Abstract

“Not only must the self-made victim be exposed, but innocent people who may be suspected must be protected.” (Gross, 1924). False allegations are always a sensitive and often a political charged subject when it comes to sex crimes investigation. False reports are a very serious concern to the sex crimes detective as well as the legitimate victim of a sex crime. Often, manpower will be diverted from the plight of actual victims to a case that is really a false report allegation. Legitimate victims are hurt by this diversion of manpower. The sex crimes detective must make every effort to bring these false report cases to a quick close. The difficulty in investigating a false report is not always the realization that a case is false but in eliciting a confession from the alleged victim. There has been a continuing argument over how many false reports there really are and over just what constitutes a false report. In this presentation we look at and decipher the literature on false allegations; motivations for false allegation; identifying false reports; lies; victim history; the victim interview; and the author’s personal and anecdotal experience and case reviews while serving with the New York City Police Department’s Manhattan Special Victims Squad. Specific case will be discussed and relevant videos are shown to make specific points about re-investigating other detectives false allegation cases. This presentation is very detailed an I will offer interesting case information related to specific false allegations successfully solved with good questioning and examination of physical evidence with some crime scene reconstruction.

Biography

Retired Detective John J. Baeza started his career in law enforcement as a New York State Correction Officer working at the Sing-Sing Correctional Facility. He was then appointed to the New York City Police Department and began his police career on patrol in Harlem’s 32nd Precinct. He was then assigned to the Manhattan North Narcotics Tactical Narcotics Team and the Manhattan North Narcotics Major Case Unit where he performed undercover work for three years. John J. Baeza was promoted to the rank of Detective and was next assigned to the Manhattan Special Victims Squad where he was personally involved and/or reviewed more than 1,000 sex crimes and child abuse cases. Det. Baeza has also been temporarily assigned the Manhattan North Homicide Squad where he investigated sexual homicide cases. Upon retiring from the NYPD, Detective Baeza worked for a county Sheriff’s Office in Florida for three years. Detective Baeza has over 20 years of experience in law enforcement. In 2011, Detective Baeza became the Director of Security for the Ron Paul 2012 Presidential campaign where he was assigned to supervise the security and safety of both the candidate and staff for 15 months. In 2016, Detective Baeza became the Director of Security for the Rand Paul Presidential campaign where he was assigned to supervise the safety and security of both the candidate and staff. Detective Baeza is now a police procedures expert witness at NYPDTRUTH.COM. He consults on numerous homicides, sexual assaults, police shootings, police misconduct cases, false allegations, and other criminal cases. He works with Det. Joseph Guida, NYPD (ret.). The second expert on this case is Det. Joseph Guida, NYPD (ret.). Detective Guida worked his way up from Patrol to Narcotics. He was then assigned as a Detective to the 46th Precinct Domestic Violence Unit. He is an expert witness for NYPDTRUTH.COM. He will be unable to personally attend.

Abstract

The purpose of this presentation is to promote thoughtful consideration for the future of forensic unit leadership and promotability from within the unit. This presentation will describe the significance of planned succession and steps for continuity and minimal interruption in productivity. Training and professional development in each forensic discipline for growth and knowledge-sharing become essential as each unit member takes on roles and responsibilities with longevity in mind. Educating senior staff on the gains and detriment associated with recruiting, hiring, retention, and losses through retirement, resignation, or termination becomes a succession strategy to institute awareness of unit needs, which also clarifies the necessity of fluid policies, networking with neighboring and distant agencies, and recognition of the long-term investment process for proficiency and expertise.

Biography

Dr. Leggie Boone is a Forensic Analyst in Central Florida, a Forensic Psychology educator at Walden University, and an author. Dr. Boone completed her PhD from the Public Policy and Administration program through Walden Universit in 2020. She has worked in forensic science fields since 1993, as an autopsy technician, crime scene investigator, and latent print analyst, as well as an educator in Maryland and Florida. She has also contributed to multiple publications, including Someday My Prints willCome (a forensic foundation to fingerprints with puzzles and activities), So You Want to Be a CSI, a forensic textbook, and the international Manual of Crime Scene Investigation. Her most recent publication, Dear Dream Maker, is currently available as a result of decades of dream journaling, applied as a coping strategy through years of vicarious traumatization. Dr. Boone has also been an invited speaker in many international conferences, including the Global Science Guild, Worldwide Association of Women Forensic Experts, and the Caribbean Association of Forensic Sciences, and she is a Senior Adjunct Faculty member for the Sherlock Institute of Forensic Sciences, India.

Abstract

Instant messages can be – and increasingly often are – analysed as evidence by forensic linguists to examine potential authorship. However, a challenge to these analyses is that little is known about how exactly intra-author consistency is influenced by the type of conversation partner and how consistent authors are over time. Theories such as audience design (Bell, 1984) and communication accommodation (Giles et al., 1991) propose that language is adapted to suit different recipients, thus reducing intra-author consistency. Further, authors such as Nini (2023) have discussed that an individual’s language style is likely to change over time, again decreasing intra-author consistency. The presented research aims to study intra-author consistency with different types of conversation partner and over time, specifically in WhatsApp messaging. For the first analysis, a corpus of 30 Dutch WhatsApp conversations was collected, consisting of a conversation with a family member, a friend and a non-personal relation for ten authors in total. The use of nineteen linguistic features was analysed and compared for the three types of conversation partner. For the second analysis, consistency in the use of these linguistic features was analysed over time, using five conversations with friends that spanned between 22 and 38 months. The findings show that the use of the majority of features is dependent on the type of conversation partner and that accommodation to a conversation partner over time differs per type of linguistic feature. The results highlight the importance of selecting appropriate reference material and features for analysis in forensic linguistic casework.

Biography

Will be updated soon.....

Abstract

Quality assurance is highly necessary in forensic science in order to ensure that the results obtained with a forensic analysis are of “quality” and they have been produced using valid, credible, and standardized protocols and to demonstrate the competency of the forensic experts. The implementation of quality systems is a legal requirement for forensic laboratories in countries across the EU and the USA, to ensure accurate, reliable and precise results. In this talk, there will be discussed the application and relevance in forensics of some quality certification programs (UNI EN ISO 9001, 17020, 17024, 17025). 

Biography

Anna Barbaro has completed her European PhD in Forensic Genetics (PhD) at University of Santiago de Compostela (Spain). She got a Diploma at the School of Specialization in Applied Genetics and a Master Diploma in Psychological and Behavioral Techniques of the Criminal Investigation at the University of Rome La Sapienza (Italy). She has published more than 150 papers, including conference presentation, she is Author of 5 technical Manuals and of some chapters in other books. She serves as President of the Worldwide Association of Women Forensic Experts, she is honor member of some scientific associations, she serves as reviewer for several international scientific journals, and she is Member of the Editorial Committee of some international scientific journals. Invited speaker at various national and international conferences, organizer of courses and conferences about Forensic Sciences, member of the Scientific Committee of several courses and conferences. She has been researcher at the University of Alcalà (Spain) since September 2020 to December 2022. She is actually the Director of Studio Indagini Mediche E Forensi (SIMEF) laboratory in Italy.

Abstract

Artificial Intelligence has facilitated numerous tasks and aided in simplifying data analysis and various human-related problems. However, AI-written content has posed challenges in numerous industries and the drawbacks of AI in the research field have caused many to wonder about the authenticity of research papers and credibility of their writers. Professors and instructors alike are doubting written texts submitted by students in the age of AI-related tools like ChatGPT which easily take over the task of text creation and submission jeopardizing the integrity and value of scientific research. Numerous AI-detection software have emerged to help identify fraudulent text and research like Turnitin, GPTZero, FLINT, among others; yet tools cannot be the sole guiding factor in detecting AIgenerated text. The human element must play an active role in realizing linguistic features that stand out like perplexity in following strict language models and grammar use which is uncommon in humangenerated texts. Humans are more diverse and irregular in their use of sentence structure and vocabulary which give them a more natural flow of ideas with variation in style. Unlike AI which is far more uniform, human-written texts display our abrupt nature in thought processes and generation of ideas. This requires a more critical technique in analyzing texts which will help in distinguishing cues to fake written material, specifically research papers. As the basis of forensic linguistics, such detection techniques will be the first step in marking fraudulent texts, followed by the newly introduced AI tools that detect, to a large degree, AI-generated texts. Tools like FLINT rely on forensic linguistic methodologies that help detect fraudulent texts by creating a digital fingerprint, not only to confirm AI-generated texts, but to confirm if the author actually wrote the material or not. To face such challenges, the human factor an indispensable factor in guaranteeing the authenticity of scientific research along with newly enhanced AI-detection software.

Biography

Dr. Amal Ismail Gomaa Assistant Professor of Applied Linguistics amal.gomaa@ejust.edu.eg Dr. Gomaa joined Egypt-Japan University of Science and Technology in September 2017 and has been Acting Director of E-JUST Language Center since September 2018. She received her PhD degree in Applied Linguistics from the Faculty of Arts, Department of English Language and Literature, Alexandria University. Throughout her career she has been teaching ESP and communication courses at various faculties and as an advocate of interdisciplinary learning, she has focused her MA and PhD on combining various fields of study including linguistics, literature, communication and media. Her interests have now broadened to include a wider field of disciplinary studies encompassing the role of discourse analysis in politics and media representation and the interrelation of linguistic techniques and marketing strategies. As a strong believer in student interaction to facilitate language acquisition, Dr. Gomaa has promoted effective student empowerment in all her courses. She held and participated in numerous communication courses, seminars, and training sessions at the university to help build soft skills and effective writing and communication skills of students. She has also focused on building competencies and employability skills of students in her capacity as academic coordinator of the University’s Career Support Section.

Abstract

Digital forensics is the practice of identifying, acquiring, and analysing electronic evidence. Today almost all criminal activity has a digital forensics element, and digital forensics experts provide critical assistance to police investigations. An important part of digital forensics is the analysis of suspected cyberattacks, with the objective of identifying, mitigating, and eradicating cyber threats. This makes digital forensics a critical part of the incident response process. Electronic evidence can be gathered from a variety of sources, including computers, mobile devices, remote storage devices, internet of things (IoT) devices, and virtually any other computerized system.

Biography

Jay Amar Makwana is a final year BSc Cyber Security and Digital forensics Student at Middlesex University London. He has achieved a First grade in his second year of study and specially gaining First Grade First Class Distinction in Digital Forensics module. He has strongly practiced Digital Incident Scene Investigation as the Lead Case Officer in various University Projects and presentations.

Abstract

RNA is transcribed from genomic DNA in a tissue-specific manner. These RNAs were adapted for body fluid identification during the last decades. Usually, there are thousands of copies of RNA in a cell, and nuclear genomic DNA polymorphism on exons can be reflected in RNA molecules, i.e., the coding SNP (cSNP). Based on these two features, we proposed that the body fluid-specific cSNPs may have the potential for deconvolution of the mixtures with different body fluids. We developed three SNaPshot body fluid-specific cSNPs typing systems for blood, semen, and vaginal secretion donor in the mixture, respectively. All three systems exhibit extraordinary performance for mixture deconvolution, even in six-component mixtures this system can accurately obtain the profile of the target body fluid without influence from other components at a ratio of 1:100 – 1:500 (target body fluid minor). In addition, the cSNPs genotype was consistency with the corresponding DNA genotype. 

The hair shaft is the most common specimen in crime scenes, however, genomic DNA in hair shaft isn’t sufficient for PCR. We proposed RNA-cSNP might be an optimal marker for hair shaft individual identification, which benefit from the feature of high copy number and polymorphism. We developed a SNaPshot assay targeting 18 cSNPs in hair shaft. They showed favorable polymorphic parameters, consistency, sensitivity, species specificity, and feasibility for aged hair shaft samples. The detection limit of the assay was 2 ng RNA. These 18 cSNPs exhibit a CDP of 0.999969 in the Shanxi population and concordance with genomic DNA. 

Biography

Gengqian Zhang, he obtained a doctoral degree from Sichuan University in 2007 and did postdoctoral research at West Virginia University in the United States from 2008 to 2010. Currently, working at the School of Forensic Medicine of Shanxi Medical University as a professor of forensic genetics, Member of the Forensic Medical Credit Committee of the Chinese Genetic Society. He presided over 10 projects as a PI, including the National Natural Science Foundation, the National Key Research and Development Plan sub project, etc. and have published more than 80 articles, including 30 SCI articles, owing 15 invention patent.

Abstract

At the GSFL roundtable in 2019, David Wright discussed the features that mark forensic data -language evidence specifically- and called to expand these attributes to include non-forensic linguistic data as well. His talk is driven by the restrictions that make forensic linguistic data unattainable, which ultimately hinders the progress of exploring various research methods and tools. Accessibility of forensic linguistic data (e.g., suicide letters, death threats, ransom notes, etc.) has and still is a challenge due to its sensitive and confidential nature. Consequently, forensic linguists remedy this by resorting to texts that share similar attributes either in terms of genre or authorship style. The internet and word processors made the provision of such texts easier, and AI accelerated the retrieval and extraction processes (Juola, 2008). Since March 2023, Chat GPT the latest AI tool, is perceived as a technological breakthrough that’s been implemented in a myriad of scientific experiments. A prospective area of interest is digital forensics and cybercrime by helping investigators process substantial amount of data and discover communication nuances produced by suspected criminals (Williams, 2023; Frąckiewicz, 2023). My talk aims to discuss the potential of Chat GPT in generating mock-up forensic data. At a time where instances of abusing this tool in fraud and plagiarism occur; exploring this route, its ethical limitations, and its applicability, is needed. Experimenting with Chat GPT’s ability to produce or mimic forensic linguistic data and formulating a code of good practice can be a form of a response to Wright’s call and ultimately the FL community. 

Biography

Mashael AlAmr has completed her PhD in forensic linguistics from the School of English and School of Computing at University of Leeds, United Kingdom. She is an Assistant Professor at the department of English Language at College of Language Sciences, King Saud University in Saudi Arabia. She is a member of the International Association of Forensic and Legal Linguistics.

Abstract

In decomposed or skeletonized bodies, conventional matrices used in forensic toxicology may no longer be available for analysis. The aim of this paper was to determine if toxicological substances could still be detected in dry bone samples with a post-mortem interval of over 23 years. To achieve this, bone samples from the cranium, ribs, and vertebrae of seven skeletons from the CAL Milano Cemetery Skeletal Collection were selected for this study. These skeletons were buried for over 23 years, fully decomposed, and had undergone changes due to taphonomic factors. The selection of samples was based on the individuals’ ante-mortem (pre-death) information, which included confirmed or suspected drug addictions or overdose. A DionexTM ASETM 350 accelerated Solvent Extractor and Q-Exactive Orbitrap-mass spectrometry with a HPLC system were utilized to conduct qualitative and quantitative analyses. Positive results were obtained in six of the seven cases, revealing the presence of various psychoactive drugs and their metabolites. These included analgesics (methadone and buprenorphine), anxiolytics (delorazepam, diazepam, nordiazepam, and lorazepam), a cannabinoid metabolite (THCCCOOH), as well as stimulant metabolites (benzoylecgonine and MDA). Consequently, this study demonstrates that toxicological substances may be found in bone tissue after a post-mortem interval of over 23 years.

Biography

Dwayne Ahmir King-Thomas is a former pharmaceutical quality control chemist who completed his Bachelor of Science in Chemistry from East Tennessee State University. He is now a chemistry graduate student at the University of Memphis where he is currently working on forensic research relating to the post-mortem interval (PMI) of skeletal remains.

Abstract

There are different statistics that can be used to evaluate the significance of mixtures of DNA. One of these is the Likelihood Ratio (LR). The LR as routinely presented to a court, as well as being misunderstood, is difficult to comprehend and explain, and does not provide any indication of:  how many other people may be considered potential contributors to the profile,  the LR for any or all of those potential contributors, or  the values of the numerator and denominator. Low template mixtures of DNA create specific additional problems in the statistical evaluation. Very low amounts mean that some alleles are not detected in every run, and possibly not at all. When an allele should appear but does not, then the phenomenon is called dropout. That problem of course is only apparent if an interpreter knows what DNA is present in the sample, or if more than one run is performed and the allele is absent in one or more of the runs, or in the extreme if an entire locus has no alleles present in the profile. Dropout is the extreme form of peak height variability. In standard DNA profiling with the recommended amount of DNA (0.5ng – 1.5ng; 500pg – 1500pg) then the peak heights are consistent between runs. When very low amounts of DNA are used the peak heights can vary considerably between runs. Drop-out of an allele in one analysis while it is present in another is the extreme form of peak height variation. Some authors created models that attempt to provide the probability of the evidence by estimating the probability that these alleles were actually there even though not seen (drop-out) or are ‘uncertain’ in the analysis. These calculations had also to take account of the probability that they were indeed spurious alleles and were ‘drop-in’ (i.e. had been introduced into the original sample – a form of contamination). Some models ignore peak height and consider only whether an allele is present regardless of any information that peak height may contribute to the assessment. Models which ignore peak height are termed ‘semicontinuous’ or discrete. Ignoring peak height may be acceptable given the wide variation in peak heights when only low amounts of DNA are present and so the peak height itself is variable. Some models include consideration of peak height within the DNA profiles (which are graphs of the amount of each DNA component within a sample). These models are called ‘continuous’. A further difference among models is how the probability of drop-out or drop-in is calculated. Some use empirical data derived from laboratory experiments while others use estimates or simply insert values that maximise the parameter under each hypothesis. The complex calculations involved in some of these approaches has led to the development of a number of software programmes which claim to calculate the LR for mixtures. Each of these uses a different method to perform the calculation. Some of these models require computer software to calculate. Different programmes have been developed. These use different models and formulae to each other. There is concern that these programmes have not been fully tested (validated). Although proponents of these models and computer programmes which perform the calculations claim to take account of dropin and dropout, others claim that although the models may be sound, the data to support the calculations is not available. Without reliable data, the calculations are themselves unreliable. Computer programmes require extensive validation as there is no ‘true’ answer to which the results can be compared. International case examples from USA, Australia and the UK will be discussed illustrating the problems that occur in court when the LR and probabilistic genotyping systems are used to evaluate evidence, with an emphasis on low template DNA and the LR, the statistic which the probabilistic genotyping systems are intended to calculate.

Biography

Prof Allan Jamieson BSc PhD FRSB Provided written evidence and advice in over 1000 criminal cases in England, Wales, Northern Ireland, Scotland, Republic of Ireland, Gibraltar, USA, New Zealand, Cyprus, and Australia. Including evidence on LTDNA in the Omagh Bomb trial of Sean Hoey, at the inquest into the death of Diana, Princess of Wales, and many trials involving DNA interpretation, probabilistic genotyping, and DNA transfer. Member of the Expert Roster for DNA for the New York State Assigned Counsel Plan Invited and adopted as, ‘a scientist and scholar’ to sign amicus briefs to the California Supreme Court, Wisconsin Supreme Court, and the United States Supreme Court on the use of statistics and DNA in Court. Co-Editor in Chief of Wiley’s Encyclopaedia of Forensic Sciences, and ‘A Guide to Forensic DNA Profiling’ (2016). Vice Chair of the Royal Society of Biology Professional Recognition Panel (which is responsible for award of Chartered Scientist status) Undertaken consultancy projects in Turkey (EU funded), Egypt (Government investigation), and Pakistan (Education). Chronology: Bachelor of Science with First Class (Double) Honours in Biology & Genetics. University of Strathclyde, Glasgow, 1976-1980 Doctor of Philosophy, Forensic Science Unit, University of Strathclyde, Glasgow, 1980-84 Post-Doctoral Research Scientist, Department of Medical Genetics, University of Glasgow, 1983-87 Research Associate, Department of Immunology, University of Edinburgh, 1987-88 Research Fellow in Virology at the Institute of Virology, Glasgow University, 1988-1990 Self-employed, photographer, 1990-92 Business Manager for Laboratory Medicine and Clinical Physics, West Glasgow Universities NHS Hospital Trust, 1992-95 Head of Forensic Science, Lothian and Borders Police, Edinburgh, 1995-2002 Director, The Forensic Institute, Glasgow, 2002-present

Abstract

The screening process to determine those latent fingermarks worthy of being forwarded for comparison following processing, either in the laboratory or at the scene, is an essential task and one that historically has not received much attention. Agencies with a high volume of cases and evidence do not want to bog down their latent print examiners (LPEs) with anymore latent fingermarks than are necessary while at the same time not having a fingermark with utility for comparison fall through the cracks. The screening decision, while not quite a suitability decision, is akin to a presumptive test. Laboratories testing substances for controlled drugs would likely be inundated with cases if every white powder was submitted for testing which is why field (presumptive) tests are necessary. Unfortunately, there is not a presumptive test for latent prints, rather a human must determine what is forwarded to the LPE. With these human presumptive tests, having a higher false positive rate but a low false negative rate is acceptable (high sensitivity, low specificity). This presentation will discuss the research related to latent fingermark screening decisions, describe the goals of the screening decision, define some of the features within friction ridge skin that are useful for comparison, discuss the issues related to the decision of whether to forward or discard a fingermark, and provide strategies of how to recognize those fingermarks with the best chance for success during the comparison stage.

Biography

Nicolas Craven is a Certified Latent Print Examiner with the International Association for Identification. He spent more than seven years working for the Idaho State Police Forensic Services (USA) where he performed latent fingermark processing and comparison. He is currently a contract Latent Print Advisor to Colombia for the US Department of Justice’s ICITAP program. Nicolas is also involved in training in latent fingermark related topics (processing, comparison, and photography) with his company, C2 Quality Solutions. He is currently working on his PhD in forensic science at the University of Lausanne in Switzerland.

Abstract

Digital forensics is a dynamic field that faces significant challenges, including the exponential growth and complexity of digital data, the rapid pace of technological innovation, and the lack of standardisation in forensic practices. To address these challenges, new tools, techniques, and emerging technologies such as artificial intelligence (AI) are essential. AI has the potential to automate many of the tasks involved in digital forensics, freeing up investigators to focus on more complex and strategic work. Additionally, AI can be used to develop new tools and techniques for analysing complex data types and emerging cybercrime threats. The increasing recognition of the importance of digital forensics in law enforcement and cybersecurity is creating new opportunities for the field. This is leading to greater investment in digital forensics capabilities and a growing understanding of the role of digital forensics in protecting organisations and individuals from cybercrime. By embracing new technologies and developing new investigative techniques, the field of digital forensics is well-positioned to meet the demands of the future and play a vital role in protecting society from cybercrime. 

Biography

Serhii Kocherhan has expertise in digital forensics and cybersecurity, with a proven ability to identify and mitigate security risks, implement and test security controls, and investigate cyber incidents. He holds a BSc in Computer Science from Lviv Polytechnic National University, Ukraine, and is proficient in a variety of digital forensics tools and techniques.