GC0146: development of co-ordinated in situ and ex situ UK farm animal genetic resources conservation strategy and implementation guidance

Executive Summary The need for the project arises from the UK Government’s international commitments to the conservation and sustainable utilization of its farm animal genetic resources (FAnGR). This report complements the other elements of the project, which have focused on background policy and specific issues of animal identification and traceability. Its aims are • To review current activities in UK FAnGR breeding and conservation; • To generate a best practice document for stakeholders and policy makers. Breeding plans “The selective breeding of livestock in order to meet commercial requirements” 1. Breeding plans operate within political, economic and scientific-technical contexts and these are reviewed; 2. UK livestock are in the private sector and while decisions are made by individual breeders, who also own the information necessary to assess the genetic consequences, but the UK Government is responsible internationally for the effects of these decisions on FAnGR; 3. Breeding plans that fail to take account of genetic conservation can lead to genetic improvement in the traits under selection being accompanied by the avoidable loss of genetic variation in other traits which may be of value either now or in the future, as has been observed in the breeding of commercial dairy cattle; 4. A practical investigation of native mainstream and at-risk breeds, using new data and methods, has shown how breeding plans and conservation strategies coexist; 5. Methodologies developed for the planning and monitoring of breeding plans can readily be adapted to perform the same functions in conservation strategies. Conservation strategies “The planned mating of livestock in order to retain breed genetic variation” 1. The contexts of FAnGR conservation, and the relevant stakeholders, are reviewed, with the role of breed societies being considered in detail; 2. Conservation strategies must take account of the desire of many owners of at-risk breeds to develop their breeds along commercial lines; 3. New research is reported showing that while genetic variation is, in general, being conserved, there are important areas where particular attention is needed; 4. Ex situ conservation (principally, the storage of frozen semen) is reviewed and found to compare favourably with what is practised elsewhere in Europe, except in the case of poultry; 5. Emergent issues are highlighted, notably the conservation of traditional segments within commercial breeds and of poultry in general; 6. New research is reported on the monitoring of genetic variation by means of demographic variables, for breeds where computational approaches cannot be applied. Best practice guidance Best Practice Guidance is presented and the principles explained. The Guidance, which is for breeders, breed societies and the UK Government, is also available as a separate document

BIOMETRIC TECHNOLOGIES FOR AMBIENT INTELLIGENCE

Il termine Ambient Intelligence (AmI) si riferisce a un ambiente in grado di riconoscere e rispondere alla presenza di diversi individui in modo trasparente, non intrusivo e spesso invisibile. In questo tipo di ambiente, le persone sono circondate da interfacce uomo macchina intuitive e integrate in oggetti di ogni tipo. Gli scopi dell\u2019AmI sono quelli di fornire un supporto ai servizi efficiente e di facile utilizzo per accrescere le potenzialit\ue0 degli individui e migliorare l\u2019interazioni uomo-macchina. Le tecnologie di AmI possono essere impiegate in contesti come uffici (smart offices), case (smart homes), ospedali (smart hospitals) e citt\ue0 (smart cities). Negli scenari di AmI, i sistemi biometrici rappresentano tecnologie abilitanti al fine di progettare servizi personalizzati per individui e gruppi di persone. La biometria \ue8 la scienza che si occupa di stabilire l\u2019identit\ue0 di una persona o di una classe di persone in base agli attributi fisici o comportamentali dell\u2019individuo. Le applicazioni tipiche dei sistemi biometrici includono: controlli di sicurezza, controllo delle frontiere, controllo fisico dell\u2019accesso e autenticazione per dispositivi elettronici. Negli scenari basati su AmI, le tecnologie biometriche devono funzionare in condizioni non controllate e meno vincolate rispetto ai sistemi biometrici comunemente impiegati. Inoltre, in numerosi scenari applicativi, potrebbe essere necessario utilizzare tecniche in grado di funzionare in modo nascosto e non cooperativo. In questo tipo di applicazioni, i campioni biometrici spesso presentano una bassa qualit\ue0 e i metodi di riconoscimento biometrici allo stato dell\u2019arte potrebbero ottenere prestazioni non soddisfacenti. \uc8 possibile distinguere due modi per migliorare l\u2019applicabilit\ue0 e la diffusione delle tecnologie biometriche negli scenari basati su AmI. Il primo modo consiste nel progettare tecnologie biometriche innovative che siano in grado di funzionare in modo robusto con campioni acquisiti in condizioni non ideali e in presenza di rumore. Il secondo modo consiste nel progettare approcci biometrici multimodali innovativi, in grado di sfruttare a proprio vantaggi tutti i sensori posizionati in un ambiente generico, al fine di ottenere un\u2019elevata accuratezza del riconoscimento ed effettuare autenticazioni continue o periodiche in modo non intrusivo. Il primo obiettivo di questa tesi \ue8 la progettazione di sistemi biometrici innovativi e scarsamente vincolati in grado di migliorare, rispetto allo stato dell\u2019arte attuale, la qualit\ue0 delle tecniche di interazione uomo-macchine in diversi scenari applicativi basati su AmI. Il secondo obiettivo riguarda la progettazione di approcci innovativi per migliorare l\u2019applicabilit\ue0 e l\u2019integrazione di tecnologie biometriche eterogenee negli scenari che utilizzano AmI. In particolare, questa tesi considera le tecnologie biometriche basate su impronte digitali, volto, voce e sistemi multimodali. Questa tesi presenta le seguenti ricerche innovative: \u2022 un metodo per il riconoscimento del parlatore tramite la voce in applicazioni che usano AmI; \u2022 un metodo per la stima dell\u2019et\ue0 dell\u2019individuo da campioni acquisiti in condizioni non-ideali nell\u2019ambito di scenari basati su AmI; \u2022 un metodo per accrescere l\u2019accuratezza del riconoscimento biometrico in modo protettivo della privacy e basato sulla normalizzazione degli score biometrici tramite l\u2019analisi di gruppi di campioni simili tra loro; \u2022 un approccio per la fusione biometrica multimodale indipendente dalla tecnologia utilizzata, in grado di combinare tratti biometrici eterogenei in scenari basati su AmI; \u2022 un approccio per l\u2019autenticazione continua multimodale in applicazioni che usano AmI. Le tecnologie biometriche innovative progettate e descritte in questa tesi sono state validate utilizzando diversi dataset biometrici (sia pubblici che acquisiti in laboratorio), i quali simulano le condizioni che si possono verificare in applicazioni di AmI. I risultati ottenuti hanno dimostrato la realizzabilit\ue0 degli approcci studiati e hanno mostrato che i metodi progettati aumentano l\u2019accuratezza, l\u2019applicabilit\ue0 e l\u2019usabilit\ue0 delle tecnologie biometriche rispetto allo stato dell\u2019arte negli scenari basati su AmI.Ambient Intelligence (AmI) refers to an environment capable of recognizing and responding to the presence of different individuals in a seamless, unobtrusive and often invisible way. In this environment, people are surrounded by intelligent intuitive interfaces that are embedded in all kinds of objects. The goals of AmI are to provide greater user-friendliness, more efficient services support, user-empowerment, and support for human interactions. Examples of AmI scenarios are smart cities, smart homes, smart offices, and smart hospitals. In AmI, biometric technologies represent enabling technologies to design personalized services for individuals or groups of people. Biometrics is the science of establishing the identity of an individual or a class of people based on the physical, or behavioral attributes of the person. Common applications include: security checks, border controls, access control to physical places, and authentication to electronic devices. In AmI, biometric technologies should work in uncontrolled and less-constrained conditions with respect to traditional biometric technologies. Furthermore, in many application scenarios, it could be required to adopt covert and non-cooperative technologies. In these non-ideal conditions, the biometric samples frequently present poor quality, and state-of-the-art biometric technologies can obtain unsatisfactory performance. There are two possible ways to improve the applicability and diffusion of biometric technologies in AmI. The first one consists in designing novel biometric technologies robust to samples acquire in noisy and non-ideal conditions. The second one consists in designing novel multimodal biometric approaches that are able to take advantage from all the sensors placed in a generic environment in order to achieve high recognition accuracy and to permit to perform continuous or periodic authentications in an unobtrusive manner. The first goal of this thesis is to design innovative less-constrained biometric systems, which are able to improve the quality of the human-machine interaction in different AmI environments with respect to the state-of-the-art technologies. The second goal is to design novel approaches to improve the applicability and integration of heterogeneous biometric systems in AmI. In particular, the thesis considers technologies based on fingerprint, face, voice, and multimodal biometrics. This thesis presents the following innovative research studies: \u2022 a method for text-independent speaker identification in AmI applications; \u2022 a method for age estimation from non-ideal samples acquired in AmI scenarios; \u2022 a privacy-compliant cohort normalization technique to increase the accuracy of already deployed biometric systems; \u2022 a technology-independent multimodal fusion approach to combine heterogeneous traits in AmI scenarios; \u2022 a multimodal continuous authentication approach for AmI applications. The designed novel biometric technologies have been tested on different biometric datasets (both public and collected in our laboratory) simulating the acquisitions performed in AmI applications. Results proved the feasibility of the studied approaches and shown that the studied methods effectively increased the accuracy, applicability, and usability of biometric technologies in AmI with respect to the state-of-the-art

Biometric Identification, Law and Ethics

This book undertakes a multifaceted and integrated examination of biometric identification, including the current state of the technology, how it is being used, the key ethical issues, and the implications for law and regulation. The five chapters examine the main forms of contemporary biometrics–fingerprint recognition, facial recognition and DNA identification– as well the integration of biometric data with other forms of personal data, analyses key ethical concepts in play, including privacy, individual autonomy, collective responsibility, and joint ownership rights, and proposes a raft of principles to guide the regulation of biometrics in liberal democracies.Biometric identification technology is developing rapidly and being implemented more widely, along with other forms of information technology. As products, services and communication moves online, digital identity and security is becoming more important. Biometric identification facilitates this transition. Citizens now use biometrics to access a smartphone or obtain a passport; law enforcement agencies use biometrics in association with CCTV to identify a terrorist in a crowd, or identify a suspect via their fingerprints or DNA; and companies use biometrics to identify their customers and employees. In some cases the use of biometrics is governed by law, in others the technology has developed and been implemented so quickly that, perhaps because it has been viewed as a valuable security enhancement, laws regulating its use have often not been updated to reflect new applications. However, the technology associated with biometrics raises significant ethical problems, including in relation to individual privacy, ownership of biometric data, dual use and, more generally, as is illustrated by the increasing use of biometrics in authoritarian states such as China, the potential for unregulated biometrics to undermine fundamental principles of liberal democracy. Resolving these ethical problems is a vital step towards more effective regulation.Ethics & Philosophy of Technolog

Biometric ID Cybersurveillance

The implementation of a universal digitalized biometric ID system risks normalizing and integrating mass cybersurveillance into the daily lives of ordinary citizens. ID documents such as driver’s licenses in some states and all U.S. passports are now implanted with radio frequency identification (RFID) technology. In recent proposals, Congress has considered implementing a digitalized biometric identification card—such as a biometric-based, “high-tech” Social Security Card—which may eventually lead to the development of a universal multimodal biometric database (e.g., the collection of the digital photos, fingerprints, iris scans, and/or DNA of all citizens and noncitizens). Such “hightech” IDs, once merged with GPS-RFID tracking technology, would facilitate exponentially a convergence of cybersurveillance-body tracking and data surveillance, or dataveillance-biographical tracking. Yet, the existing Fourth Amendment jurisprudence is tethered to a “reasonable expectation of privacy” test that does not appear to restrain the comprehensive, suspicionless amassing of databases that concern the biometric data, movements, activities, and other personally identifiable information of individuals. In this Article, I initiate a project to explore the constitutional and other legal consequences of big data cybersurveillance generally and mass biometric dataveillance in particular. This Article focuses on how biometric data is increasingly incorporated into identity management systems through bureaucratized cybersurveillance or the normalization of cybersurveillance through the daily course of business and integrated forms of governance

Investigation of Multimodal Template-Free Biometric Techniques and Associated Exception Handling

The Biometric systems are commonly used as a fundamental tool by both government and private sector organizations to allow restricted access to sensitive areas, to identify the criminals by the police and to authenticate the identification of individuals requesting to access to certain personal and confidential services. The applications of these identification tools have created issues of security and privacy relating to personal, commercial and government identities. Over the last decade, reports of increasing insecurity to the personal data of users in the public and commercial domain applications has prompted the development of more robust and sound measures to protect the personal data of users from being stolen and spoofing. The present study aimed to introduce the scheme for integrating direct and indirect biometric key generation schemes with the application of Shamir‘s secret sharing algorithm in order to address the two disadvantages: revocability of the biometric key and the exception handling of biometric modality. This study used two different approaches for key generation using Shamir‘s secret sharing scheme: template based approach for indirect key generation and template-free. The findings of this study demonstrated that the encryption key generated by the proposed system was not required to be stored in the database which prevented the attack on the privacy of the data of the individuals from the hackers. Interestingly, the proposed system was also able to generate multiple encryption keys with varying lengths. Furthermore, the results of this study also offered the flexibility of providing the multiple keys for different applications for each user. The results from this study, consequently, showed the considerable potential and prospect of the proposed scheme to generate encryption keys directly and indirectly from the biometric samples, which could enhance its success in biometric security field

Biometrics Technology: Understanding Dynamics Influencing Adoption for Control of Identification Deception Within Nigeria

One of the objectives of any government is the establishment of an effective solution to significantly control crime. Identity fraud in Nigeria has generated global attention and negative publicity toward its citizens. The research problem addressed in this study was the lack of understanding of the dynamics that influenced the adoption and usability of biometrics technology for reliable identification and authentication to control identity deception. The support for this study was found in the theoretical framework of the technology acceptance model (TAM). The purpose of the study was to provide scholarly research about the factors that influenced the adoption of biometrics technology to reliably identify and verify individuals in Nigeria to control identity fraud. The mixed-method descriptive and inferential study used interview and survey questionnaires for data collection. The binary logistic regression, point bi-serial correlation, independent samples t test, and content analyses were performed using SPSS version 18, Microsoft Excel spreadsheet 2007, and Nvivo 7.0 software. The results from the findings indicated statistical correlation between adopt biometrics technology and three other variables, ease of use (r = .38, n = 120, p \u3c.01), perceived usefulness (ri = .41, n = 120, p \u3c .01), and awareness (ri = .33, ni = 120, p \u3c .01). The implications for social change include leveraging biometrics technology for recognition, confirmation, and accountability of individuals to prevent identity scheming, ensure security, and control the propagation of personal information. Beyond these immediate benefits, this research presents an example that other developing countries may use to facilitate the adoption of biometrics technology

Program and Proceedings: The Nebraska Academy of Sciences 1880-2023. 142th Anniversary Year. One Hundred-Thirty-Third Annual Meeting April 21, 2023. Hybrid Meeting: Nebraska Wesleyan University & Online, Lincoln, Nebraska

AERONAUTICS & SPACE SCIENCE Chairperson(s): Dr. Scott Tarry & Michaela Lucas HUMANS PAST AND PRESENT Chairperson(s): Phil R. Geib & Allegra Ward APPLIED SCIENCE & TECHNOLOGY SECTION Chairperson(s): Mary Ettel BIOLOGY Chairpersons: Lauren Gillespie, Steve Heinisch, and Paul Davis BIOMEDICAL SCIENCES Chairperson(s): Annemarie Shibata, Kimberly Carlson, Joseph Dolence, Alexis Hobbs, James Fletcher, Paul Denton CHEM Section Chairperson(s): Nathanael Fackler EARTH SCIENCES Chairpersons: Irina Filina, Jon Schueth, Ross Dixon, Michael Leite ENVIRONMENTAL SCIENCE Chairperson: Mark Hammer PHYSICS Chairperson(s): Dr. Adam Davis SCIENCE EDUCATION Chairperson: Christine Gustafson 2023 Maiben Lecturer: Jason Bartz 2023 FRIEND OF SCIENCE AWARD TO: Ray Ward and Jim Lewi

Збірник тез доповідей учасників XXIIІ Міжнародної студентської науково-практичної конференції іноземними мовами, присвяченої 30-річчю кафедри іноземних мов

Інноваційні технології на службі правопорядку (зарубіжний досвід) : зб. тез доп. учасників ХХIІІ Міжнар. студент. наук.-практ. конф. інозем. мовами, присвяч. 30-річчю каф. інозем. мов (м. Харків, Україна, 12 квіт. 2021 р.) / МВС України, Харків. нац. ун-т внут. справ, Каф. інозем. мов ф-ту № 4, Наук. парк «Наука та безпека». – Харків : ХНУВС, 2022. – 248 с.Збірник містить аналітичний огляд та узагальнення зарубіжного досвіду використання інноваційних технологій правоохоронними органами. Інформаційною основою проведених досліджень є автентичні джерела англійською, німецькою та французською мовами. Матеріали конференції сприятимуть удосконаленню та підвищенню ефективності діяльності вітчизняних працівників поліції.A selection of analytical reviews of the foreign information about the development of innovative technologies by law enforcement agencies. The informational basis for conducting research is authentic English, German and French languages. The materials of the conference will be accepted to improve and improve the efficiency of the work of the clergy in the police.Сборник содержит аналитический обзор и обобщение зарубежного опыта использования инновационных технологий правоохранительными органами. Информационной основой проведенных исследований являются аутентичные источники на английском, немецком и французском языках. Материалы конференции будут способствовать усовершенствованию и повышению эффективности деятельности отечественных работников полиции

Investigating combinations of feature extraction and classification for improved image-based multimodal biometric systems at the feature level

Multimodal biometrics has become a popular means of overcoming the limitations of unimodal biometric systems. However, the rich information particular to the feature level is of a complex nature and leveraging its potential without overfitting a classifier is not well studied. This research investigates feature-classifier combinations on the fingerprint, face, palmprint, and iris modalities to effectively fuse their feature vectors for a complementary result. The effects of different feature-classifier combinations are thus isolated to identify novel or improved algorithms. A new face segmentation algorithm is shown to increase consistency in nominal and extreme scenarios. Moreover, two novel feature extraction techniques demonstrate better adaptation to dynamic lighting conditions, while reducing feature dimensionality to the benefit of classifiers. A comprehensive set of unimodal experiments are carried out to evaluate both verification and identification performance on a variety of datasets using four classifiers, namely Eigen, Fisher, Local Binary Pattern Histogram and linear Support Vector Machine on various feature extraction methods. The recognition performance of the proposed algorithms are shown to outperform the vast majority of related studies, when using the same dataset under the same test conditions. In the unimodal comparisons presented, the proposed approaches outperform existing systems even when given a handicap such as fewer training samples or data with a greater number of classes. A separate comprehensive set of experiments on feature fusion show that combining modality data provides a substantial increase in accuracy, with only a few exceptions that occur when differences in the image data quality of two modalities are substantial. However, when two poor quality datasets are fused, noticeable gains in recognition performance are realized when using the novel feature extraction approach. Finally, feature-fusion guidelines are proposed to provide the necessary insight to leverage the rich information effectively when fusing multiple biometric modalities at the feature level. These guidelines serve as the foundation to better understand and construct biometric systems that are effective in a variety of applications