occurrences when the text on its own is not sufficient. This context can be modeled as a contextual graph representing the conversation which includes the message. By comparing two methods based on feature engineering on a dataset of conversations extracted from a video games, we could show that a method relying exclusively on conversational graphs and ignoring the content was able to obtain better detection performance. The literature suggest that combining multiple modalities often result in a better detection of abusive messages. We propose multiple strategies to combine the content and structure of conversations and prove that their combination is indeed beneficial to the detection. A limitation of feature-based methods is that they are costly in time and computational resources. Our study also highlights that only a fraction of the computed features are truly relevant for the task. Representation learning methods can be used to mitigate these issues by automatically learning the representations of text and conversational graphs. For graphs, we demonstrated that using edge weights, signs and directions improved the performance. As no method exists for signed whole-graph embedding, we fill this gap in the literature by developing two such methods. We assess them on a newly constituted benchmark of three datasets of signed graphs and show that they perform better than their unsigned counterparts. Lastly, we perform a comparative study of several lexical and graph-embedding method for abuse detection by applying them to our dataset of conversations. Our results show that they perform better than feature-based approaches on text and are slightly less effective on graphs. Still, they obtain promising results given that they are completely task independent, much more scalable and time-efficient than feature-based approaches
8

Yang, Li. "A comparison of unsupervised learning techniques for detection of medical abuse in automobile claims." California State University, Long Beach, 2013.

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Mwenesongole, Ellen Musili. "Simultaneous detection of drugs of abuse in waste water using gas chromatography-mass spectrometry." Thesis, Anglia Ruskin University, 2015. http://arro.anglia.ac.uk/550378/.

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Sewage epidemiology is increasingly becoming an alternative method of estimating drug usage and consumption patterns for a given population. With the constant emergence of new psychoactive substances such as cathinones and piperazines, versatile, reliable, specific and sensitive analytical methods are needed for their detection in complex matrices such as waste water. This thesis reports the development of an analytical method based on solid phase extraction, derivatization with pentafluoropropionic anhydride and analysis by gas chromatography-mass spectrometry for the simultaneous analysis of 29 illicit and therapeutic drugs of abuse. All 29 drugs could be reliably identified in spiked waste water samples using selected ion monitoring and splitless injection. Recoveries for the majority of the drugs were above 70 %. Linearity varied based on the analyte but was assessed in the range 2.0 x 10-4 to 1.4 μg/mL. Intra-assay and intermediate precision of the instrument was determined at 0.005, 0.1 and 1.0 μg/mL, with the majority of relative standard deviations less than 10 %. Limits of detection and quantification for drugs such as amphetamine and methamphetamine were better than reported values for liquid chromatography-tandem mass spectrometry, a more commonly used technique. Untreated 72 h composite waste water samples from Cambridge, UK, were analysed using a six-point standard addition curve. Eleven drugs of abuse were detected, including amphetamine, methamphetamine, butylone and 4-fluoromethamphetamine. The latter two having been detected for the very first time in waste water. Using the validated method, the consumption of heroin, ketamine, cocaine, methamphetamine and amphetamine, in Cambridge, UK, was estimated to be 399.4 ± 90.8, 2463.5 ± 182.5, 195.5 ± 95.4, 84.3 ± 59.1 and 38.9 ± 24.8 mg/day per 1000 inhabitants. This is the first reported validated method for the detection of both classic drugs of abuse and new psychoactive substances in waste water using gas chromatography-mass spectrometry and derivatization with pentafluoropropionic anhydride.
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Low, Ann Stewart. "An evaluation of analytical procedures for detection of drug abuse with particular reference to opiates." Thesis, Robert Gordon University, 1998. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.242985.

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Books on the topic "Abuse detection":

1

Mwiti, Gladys. Child abuse: Detection, prevention, and counselling. Nairobi, Kenya: Evangel Pub. House, 2006.

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Medical Express. Professional Development Center., ed. The prevention and detection of elder abuse. San Diego, CA (12235 El Camino Real, Suite 200, San Diego 92130): MedicalExpress Professional Development Center, 2000.

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Medical Express. Professional Development Center., ed. The prevention and detection of elder abuse. San Diego, CA (12235 El Camino Real, Suite 200, San Diego 92130): MedicalExpress Professional Development Center, 2000.

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Medical Express. Professional Development Center., ed. The prevention and detection of elder abuse. San Diego, CA (12235 El Camino Real, Suite 200, San Diego 92130): MedicalExpress Professional Development Center, 2000.

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Bonnie, Brandl, ed. Elder abuse detection and intervention: A collaborative approach. New York: Springer, 2007.

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Dubois, William Edward Lee. Occult crime: Detection, investigation, and verification. Las Vegas, N.M: San Miguel Press, 1992.

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Miller, Gary J. Drugs and the law: Detection, recognition & investigation. [Altamonte Springs, FL]: Gould Publications, 1992.

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Miller, Gary J. Drugs and the law: Detection, recognition & investigation. Charlottesville, VA: LexisNexis, 2014.

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Reno Conference on the Integration of Behavioral Health in Primary Care: Beyond Efficacy to Effectiveness. Early detection and treatment of substance abuse within integrated primary care. Reno, NV: Context Press, 2006.

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A, Burtonwood C., and Great Britain. Medicines and Healthcare products Regulatory Agency., eds. Sixteen devices for the detection of drugs of abuse in urine. London: MRHA, 2003.

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Book chapters on the topic "Abuse detection":

1

Kumar, Ayush, Aryan Nigam, Aradhana Tripathi, Aftab Khan, Nigam Kumar Mishra, and Rochak Bajpai. "Real-time-abuse detection model." In Advances in AI for Biomedical Instrumentation, Electronics and Computing, 595–99. London: CRC Press, 2024. http://dx.doi.org/10.1201/9781032644752-108.

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Kong, Chao, Jianye Liu, Hao Li, Ying Liu, Haibei Zhu, and Tao Liu. "Drug Abuse Detection via Broad Learning." In Web Information Systems and Applications, 499–505. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-30952-7_49.

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Chen, Yizheng, Panagiotis Kintis, Manos Antonakakis, Yacin Nadji, David Dagon, Wenke Lee, and Michael Farrell. "Financial Lower Bounds of Online Advertising Abuse." In Detection of Intrusions and Malware, and Vulnerability Assessment, 231–54. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-40667-1_12.

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Rao, Udai Pratap, and Nikhil Kumar Singh. "Detection of Privilege Abuse in RBAC Administered Database." In Studies in Computational Intelligence, 57–76. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-14654-6_4.

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Schänzer, Wilhelm. "Abuse of androgens and detection of illegal use." In Testosterone, 545–65. Berlin, Heidelberg: Springer Berlin Heidelberg, 1998. http://dx.doi.org/10.1007/978-3-642-72185-4_20.

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Papegnies, Etienne, Vincent Labatut, Richard Dufour, and Georges Linarès. "Graph-Based Features for Automatic Online Abuse Detection." In Statistical Language and Speech Processing, 70–81. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-68456-7_6.

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Nelson, Anne E., and Ken K. Y. Ho. "Detection of Growth Hormone Doping in Sport Using Growth Hormone-Responsive Markers." In Hormone Use and Abuse by Athletes, 139–50. Boston, MA: Springer US, 2010. http://dx.doi.org/10.1007/978-1-4419-7014-5_15.

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Belkowski, Stanley M., Jinmin Zhu, Lee Y. Liu-Chen, Toby K. Eisenstein, Martin W. Adler, and Thomas J. Rogers. "Detection of К-Opioid Receptor mRNA in Immature T Cells." In The Brain Immune Axis and Substance Abuse, 11–16. Boston, MA: Springer US, 1995. http://dx.doi.org/10.1007/978-1-4615-1951-5_2.

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Papegnies, Etienne, Vincent Labatut, Richard Dufour, and Georges Linarès. "Impact of Content Features for Automatic Online Abuse Detection." In Computational Linguistics and Intelligent Text Processing, 404–19. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-77116-8_30.

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García-Recuero, Álvaro, Jeffrey Burdges, and Christian Grothoff. "Privacy-Preserving Abuse Detection in Future Decentralised Online Social Networks." In Data Privacy Management and Security Assurance, 78–93. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-47072-6_6.

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Conference papers on the topic "Abuse detection":

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Sharon, Rini, Heet Shah, Debdoot Mukherjee, and Vikram Gupta. "Multilingual and Multimodal Abuse Detection." In Interspeech 2022. ISCA: ISCA, 2022. http://dx.doi.org/10.21437/interspeech.2022-10629.

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Wang, Andrew Z., Rex Ying, Pan Li, Nikhil Rao, Karthik Subbian, and Jure Leskovec. "Bipartite Dynamic Representations for Abuse Detection." In KDD '21: The 27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining. New York, NY, USA: ACM, 2021. http://dx.doi.org/10.1145/3447548.3467141.

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Fa, Zhou, Guang-Gang Geng, Zhi-Wei Yan, and Xiao-Dong Lee. "A robust internet abuse detection method." In 2017 IEEE International Conference on Big Data (Big Data). IEEE, 2017. http://dx.doi.org/10.1109/bigdata.2017.8258113.

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Whiton, Adam, and Yolita Nugent. "A Wearable for Physical Abuse Detection." In 2007 11th IEEE International Symposium on Wearable Computers. IEEE, 2007. http://dx.doi.org/10.1109/iswc.2007.4373796.

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Gupta, Vikram, Rini Sharon, Ramit Sawhney, and Debdoot Mukherjee. "ADIMA: Abuse Detection In Multilingual Audio." In ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). IEEE, 2022. http://dx.doi.org/10.1109/icassp43922.2022.9746718.

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Medvedeva, Marina. "AUTOMATIC DETECTION OF ABUSE ON SOCIAL MEDIA." In 16th International Multidisciplinary Scientific GeoConference SGEM2016. Stef92 Technology, 2016. http://dx.doi.org/10.5593/sgem2016/b21/s07.013.

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Thakran, Yash, and Vinayak Abrol. "Investigating Acoustic Cues for Multilingual Abuse Detection." In INTERSPEECH 2023. ISCA: ISCA, 2023. http://dx.doi.org/10.21437/interspeech.2023-1311.

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Palanikumar, Vasanth, Sean Benhur, Adeep Hande, and Bharathi Raja Chakravarthi. "DE-ABUSE@TamilNLP-ACL 2022: Transliteration as Data Augmentation for Abuse Detection in Tamil." In Proceedings of the Second Workshop on Speech and Language Technologies for Dravidian Languages. Stroudsburg, PA, USA: Association for Computational Linguistics, 2022. http://dx.doi.org/10.18653/v1/2022.dravidianlangtech-1.5.

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Malte, Aditya, and Pratik Ratadiya. "Multilingual Cyber Abuse Detection using Advanced Transformer Architecture." In TENCON 2019 - 2019 IEEE Region 10 Conference (TENCON). IEEE, 2019. http://dx.doi.org/10.1109/tencon.2019.8929493.

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Founta, Antigoni Maria, Despoina Chatzakou, Nicolas Kourtellis, Jeremy Blackburn, Athena Vakali, and Ilias Leontiadis. "A Unified Deep Learning Architecture for Abuse Detection." In the 10th ACM Conference. New York, New York, USA: ACM Press, 2019. http://dx.doi.org/10.1145/3292522.3326028.

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Reports on the topic "Abuse detection":

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Peter W. Carr, K.M. Fuller, D.R. Stoll, L.D. Steinkraus, M.S. Pasha, and Glenn G. Hardin. Fast Gradient Elution Reversed-Phase HPLC with Diode-Array Detection as a High Throughput Screening Method for Drugs of Abuse. Office of Scientific and Technical Information (OSTI), December 2005. http://dx.doi.org/10.2172/892807.

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Becker, David, Daniel Kessler, and Mark McClellan. Detecting Medicare Abuse. Cambridge, MA: National Bureau of Economic Research, August 2004. http://dx.doi.org/10.3386/w10677.

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Botulinum Neurotoxin-Producing Clostridia, Working Group on. Report on Botulinum Neurotoxin-Producing Clostridia. Food Standards Agency, August 2023. http://dx.doi.org/10.46756/sci.fsa.ozk974.

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Abstract:
In 1992 a working group of the UK Advisory Committee on the Microbiological Safety of Food presented a report on Vacuum Packaging and Associated Processes regarding the microbiological safety of chilled foods. The report supported subsequent guidance provided by the UK Food Standards Agency for the safe manufacture of vacuum packed and modified atmosphere packed chilled foods. In 2021 the ACMSF requested that a new subgroup should update and build on the 1992 report as well as considering, in addition to chilled foods, some foods that are intended to be stored at ambient temperatures. The new subgroup agreed a scope that includes the conditions that support growth and/or neurotoxin formation by C. botulinum, and other clostridia, as well as identification of limiting conditions that provide control. Other foodborne pathogens that need to be considered separately and some foods including raw beef, pork and lamb were explicitly excluded. The subgroup considered the taxonomy, detection, epidemiology, occurrence, growth, survival and risks associated with C. botulinum and other neurotoxin-forming clostridia. There has been no significant change in the nature of foodborne botulism in recent decades except for the identification of rare cases caused by neurotoxigenic C. butyricum, C. baratii and C. sporogenes. Currently evidence indicates that non-clostridia do not pose a risk in relation to foodborne botulism. The subgroup has compiled lists of incidents and outbreaks of botulism, reported in the UK and worldwide, and have reviewed published information concerning growth parameters and control factors in relation to proteolytic C. botulinum, non-proteolytic C. botulinum and the other neurotoxigenic clostridia. The subgroup concluded that the frequency of occurrence of foodborne botulism is very low (very rare but cannot be excluded) with high severity (severe illness: causing life threatening or substantial sequelae or long-term illness). Uncertainty associated with the assessment of the frequency of occurrence, and with the assessment of severity, of foodborne botulism is low (solid and complete data; strong evidence in multiple sources). The vast majority of reported botulism outbreaks, for chilled or ambient stored foods, are identified with proteolytic C. botulinum and temperature abuse is the single most common cause. In the last 30 years, in the UK and worldwide where a cause can be identified, there is evidence that known controls, combined with the correct storage, would have prevented the reported incidents of foodborne botulism. The subgroup recommends that foods should continue to be formulated to control C. botulinum, and other botulinum neurotoxin-producing clostridia, in accordance with the known factors. With regard to these controls, the subgroup recommends some changes to the FSA guidelines that reflect improved information about using combinations of controls, the z-value used to establish equivalent thermal processes and the variable efficacy associated with some controls such as herbs and spices. Current information does not facilitate revision of the current reference process, heating at 90°C for 10 minutes, but there is strong evidence that this provides a lethality that exceeds the target 6 order of magnitude reduction in population size that is widely attributed to the process and the subgroup includes a recommendation that the FSA considers this issue. Early detection and connection of cases and rapid, effective coordinated responses to very rare incidents are identified as crucial elements for reducing risks from foodborne botulism. The subgroup recommends that the FSA works closely with other agencies to establish clear and validated preparedness in relation to potential major incidents of foodborne botulism in the UK.
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Steinman, Dave, Mike Celiceo, and Joe Head. Stopping Insider Abuse and Spying. Detecting the Hard Stuff: Stolen Passwords Unauthorized Records Browsing, Employee Espionage, Infiltration, and Insertion of Unwelcome Code, via Automatic Behavior Profiling. Fort Belvoir, VA: Defense Technical Information Center, June 1999. http://dx.doi.org/10.21236/ada385478.

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