Search results for: multimodal biometrics

Authors: Niloofar Yousefi, Marie Alaghband, Ivan Garibay

Abstract:

With the increase of credit card usage, the volume of credit card misuse also has significantly increased, which may cause appreciable financial losses for both credit card holders and financial organizations issuing credit cards. As a result, financial organizations are working hard on developing and deploying credit card fraud detection methods, in order to adapt to ever-evolving, increasingly sophisticated defrauding strategies and identifying illicit transactions as quickly as possible to protect themselves and their customers. Compounding on the complex nature of such adverse strategies, credit card fraudulent activities are rare events compared to the number of legitimate transactions. Hence, the challenge to develop fraud detection that are accurate and efficient is substantially intensified and, as a consequence, credit card fraud detection has lately become a very active area of research. In this work, we provide a survey of current techniques most relevant to the problem of credit card fraud detection. We carry out our survey in two main parts. In the first part, we focus on studies utilizing classical machine learning models, which mostly employ traditional transnational features to make fraud predictions. These models typically rely on some static physical characteristics, such as what the user knows (knowledge-based method), or what he/she has access to (object-based method). In the second part of our survey, we review more advanced techniques of user authentication, which use behavioral biometrics to identify an individual based on his/her unique behavior while he/she is interacting with his/her electronic devices. These approaches rely on how people behave (instead of what they do), which cannot be easily forged. By providing an overview of current approaches and the results reported in the literature, this survey aims to drive the future research agenda for the community in order to develop more accurate, reliable and scalable models of credit card fraud detection.

Keywords: Credit Card Fraud Detection, User Authentication, Behavioral Biometrics, Machine Learning, Literature Survey

Procedia PDF Downloads 87

Authors: Fedili Benamar, Beloulou Mohamed Lamine, Ouahes Hassane, Ghattas Samir

Abstract:

 Background and aims: Peripheral regional anesthesia has been integrated into most analgesia protocols for total knee arthroplasty which considered among the most painful surgeries with a huge potential for chronicization. The adductor canal block (ACB) has gained popularity. Similarly, the IPACK block has been described to provide analgesia of the posterior knee capsule. This study aimed to evaluate the analgesic efficacy of this block in patients undergoing primary PTG. Methods: 90 patients were randomized to receive either an IPACK, an anterior sciatic block, or a sham block (30 patients in each group + multimodal analgesia and a catheter in the KCA adductor canal). GROUP 1 KCA GROUP 2 KCA+BSA GROUP 3 KCA+IPACK The analgesic blocks were done under echo-guidance preoperatively respecting the safety rules, the dose administered was 20 cc of ropivacaine 0.25% was used. We were to assess posterior knee pain 6 hours after surgery. Other endpoints included quality of recovery after surgery, pain scores, opioid requirements (PCA morphine)(EPI info 7.2 analysis). Results: -groups were matched -A predominance of women (4F/1H). -average age: 68 +/-7 years -the average BMI =31.75 kg/m2 +/- 4. -70% of patients ASA2 ,20% ASA3. -The average duration of the intervention: 89 +/- 19 minutes. -Morphine consumption (PCA) significantly higher in group 1 (16mg) & group 2 (8mg) group 3 (4mg) - The groups were matched . -There was a correlation between the use of the ipack block and postoperative pain Conclusions :In a multimodal analgesic protocol, the addition of IPACK block decreased pain scores and morphine consumption ,

Keywords: regional anesthesia, analgesia, total knee arthroplasty, the adductor canal block (acb), the ipack block, pain

Procedia PDF Downloads 37

Authors: Marina Charalambous, Phivos Phylactou, Thekla Elriz, Loukia Psychogios, Jean-Marie Annoni

Abstract:

Background: Evidence-based practices for the evaluation and treatment of people with aphasia (PWA) in Greek are mainly impairment-based. Functional and multimodal communication is usually under assessed and neglected by clinicians. This study explores the adaptation and psychometric testing of the Greek (GR) version of The Scenario Test. The Scenario Test assesses the everyday functional communication of PWA in an interactive multimodal communication setting with the support of an active communication facilitator. Aims: To define the reliability and validity of The Scenario Test GR and discuss its clinical value. Methods & Procedures: The Scenario Test-GR was administered to 54 people with chronic stroke (6+ months post-stroke): 32 PWA and 22 people with stroke without aphasia. Participants were recruited from Greece and Cyprus. All measures were performed in an interview format. Standard psychometric criteria were applied to evaluate reliability (internal consistency, test-retest, and interrater reliability) and validity (construct and known – groups validity) of the Scenario Test GR. Video analysis was performed for the qualitative examination of the communication modes used. Outcomes & Results: The Scenario Test-GR shows high levels of reliability and validity. High scores of internal consistency (Cronbach’s α = .95), test-retest reliability (ICC = .99), and interrater reliability (ICC = .99) were found. Interrater agreement in scores on individual items fell between good and excellent levels of agreement. Correlations with a tool measuring language function in aphasia (the Aphasia Severity Rating Scale of the Boston Diagnostic Aphasia Examination), a measure of functional communication (the Communicative Effectiveness Index), and two instruments examining the psychosocial impact of aphasia (the Stroke and Aphasia Quality of Life questionnaire and the Aphasia Impact Questionnaire) revealed good convergent validity (all ps< .05). Results showed good known – groups validity (Mann-Whitney U = 96.5, p < .001), with significantly higher scores for participants without aphasia compared to those with aphasia. Conclusions: The psychometric qualities of The Scenario Test-GR support the reliability and validity of the tool for the assessment of functional communication for Greek-speaking PWA. The Scenario Test-GR can be used to assess multimodal functional communication, orient aphasia rehabilitation goal setting towards the activity and participation level, and be used as an outcome measure of everyday communication. Future studies will focus on the measurement of sensitivity to change in PWA with severe non-fluent aphasia.

Keywords: the scenario test GR, functional communication assessment, people with aphasia (PWA), tool validation

Procedia PDF Downloads 103

Authors: Hadri Hussain, M.Nasir Ibrahim, Chee-Ming Ting, Mariani Idroas, Fuad Numan, Alias Mohd Noor

Abstract:

A biometric security system has become an important application in client identification and verification system. A conventional biometric system is normally based on unimodal biometric that depends on either behavioural or physiological information for authentication purposes. The behavioural biometric depends on human body biometric signal (such as speech) and biosignal biometric (such as electrocardiogram (ECG) and phonocardiogram or heart sound (HS)). The speech signal is commonly used in a recognition system in biometric, while the ECG and the HS have been used to identify a person’s diseases uniquely related to its cluster. However, the conventional biometric system is liable to spoof attack that will affect the performance of the system. Therefore, a multimodal biometric security system is developed, which is based on biometric signal of ECG, HS, and speech. The biosignal data involved in the biometric system is initially segmented, with each segment Mel Frequency Cepstral Coefficients (MFCC) method is exploited for extracting the feature. The Hidden Markov Model (HMM) is used to model the client and to classify the unknown input with respect to the modal. The recognition system involved training and testing session that is known as client identification (CID). In this project, twenty clients are tested with the developed system. The best overall performance at 44 kHz was 93.92% for ECG and the worst overall performance was ECG at 88.47%. The results were compared to the best overall performance at 44 kHz for (20clients) to increment of clients, which was 90.00% for HS and the worst overall performance falls at ECG at 79.91%. It can be concluded that the difference multimodal biometric has a substantial effect on performance of the biometric system and with the increment of data, even with higher frequency sampling, the performance still decreased slightly as predicted.

Keywords: electrocardiogram, phonocardiogram, hidden markov model, mel frequency cepstral coeffiecients, client identification

Procedia PDF Downloads 252

Authors: Digvijaysingh S. Bana, Kiran R. Trivedi

Abstract:

This paper introduces various methods for the alpha wave to detect the difference between two states of brain. One healthy subject participated in the experiment. EEG was measured on the forehead above the eye (FP1 Position) with reference and ground electrode are on the ear clip. The data samples are obtained in the form of EEG raw data. The time duration of reading is of one minute. Various test are being performed on the alpha band EEG raw data.The readings are performed in different time duration of the entire day. The statistical analysis is being carried out on the EEG sample data in the form of various tests.

Keywords: electroencephalogram(EEG), biometrics, authentication, EEG raw data

Procedia PDF Downloads 438

Authors: Saulutė Juzelėnienė, Skirmantė Šarkauskienė

Abstract:

In this paper, it is aimed to analyse the multimodal representations of the concepts of LOVE and PASSION in Lithuanian graphic novel “Gertrūda”, by Gerda Jord. The research is based on the earlier findings by Forceville (2005), Eerden (2009) as well as insights made by Shihara and Matsunaka (2009) and Kövecses (2000). The domains of target and source of LOVE and PASSION metaphors in comics are expressed by verbal and non-verbal cues. The analysis of non-verbal cues adopts the concepts of rune and indexes. A pictorial rune is a graphic representation of an object that does not exist in reality in comics, such as lines, dashes, text "balloons", and pictorial index – a graphically represented object of reality, a real symptom expressing a certain emotion, such as a wide smile, furrowed eyebrows, etc. Indexes are often hyperbolized in comics. The research revealed that most frequent source domains are CLOSINESS/UNITY, NATURAL/ PHYSICAL FORCE, VALUABLE OBJECT, PRESSURE. The target is the emotion of LOVE/PASSION which belongs to a more abstract domain of psychological experience. In this kind of metaphor, the picture can be interpreted as representing the emotion of happiness. Data are taken from Lithuanian comic books and Internet sites, where comics have been presented. The data and the analysis we are providing in this article aims to reveal that there are pictorial metaphors that manifest conceptual metaphors that are also expressed verbally and that methodological framework constructed for the analysis in the papers by Forceville at all is applicable to other emotions and culture specific pictorial manifestations.

Keywords: multimodal metaphor, conceptual metaphor, comics, graphic novel, concept of love/passion

Procedia PDF Downloads 44

Authors: O. Iyare, A. H. Afolayan, O. T. Oluwadare, B. K. Alese

Abstract:

Access to advanced medical services has been one of the medical challenges faced by our present society especially in distant geographical locations which may be inaccessible. Then the need for telemedicine arises through which live videos of a doctor can be streamed to a patient located anywhere in the world at any time. Patients’ medical records contain very sensitive information which should not be made accessible to unauthorized people in order to protect privacy, integrity and confidentiality. This research work focuses on a more robust security measure which is biometric (fingerprint) as a form of access control to data of patients by the medical specialist/practitioner.

Keywords: biometrics, telemedicine, privacy, patient information

Procedia PDF Downloads 265

Authors: Tunde Ope-Davies

Abstract:

Transmediality and platformization as online content-sharing protocols have continued to accentuate the growing impact of the unprecedented digital revolution across the world. The rapid transformation across all sectors as a result of this revolution has continued to spotlight the increasing importance of new media technologies in redefining and reshaping the rhythm and dynamics of our private and public discursive practices. Equally, social and political activities are being impacted daily through the creation and transmission of political discourse content through multi-channel platforms such as mobile telephone communication, social media networks and the internet. It has been observed that digital platforms have become central to the production, processing, and distribution of multimodal social data and cultural content. The platformization paradigm thus underpins our understanding of how digital platforms enhance the production and heterogenous distribution of media and cultural content through these platforms and how this process facilitates socioeconomic and political activities. The use of multiple digital platforms to share and transmit political discourse material synchronously and asynchronously has gained some exciting momentum in the last few years. Nigeria’s 2023 general elections amplified the usage of social media and other online platforms as tools for electioneering campaigns, socio-political mobilizations and civic engagement. The study, therefore, focuses on transmedia and platformed political discourse as a new strategy to promote political candidates and their manifesto in order to mobilize support and woo voters. This innovative transmedia digital discourse model involves a constellation of online texts and images transmitted through different online platforms almost simultaneously. The data for the study was extracted from the 2023 general elections campaigns in Nigeria between January- March 2023 through media monitoring, manual download and the use of software to harvest the online electioneering campaign material. I adopted a discursive-analytic qualitative technique with toolkits drawn from a computer-mediated multimodal discourse paradigm. The study maps the progressive development of digital political discourse in this young democracy. The findings also demonstrate the inevitable transformation of modern democratic practice through platform-dependent and transmedia political discourse. Political actors and media practitioners now deploy layers of social media network platforms to convey messages and mobilize supporters in order to aggregate and maximize the impact of their media campaign projects and audience reach.

Keywords: social media, digital humanities, political discourse, platformized discourse, multimodal discourse

Procedia PDF Downloads 53

Authors: Rauha Salam

Abstract:

In Pakistan, over the past decade, the notion of what counts as a true ‘masculine and feminine’ behaviour has become more complicated with the inspection of social media. Given its strong religious and socio-cultural norms, patriarchal values are entrenched in the local and cultural traditions of the Pakistani society and regulate the social value of gender. However, the increasing use of internet among Pakistani men and women, especially in the form of social media uses by the youth, is increasingly becoming disruptive and challenging to the strict modes of behavioural monitoring and control both at familial and state level. Facebook, being the prime social media communication platform in Pakistan, provide its users a relatively ‘safe’ place to embrace how they want to be perceived by their audience. Moreover, the availability of an array of semiotic resources (e.g. the videos, audios, visuals and gifs) on Facebook makes it possible for the users to create a virtual identity that allows them to describe themselves in detail. By making use of Multimodal Discourse Analysis, I aimed to investigate how men and women in Pakistan construct their gendered identities multimodally (visually and linguistically) through their Facebook posts and how these semiotic modes are interconnected to communicate specific meanings. In case of the female data, the analysis showed an ambivalence as females were found to be conforming to the existing socio-cultural norms of the society and they were also employing social media platforms to deviate from traditional gendered patterns and to voice their opinions simultaneously. Similarly, the male data highlighted the reproduction of the prevalent cultural models of masculinity. However, there were instances in the data that showed a digression from the standard norms and there is a (re)negotiation of the traditional patriarchal representations.

Keywords: Facebook, Gendered Identities, Multimodal Discourse Analysis, Pakistan

Procedia PDF Downloads 90

Authors: Ana Maria Reis d'Azevedo Breda, Catarina Maria Neto da Cruz

Abstract:

The role of images/illustrations in communicating meanings and triggering emotions assumes an increasingly relevant role in contemporary texts, regardless of the age group for which they are intended or the nature of the texts that host them. It is no coincidence that children's books are full of illustrations and that the image/text ratio decreases as the age group grows. The vast majority of children's books can be considered multimodal texts containing text and images/illustrations interacting with each other to provide the young reader with a broader and more creative understanding of the book's narrative. This interaction is very diverse, ranging from images/illustrations that are not essential for understanding the storytelling to those that contribute significantly to the meaning of the story. Usually, these books are also read by adults, namely by parents, educators, and teachers who act as mediators between the book and the children, explaining aspects that are or seem to be too complex for the child's context. It should be noted that there are books labeled as children's books that are clearly intended for both children and adults. In this work, following a qualitative and interpretative methodology based on written productions, participant observation, and field notes, we will describe the perceptions of future teachers of the 1st cycle of basic education, attending a master's degree at a Portuguese university, about the role of the image in literary and non-literary texts, namely in mathematical texts, and how these can constitute precious resources for emotional regulation and for the design of creative didactic situations. The analysis of the collected data allowed us to obtain evidence regarding the evolution of the participants' perception regarding the crucial role of images in children's literature, not only as an emotional regulator for young readers but also as a creative source for the design of meaningful didactical situations, crossing other scientific areas, other than the mother tongue, namely mathematics.

Keywords: children’s literature, emotions, multimodal texts, soft skills

Procedia PDF Downloads 57

Authors: Md. Khayrul Bashar, Md. Saiful Islam, Kimiko Yamashita, Yano Midori

Abstract:

Despite having some progress in human authentication, conventional biometrics (e.g., facial features, fingerprints, retinal scans, gait, voice patterns) are not robust against falsification because they are neither confidential nor secret to an individual. As a non-invasive tool, electrocardiogram (ECG) has recently shown a great potential in human recognition due to its unique rhythms characterizing the variability of human heart structures (chest geometry, sizes, and positions). Moreover, ECG has a real-time vitality characteristic that signifies the live signs, which ensure legitimate individual to be identified. However, the detection accuracy of the current ECG-based methods is not sufficient due to a high variability of the individual’s heartbeats at a different instance of time. These variations may occur due to muscle flexure, the change of mental or emotional states, and the change of sensor positions or long-term baseline shift during the recording of ECG signal. In this study, a new method is proposed for human identification, which is based on the extraction of the local roughness of ECG heartbeat signals. First ECG signal is preprocessed using a second order band-pass Butterworth filter having cut-off frequencies of 0.00025 and 0.04. A number of local binary patterns are then extracted by applying a moving neighborhood window along the ECG signal. At each instant of the ECG signal, the pattern is formed by comparing the ECG intensities at neighboring time points with the central intensity in the moving window. Then, binary weights are multiplied with the pattern to come up with the local roughness description of the signal. Finally, histograms are constructed that describe the heartbeat signals of individual subjects in the database. One advantage of the proposed feature is that it does not depend on the accuracy of detecting QRS complex, unlike the conventional methods. Supervised recognition methods are then designed using minimum distance to mean and Bayesian classifiers to identify authentic human subjects. An experiment with sixty (60) ECG signals from sixty adult subjects from National Metrology Institute of Germany (NMIG) - PTB database, showed that the proposed new method is promising compared to a conventional interval and amplitude feature-based method.

Keywords: human identification, ECG biometrics, local roughness patterns, supervised classification

Procedia PDF Downloads 376

Authors: Alena Radina

Abstract:

On the global stage, national image is shaped by historical memory of wars and alliances, government ideology and particularly media stereotypes which represent countries in positive or negative ways. News magazine covers are a key site for national representation. The object of analysis in this paper is the portrayals of the US, Germany, China, and Russia in the front pages and cover stories of “Time”, “Der Spiegel”, “Beijing Review”, and “Expert”. Political comedy helps people learn about current affairs even if politics is not their area of interest, and thus satire indirectly sets the public agenda. Coupled with satirical messages, cover images and the linguistic messages embedded in the covers become persuasive visual and verbal factors, known to drive about 80% of magazine sales. Preliminary analysis identified satirical elements in magazine covers, which are known to influence and frame understandings and attract younger audiences. Multimodal and transnational comparative framing analyses lay the groundwork to investigate why journalists, editors and designers deploy certain frames rather than others. This research investigates to what degree frames used in covers correlate with frames within the cover stories and what these framings can tell us about media professionals’ representations of their own and other nations. The study sample includes 32 covers consisting of two covers representing each of the four chosen countries from the four magazines. The sampling framework considers two time periods to compare countries’ representation with two different presidents, and between men and women when present. The countries selected for analysis represent each category of the international news flows model: the core nations are the US and Germany; China is a semi-peripheral country; and Russia is peripheral. Examining textual and visual design elements on the covers and images in the cover stories reveals not only what editors believe visually attracts the reader’s attention to the magazine but also how the magazines frame and construct national images and national leaders. The cover is the most powerful editorial and design page in a magazine because images incorporate less intrusive framing tools. Thus, covers require less cognitive effort of audiences who may therefore be more likely to accept the visual frame without question. Analysis of design and linguistic elements in magazine covers helps to understand how media outlets shape their audience’s perceptions and how magazines frame global issues. While previous multimodal research of covers has focused mostly on lifestyle magazines or newspapers, this paper examines the power of current affairs magazines’ covers to shape audience perception of national image.

Keywords: framing analysis, magazine covers, multimodality, national image, satire

Procedia PDF Downloads 74

Authors: Luisa Mesquita Oliveira Ribeiro, Alexei Manso Correa Machado

Abstract:

Handwritten signature is a unique form for recognizing an individual, used to discern documents, carry out investigations in the criminal, legal, banking areas and other applications. Signature verification is based on large amounts of biometric data, as they are simple and easy to acquire, among other characteristics. Given this scenario, signature forgery is a worldwide recurring problem and fast and precise techniques are needed to prevent crimes of this nature from occurring. This article carried out a study on the efficiency of the Capsule Network in analyzing and recognizing signatures. The chosen architecture achieved an accuracy of 98.11% and 80.15% for the CEDAR and GPDS databases, respectively.

Keywords: biometrics, deep learning, handwriting, signature forgery

Procedia PDF Downloads 44

Authors: Efstratios Karavasilis, Foteini Christidi, Georgios Velonakis, Agapi Plousi, Kalliopi Platoni, Nikolaos Kelekis, Ioannis Evdokimidis, Efstathios Efstathopoulos

Abstract:

Introduction: Advanced structural and functional neuroimaging techniques contribute to the study of anatomical and functional brain connectivity and its role in the pathophysiology and symptoms’ heterogeneity in several neurodegenerative disorders, including multiple sclerosis (MS). Aim: In the present study, we applied multiparametric neuroimaging techniques to investigate the structural and functional cortico-cerebellar changes in MS patients. Material: We included 51 MS patients (28 with clinically isolated syndrome [CIS], 31 with relapsing-remitting MS [RRMS]) and 51 age- and gender-matched healthy controls (HC) who underwent MRI in a 3.0T MRI scanner. Methodology: The acquisition protocol included high-resolution 3D T1 weighted, diffusion-weighted imaging and echo planar imaging sequences for the analysis of volumetric, tractography and functional resting state data, respectively. We performed between-group comparisons (CIS, RRMS, HC) using CAT12 and CONN16 MATLAB toolboxes for the analysis of volumetric (cerebellar gray matter density) and functional (cortico-cerebellar resting-state functional connectivity) data, respectively. Brainance suite was used for the analysis of tractography data (cortico-cerebellar white matter integrity; fractional anisotropy [FA]; axial and radial diffusivity [AD; RD]) to reconstruct the cerebellum tracts. Results: Patients with CIS did not show significant gray matter (GM) density differences compared with HC. However, they showed decreased FA and increased diffusivity measures in cortico-cerebellar tracts, and increased cortico-cerebellar functional connectivity. Patients with RRMS showed decreased GM density in cerebellar regions, decreased FA and increased diffusivity measures in cortico-cerebellar WM tracts, as well as a pattern of increased and mostly decreased functional cortico-cerebellar connectivity compared to HC. The comparison between CIS and RRMS patients revealed significant GM density difference, reduced FA and increased diffusivity measures in WM cortico-cerebellar tracts and increased/decreased functional connectivity. The identification of decreased WM integrity and increased functional cortico-cerebellar connectivity without GM changes in CIS and the pattern of decreased GM density decreased WM integrity and mostly decreased functional connectivity in RRMS patients emphasizes the role of compensatory mechanisms in early disease stages and the disintegration of structural and functional networks with disease progression. Conclusions: In conclusion, our study highlights the added value of multimodal neuroimaging techniques for the in vivo investigation of cortico-cerebellar brain changes in neurodegenerative disorders. An extension and future opportunity to leverage multimodal neuroimaging data inevitably remain the integration of such data in the recently-applied mathematical approaches of machine learning algorithms to more accurately classify and predict patients’ disease course.

Keywords: advanced neuroimaging techniques, cerebellum, MRI, multiple sclerosis

Procedia PDF Downloads 117

Authors: Jared Cheves, Amanda DeChent, Joyce Pan

Abstract:

Total knee replacements (TKAs) are one of the most common but painful surgical procedures performed in the United States. Currently, the gold standard for postoperative pain management is the utilization of opioids. However, in the wake of the opioid epidemic, the healthcare system is attempting to reduce opioid consumption by trialing innovative opioid sparing analgesic techniques such as continuous peripheral nerve blocks (CPNB) and continuous periarticular infiltration (CPAI). The alleviation of pain, particularly during the first 72 hours postoperatively, is of utmost importance due to its association with delayed recovery, impaired rehabilitation, immunosuppression, the development of chronic pain, the development of rebound pain, and decreased patient satisfaction. While both CPNB and CPAI are being used today, there is limited evidence comparing the two to the current standard of care or to each other. An extensive literature review was performed to explore the safety profiles and effectiveness of CPNB and CPAI in reducing reported pain scores and decreasing opioid consumption. The literature revealed the usage of CPNB contributed to lower pain scores and decreased opioid use when compared to opioid-only control groups. Additionally, CPAI did not improve pain scores or decrease opioid consumption when combined with a multimodal analgesic (MMA) regimen. When comparing CPNB and CPAI to each other, neither unanimously lowered pain scores to a greater degree, but the literature indicates that CPNB decreased opioid consumption more than CPAI. More research is needed to further cement the efficacy of CPNB and CPAI as standard components of MMA in TKA procedures. In addition, future research can also focus on novel catheter-free applications to reduce the complications of continuous catheter analgesics.

Keywords: total knee arthroplasty, continuous peripheral nerve blocks, continuous periarticular infiltration, opioid, multimodal analgesia

Procedia PDF Downloads 60

Authors: P. Weerkamp Bartholomeus

Abstract:

Autism treatment evaluation is crucial for monitoring the development of an intervention at an early stage. ‘ReAttach’ is a new intervention based on the principles of attachment and social cognitive training. Practical research suggests promising results on a variety of developmental areas. Five years after the first ReAttach sessions these findings can be extended with qualitative research by means of follow-up interviews. The potential impact of this treatment on daily life functioning and well-being of autistic persons becomes clear.

Keywords: autism, innovation, treatment, social cognitive training

Procedia PDF Downloads 261

Authors: Safa Saoudi, Souheib Yousfi, Riadh Robbana

Abstract:

E-passport is a relatively new electronic document which maintains the passport features and provides better security. It deploys new technologies such as biometrics and Radio Frequency identification (RFID). The international civil aviation organization (ICAO) and the European union define mechanisms and protocols to provide security but their solutions present many threats. In this paper, a new mechanism is presented to strengthen e-passport security and authentication process. We propose a new protocol based on Elliptic curve, identity based encryption and shared secret between entities. Authentication in our contribution is formally proved with BAN Logic verification language. This proposal aims to provide a secure data storage and authentication.

Keywords: e-passport, elliptic curve cryptography, identity based encryption, shared secret, BAN Logic

Procedia PDF Downloads 403

Authors: Andrew Lock, Alastair Allen

Abstract:

Fragile watermarking has been proposed as a means of adding additional security or functionality to biometric systems, particularly for authentication and tamper detection. In this paper we describe an experimental study on the effect of watermarking iris images with a particular class of fragile algorithm, reversible algorithms, and the ability to correctly perform iris recognition. We investigate two scenarios, matching watermarked images to unmodified images, and matching watermarked images to watermarked images. We show that different watermarking schemes give very different results for a given capacity, highlighting the importance of investigation. At high embedding rates most algorithms cause significant reduction in recognition performance. However, in many cases, for low embedding rates, recognition accuracy is improved by the watermarking process.

Keywords: biometrics, iris recognition, reversible watermarking, vision engineering

Procedia PDF Downloads 421

Authors: Luo Jiaoyang, Yu Hongyang

Abstract:

In this paper, we explore a method that can be used in the working scene of intelligent industrial robots to confirm the identity information of operators to ensure that the robot executes instructions in a sufficiently safe environment. This approach uses three information modalities, namely visible light, depth, and sound. We explored a variety of fusion modes for the three modalities and finally used the joint feature learning method to improve the performance of the model in the case of noise compared with the single-modal case, making the maximum noise in the experiment. It can also maintain an accuracy rate of more than 90%.

Keywords: multimodal, kinect, machine learning, distance image

Procedia PDF Downloads 51

Authors: Prikhil Agrawal, N. Priyanka

Abstract:

With the increase of millions of users on Internet day by day, it is very essential to maintain highly reliable and secured data communication between various corporations. Although there are various traditional security imparting techniques such as antivirus software, password protection, data encryption, biometrics and firewall etc. But still network security has become the main issue in various leading companies. So IDSs have become an essential component in terms of security, as it can detect various network attacks and respond quickly to such occurrences. IDSs are used to detect unauthorized access to a computer system. This paper describes various intrusion detection techniques using GA approach. The intrusion detection problem has become a challenging task due to the conception of miscellaneous computer networks under various vulnerabilities. Thus the damage caused to various organizations by malicious intrusions can be mitigated and even be deterred by using this powerful tool.

Keywords: genetic algorithm (GA), intrusion detection system (IDS), dataset, network security

Procedia PDF Downloads 263

Authors: Gertraud Koch, Teresa Stumpf, Alejandra Tijerina García

Abstract:

Discourse analysis research approaches belong to the central research strategies applied throughout the humanities; they focus on the countless forms and ways digital texts and images shape present-day notions of the world. Despite the constantly growing number of relevant digital, multimodal discourse resources, digital humanities (DH) methods are thus far not systematically developed and accessible for discourse analysis approaches. Specifically, the significance of multimodality and meaning plurality modelling are yet to be sufficiently addressed. In order to address this research gap, the D-WISE project aims to develop a prototypical working environment as digital support for the sociology of knowledge approach to discourse analysis and new IT-analysis approaches for the use of context-oriented embedding representations. Playing an essential role throughout our research endeavor is the constant optimization of hermeneutical methodology in the use of (semi)automated processes and their corresponding epistemological reflection. Among the discourse analyses, the sociology of knowledge approach to discourse analysis is characterised by the reconstructive and accompanying research into the formation of knowledge systems in social negotiation processes. The approach analyses how dominant understandings of a phenomenon develop, i.e., the way they are expressed and consolidated by various actors in specific arenas of discourse until a specific understanding of the phenomenon and its socially accepted structure are established. This article presents insights and initial findings from D-WISE, a joint research project running since 2021 between the Institute of Anthropological Studies in Culture and History and the Language Technology Group of the Department of Informatics at the University of Hamburg. As an interdisciplinary team, we develop central innovations with regard to the availability of relevant DH applications by building up a uniform working environment, which supports the procedure of the sociology of knowledge approach to discourse analysis within open corpora and heterogeneous, multimodal data sources for researchers in the humanities. We are hereby expanding the existing range of DH methods by developing contextualized embeddings for improved modelling of the plurality of meaning and the integrated processing of multimodal data. The alignment of this methodological and technical innovation is based on the epistemological working methods according to grounded theory as a hermeneutic methodology. In order to systematically relate, compare, and reflect the approaches of structural-IT and hermeneutic-interpretative analysis, the discourse analysis is carried out both manually and digitally. Using the example of current discourses on digitization in the healthcare sector and the associated issues regarding data protection, we have manually built an initial data corpus of which the relevant actors and discourse positions are analysed in conventional qualitative discourse analysis. At the same time, we are building an extensive digital corpus on the same topic based on the use and further development of entity-centered research tools such as topic crawlers and automated newsreaders. In addition to the text material, this consists of multimodal sources such as images, video sequences, and apps. In a blended reading process, the data material is filtered, annotated, and finally coded with the help of NLP tools such as dependency parsing, named entity recognition, co-reference resolution, entity linking, sentiment analysis, and other project-specific tools that are being adapted and developed. The coding process is carried out (semi-)automated by programs that propose coding paradigms based on the calculated entities and their relationships. Simultaneously, these can be specifically trained by manual coding in a closed reading process and specified according to the content issues. Overall, this approach enables purely qualitative, fully automated, and semi-automated analyses to be compared and reflected upon.

Keywords: entanglement of structural IT and hermeneutic-interpretative analysis, multimodality, plurality of meaning, sociology of knowledge approach to discourse analysis

Procedia PDF Downloads 202

Authors: Fuad M. Alkoot

Abstract:

DNA data have been used in forensics for decades. However, current research looks at using the DNA as a biometric identity verification modality. The goal is to improve the speed of identification. We aim at using gene data that was initially used for autism detection to find if and how accurate is this data for identification applications. Mainly our goal is to find if our data preprocessing technique yields data useful as a biometric identification tool. We experiment with using the nearest neighbor classifier to identify subjects. Results show that optimal classification rate is achieved when the test set is corrupted by normally distributed noise with zero mean and standard deviation of 1. The classification rate is close to optimal at higher noise standard deviation reaching 3. This shows that the data can be used for identity verification with high accuracy using a simple classifier such as the k-nearest neighbor (k-NN). 

Keywords: biometrics, genetic data, identity verification, k nearest neighbor

Procedia PDF Downloads 225

Authors: Tsu-Wang Shen, Shan-Chun Chang, Chih-Hsien Wang, Te-Chao Fang

Abstract:

For electrocardiogram (ECG) biometrics system, it is a tedious process to pre-install user’s high-intensity heart rate (HR) templates in ECG biometric systems. Based on only resting enrollment templates, it is a challenge to identify human by using ECG with the high-intensity HR caused from exercises and stress. This research provides a heartbeat segment method with slope-oriented neural networks against the ECG morphology changes due to high intensity HRs. The method has overall system accuracy at 97.73% which includes six levels of HR intensities. A cumulative match characteristic curve is also used to compare with other traditional ECG biometric methods.

Keywords: high-intensity heart rate, heart rate resistant, ECG human identification, decision based artificial neural network

Procedia PDF Downloads 393

Authors: Shen Jian, Hu Jie, Qi Jin, Liu Wei Jie, Chen Ji Yi, Peng Ying Hong

Abstract:

In order to settle the problem of acquiring case in biological related to design problems, a biometrics instance acquisition method based on text mining is presented. Through the construction of corpus text vector space and knowledge mining, the feature selection, similarity measure and case retrieval method of text in the field of biology are studied. First, we establish a vector space model of the corpus in the biological field and complete the preprocessing steps. Then, the corpus is retrieved by using the vector space model combined with the functional keywords to obtain the biological domain examples related to the design problems. Finally, we verify the validity of this method by taking the example of text.

Keywords: text mining, vector space model, feature selection, biologically inspired design

Procedia PDF Downloads 227

Authors: Ryan C. Zlomek

Abstract:

The value of using comics in the literacy classroom has been explored since the 1930s. At that point in time researchers had begun to implement comics into daily lesson plans and, in some instances, had started the development process for comics-supported curriculum. In the mid-1950s, this type of research was cut short due to the work of psychiatrist Frederic Wertham whose research seemingly discovered a correlation between comic readership and juvenile delinquency. Since Wertham’s allegations the comics medium has had a hard time finding its way back to education. Now, over fifty years later, the definition of literacy is in mid-transition as the world has become more visually-oriented and students require the ability to interpret images as often as words. Through this transition, comics has found a place in the field of literacy education research as the shift focuses from traditional print to multimodal and media literacies. Comics are now believed to be an effective resource in bridging the gap between these different types of literacies. This paper seeks to better understand what students learn from the process of reading comics and how those skills line up with the core principles of media literacy education in the United States. In the first section, comics are defined to determine the exact medium that is being examined. The different conventions that the medium utilizes are also discussed. In the second section, the comics reading process is explored through a dissection of the ways a reader interacts with the page, panel, gutter, and different comic conventions found within a traditional graphic narrative. The concepts of intersubjective acts and visualization are attributed to the comics reading process as readers draw in real world knowledge to decode meaning. In the next section, the learning processes that comics encourage are explored parallel to the core principles of media literacy education. Each principle is explained and the extent to which comics can act as an intermediary for this type of education is theorized. In the final section, the author examines comics use in his computer science and technology classroom. He lays out different theories he utilizes from Scott McCloud’s text Understanding Comics and how he uses them to break down media literacy strategies with his students. The article concludes with examples of how comics has positively impacted classrooms around the United States. It is stated that integrating comics into the classroom will not solve all issues related to literacy education but, rather, that comics can be a powerful multimodal resource for educators looking for new mediums to explore with their students.

Keywords: comics, graphics novels, mass communication, media literacy, metacognition

Procedia PDF Downloads 263

Authors: Devika Tanna

Abstract:

'Biometrics' means 'life measurement' but the term is usually associated with the use of unique physiological characteristics to identify an individual. It is important to secure the privacy of digital face image that is stored in central database. To impart privacy to such biometric face images, first, the digital face image is split into two host face images such that, each of it gives no idea of existence of the original face image and, then each cover image is stored in two different databases geographically apart. When both the cover images are simultaneously available then only we can access that original image. This can be achieved by using the XM2VTS and IMM face database, an adaptive algorithm for spatial greyscale. The algorithm helps to select the appropriate host images which are most likely to be compatible with the secret image stored in the central database based on its geometry and appearance. The encryption is done using GEVCS which results in a reconstructed image identical to the original private image.

Keywords: adaptive algorithm, database, host images, privacy, visual cryptography

Procedia PDF Downloads 98

Authors: Degale Desta, Cheng Jian

Abstract:

The most important factor in identifying a person is their face. Even identical twins have their own distinct faces. As a result, identification and face recognition are needed to tell one person from another. A face recognition system is a verification tool used to establish a person's identity using biometrics. Nowadays, face recognition is a common technique used in a variety of applications, including home security systems, criminal identification, and phone unlock systems. This system is more secure because it only requires a facial image instead of other dependencies like a key or card. Face detection and face identification are the two phases that typically make up a human recognition system.The idea behind designing and creating a face recognition system using deep learning with Azure ML Python's OpenCV is explained in this paper. Face recognition is a task that can be accomplished using deep learning, and given the accuracy of this method, it appears to be a suitable approach. To show how accurate the suggested face recognition system is, experimental results are given in 98.46% accuracy using Fast-RCNN Performance of algorithms under different training conditions.

Keywords: deep learning, face recognition, identification, fast-RCNN

Procedia PDF Downloads 91

Authors: Victor N. Anisimov, Lyubov A. Boyko, Yazgul R. Almukhametova, Natalia V. Galkina, Alexander V. Latanov

Abstract:

Modern commercials presented on billboards, TV and on the Internet contain a lot of information about the product or service in text form. However, this information cannot always be perceived and understood by consumers. Typical sociological focus group studies often cannot reveal important features of the interpretation and understanding information that has been read in text messages. In addition, there is no reliable method to determine the degree of understanding of the information contained in a text. Only the fact of viewing a text does not mean that consumer has perceived and understood the meaning of this text. At the same time, the tools based on marketing analysis allow only to indirectly estimate the process of reading and understanding a text. Therefore, the aim of this work is to develop a valid method of recording objective indicators in real time for assessing the fact of reading and the degree of text comprehension. Psychophysiological parameters recorded during text reading can form the basis for this objective method. We studied the relationship between multimodal psychophysiological parameters and the process of text comprehension during reading using the method of correlation analysis. We used eye-tracking technology to record eye movements parameters to estimate visual attention, electroencephalography (EEG) to assess cognitive load and polygraphic indicators (skin-galvanic reaction, SGR) that reflect the emotional state of the respondent during text reading. We revealed reliable interrelations between perceiving the information and the dynamics of psychophysiological parameters during reading the text in commercials. Eye movement parameters reflected the difficulties arising in respondents during perceiving ambiguous parts of text. EEG dynamics in rate of alpha band were related with cumulative effect of cognitive load. SGR dynamics were related with emotional state of the respondent and with the meaning of text and type of commercial. EEG and polygraph parameters together also reflected the mental difficulties of respondents in understanding text and showed significant differences in cases of low and high text comprehension. We also revealed differences in psychophysiological parameters for different type of commercials (static vs. video, financial vs. cinema vs. pharmaceutics vs. mobile communication, etc.). Conclusions: Our methodology allows to perform multimodal evaluation of text perusal and the quality of text reading in commercials. In general, our results indicate the possibility of designing an integral model to estimate the comprehension of reading the commercial text in percent scale based on all noticed markers.

Keywords: reading, commercials, eye movements, EEG, polygraphic indicators

Procedia PDF Downloads 139

Authors: Maria Barriga

Abstract:

The article focuses on the analysis of three images of the last five years that represent different visions of social groups in the context of the so call “Conflicto Mapuche” in la Araucanía, Chile. Using a multimodal social semiotic approach, we analyze the meaning making of these images and the social groups strategies to achieve visibility and recognition in political contexts. We explore the making and appropriation of symbols and concepts and analyze the different strategies that groups use to built hegemonic views. Among these strategies, we compare the use of digital technologies in design these images and the influence of Chilean Estate's vision on the Mapuche political conflict. Finally, we propose visual strategies to improve basic conditions for dialogue and recognition among these groups.

Keywords: visual culture, power, conflict, indigenous people

Procedia PDF Downloads 259

Authors: Ramin Javadzadeh

Abstract:

The particle swarm optimization are Meta heuristic optimization method, which are used for clustering and pattern recognition applications are abundantly. These algorithms in multimodal optimization problems are more efficient than genetic algorithms. A major drawback in these algorithms is their slow convergence to global optimum and their weak stability can be considered in various running of these algorithms. In this paper, improved Particle swarm optimization is introduced for the first time to overcome its problems. The fuzzy cellular automata is used for improving the algorithm efficiently. The credibility of the proposed approach is evaluated by simulations, and it is shown that the proposed approach achieves better results can be achieved compared to the Particle swarm optimization algorithms.

Keywords: cellular automata, cellular learning automata, local search, optimization, particle swarm optimization

Procedia PDF Downloads 569