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Biometric systems are widely used for face recognition. They have rapidly developed in recent years. Compared with other approaches, such as fingerprint recognition, handwriting verification and retinal and iris scanning, face recognition is more straightforward, user friendly and extensively used. The aforementioned approaches, including face recognition, are vulnerable to malicious attacks by impostors; in such cases, face liveness detection comes in handy to ensure both accuracy and robustness. Liveness is an important feature that reflects physiological signs and differentiates artificial from real biometric traits. This paper aims to provide a simple path for the future development of more robust and accurate liveness detection approaches.

This paper discusses about introduction to the face biometric system, liveness detection in face recognition system and comparisons between the different discussed works of existing measures.

This paper presents an overview, comparison and discussion of proposed face liveness detection methods to provide a reference for the future development of more robust and accurate liveness detection approaches.

Biometric scans using fingerprints are widely used for security purposes. Eventually, for authentication purposes, fingerprint scans are not very reliable because they can be faked by obtaining a sample of the fingerprint of the person. There are a few spoof detection techniques available to reduce the incidence of spoofing of the biometric system. Among them, the most commonly used is the binary classification technique that detects real or fake fingerprints based on the fingerprint samples provided during training. However, this technique fails when it is provided with samples formed using other spoofing techniques that are different from the spoofing techniques covered in the training samples. This paper aims to improve the liveness detection accuracy by fusing electrocardiogram (ECG) and fingerprint.

In this paper, to avoid this limitation, an efficient liveness detection algorithm is developed using the fusion of ECG signals captured from the fingertips and fingerprint data in Internet of Things (IoT) environment. The ECG signal will ensure the detection of real fingerprint samples from fake ones.

Single model fingerprint methods have some disadvantages, such as noisy data and position of the fingerprint. To overcome this, fusion of both ECG and fingerprint is done so that the combined data improves the detection accuracy.

System security is improved in this approach, and the fingerprint recognition rate is also improved. IoT-based approach is used in this work to reduce the computation burden of data processing systems.

The purpose of this paper is to introduce a novel respiration pattern-based biometric prediction system (BPS) by using artificial neural network (ANN).

Respiration patterns were obtained using a knitted piezoresistive smart chest band. The ANN model was implemented by using four hidden layers to help achieve the best complexity to produce an adequate fit for the data. Not only did this study give a detailed distribution of an ANN model construction including the scheme of parameters and network layers, ablation of the architecture and the derivation of back-propagation during the iterations but also engaged a step-based decay to systematically drop the learning rate after specific epochs during training to minimize the loss and increase the model’s accuracy as well as to limit the risk of overfitting.

Findings establish the feasibility of using respiratory patterns for biometric identification. Experimental results show that, with a learning rate drop factor = 0.5, the network is able to continue to learn past epoch 40 until stagnation occurs which yielded a classification accuracy of 98 per cent. Out of 51,338 test set, the model achieved 51,557 correctly classified instances and 169 misclassified instances.

The findings provide an impetus for possible studies into the application of chest breathing sensors for human machine interfaces in the area of entertainment.

This is the first time respiratory patterns have been applied in biometric prediction system design.

Personal mobile devices currently have access to a significant portion of their user's private sensitive data and are increasingly used for processing mobile payments. Consequently, securing access to these mobile devices is a requirement for securing access to the sensitive data and potentially costly services. The authors propose and evaluate a first version of a pan shot face unlock method: a mobile device unlock mechanism using all information available from a 180° pan shot of the device around the user's head – utilizing biometric face information as well as sensor data of built‐in sensors of the device. The paper aims to discuss these issues.

This approach uses grayscale 2D images, on which the authors perform frontal and profile face detection. For face recognition, the authors evaluate different support vector machines and neural networks. To reproducibly evaluate this pan shot face unlock toolchain, the authors assembled the 2013 Hagenberg stereo vision pan shot face database, which the authors describe in detail in this article.

Current results indicate that the approach to face recognition is sufficient for further usage in this research. However, face detection is still error prone for the mobile use case, which consequently decreases the face recognition performance as well.

The contributions of this paper include: introducing pan shot face unlock as an approach to increase security and usability during mobile device authentication; introducing the 2013 Hagenberg stereo vision pan shot face database; evaluating this current pan shot face unlock toolchain using the newly created face database.

Presents an approach to improved performance and flexibility in industrial robotics by means of sensor integration and feedback control in task‐level programming and task execution. Also presents feasibility studies in support of the ideas. Discusses some solutions to the problem using six degrees of freedom force control together with the ABB S4CPlus system as an illustrative example. Consider various problems in the design of an open sensor interface for industrial robotics and discusses possible solutions. Finally, presents experimental results from industrial force controlled grinding.

To identify safeguards against threats and vulnerabilities posed by the emerging world of ambient intelligence.

Dark scenarios were constructed to highlight the threats and vulnerabilities; safeguards are identified to address those threats and vulnerabilities and recommendations for specific stakeholders are made for implementing those safeguards.

A multiplicity of threats and vulnerabilities can be expected in the emerging world of ambient intelligence, and a multiplicity of safeguards are similarly necessary to address those.

Additional technological research is necessary in order to develop some of the safeguards envisaged as necessary.

The existing legal and regulatory regime suffers from various lacunae and must be amended to address AmI challenges. Many stakeholders have important roles to play.

The paper identifies necessary safeguards to protect privacy, identity, trust, security and e‐inclusion. It identifies specific recommendations for the European Commission, Member States, industry, civil society organizations, academia and individuals.

The purpose of this paper is to investigate factors that influence customers’ adoption of biometric-based point-of-sale in Brunei.

This paper extends technology acceptance model constructs with trust and some other variables as the framework to investigate their influence on the attitude toward the usage of a biometric point-of-sale terminal for payments in Brunei. Nine variables may influence user’s perception toward usage. The nine variables are needed, perceived ease of use, perceived usefulness, experience, innovativeness, privacy, security, trust and attitude toward usage. Multiple regression analysis was conducted to test hypotheses related to these nine variables.

It is found that the innovativeness of an individual and similar experience corresponds toward trust, which is positively related to attitude toward usage. Perceived usefulness and trust have significantly influenced the intention of individuals to use biometrics as an authentication method for payment.

The nature of this research is to gather the public’s opinion and perception as much as it is deemed possible to get a bigger and clearer picture of the study. As the target respondence is citizens and residents of Brunei without any specification or exclusion, a large response would be needed to have a more reliable and accurate result. However, only 205 respondents can be gathered in this study. Had there been a longer time frame, it would be best to gather a lot more responses.

This paper explores the adoption of biometric authentication in large-scale point-of-terminals. It identifies factors that influence adoption. The results of this study could assist future researchers in which direction to take to further explore biometric as an authentication method for payment. In addition to this, it could also provide banks and financial technology in Brunei a clearer picture of the Brunei market and Bruneians perspective on the biometric system.

This paper presents a survey of research into interactive robotic systems for the purpose of identifying the state of the art capabilities as well as the extant gaps in this emerging field. Communication is multimodal. Multimodality is a representation of many modes chosen from rhetorical aspects for its communication potentials. The author seeks to define the available automation capabilities in communication using multimodalities that will support a proposed Interactive Robot System (IRS) as an AI mounted robotic platform to advance the speed and quality of military operational and tactical decision making.

This review will begin by presenting key developments in the robotic interaction field with the objective of identifying essential technological developments that set conditions for robotic platforms to function autonomously. After surveying the key aspects in Human Robot Interaction (HRI), Unmanned Autonomous System (UAS), visualization, Virtual Environment (VE) and prediction, the paper then proceeds to describe the gaps in the application areas that will require extension and integration to enable the prototyping of the IRS. A brief examination of other work in HRI-related fields concludes with a recapitulation of the IRS challenge that will set conditions for future success.

Using insights from a balanced cross section of sources from the government, academic, and commercial entities that contribute to HRI a multimodal IRS in military communication is introduced. Multimodal IRS (MIRS) in military communication has yet to be deployed.

Multimodal robotic interface for the MIRS is an interdisciplinary endeavour. This is not realistic that one can comprehend all expert and related knowledge and skills to design and develop such multimodal interactive robotic interface. In this brief preliminary survey, the author has discussed extant AI, robotics, NLP, CV, VDM, and VE applications that is directly related to multimodal interaction. Each mode of this multimodal communication is an active research area. Multimodal human/military robot communication is the ultimate goal of this research.

A multimodal autonomous robot in military communication using speech, images, gestures, VST and VE has yet to be deployed. Autonomous multimodal communication is expected to open wider possibilities for all armed forces. Given the density of the land domain, the army is in a position to exploit the opportunities for human–machine teaming (HMT) exposure. Naval and air forces will adopt platform specific suites for specially selected operators to integrate with and leverage this emerging technology. The possession of a flexible communications means that readily adapts to virtual training will enhance planning and mission rehearsals tremendously.

Interaction, perception, cognition and visualization based multimodal communication system is yet missing. Options to communicate, express and convey information in HMT setting with multiple options, suggestions and recommendations will certainly enhance military communication, strength, engagement, security, cognition, perception as well as the ability to act confidently for a successful mission.

The objective is to develop a multimodal autonomous interactive robot for military communications. This survey reports the state of the art, what exists and what is missing, what can be done and possibilities of extension that support the military in maintaining effective communication using multimodalities. There are some separate ongoing progresses, such as in machine-enabled speech, image recognition, tracking, visualizations for situational awareness, and virtual environments. At this time, there is no integrated approach for multimodal human robot interaction that proposes a flexible and agile communication. The report briefly introduces the research proposal about multimodal interactive robot in military communication.

Siphon-based deadlock control in a flexible manufacturing system (FMS) suffers from the problems of computational and structural complexity since the number of siphons grows exponentially with respect to the size of its Petri net model. In order to reduce structural complexity of a supervisor, a set of elementary siphons derived from all strict minimal siphons (SMS) is explicitly controlled. The purpose of this paper is through fully investigating the structure of a class of generalized Petri nets, WS3PR, to compute all SMS and a compact set of elementary siphons.

Based on graph theory, the concepts of initial resource weighted digraphs and restricted subgraphs are proposed. Moreover, the concept of augmented siphons is proposed to extend the application of elementary siphons theory for WS3PR. Consequently, the set of elementary siphons obtained by the proposed method is more compact and well suits for WS3PR.

In order to demonstrate the proposed method, an FMS example is presented. All SMS and elementary siphons can be derived from initial resource weighted digraphs. Compared with those obtained by the method in Li and Zhou, the presented method is more effective to design a structural simple liveness-enforcing supervisor for WS3PR.

This work presents an effective method of computing SMS and elementary siphons for WS3PR. Monitors are added for the elementary siphons only, and the controllability of every dependent siphon is ensured by properly supervising its elementary ones. A same set of elementary siphons can be admitted by different WS3PR with isomorphic structures.