The Role of Eye Gaze in Security and Privacy Applications: Survey and Future HCI Research Directions

For the past 20 years, researchers have investigated the use of eye tracking in security applications. We present a holistic view on gaze-based security applications. In particular, we canvassed the literature and classify the utility of gaze in security applications into a) authentication, b) privacy protection, and c) gaze monitoring during security critical tasks. This allows us to chart several research directions, most importantly 1) conducting field studies of implicit and explicit gaze-based authentication due to recent advances in eye tracking, 2) research on gaze-based privacy protection and gaze monitoring in security critical tasks which are under-investigated yet very promising areas, and 3) understanding the privacy implications of pervasive eye tracking. We discuss the most promising opportunities and most pressing challenges of eye tracking for security that will shape research in gaze-based security applications for the next decade

Adaptive Hiding Algorithm Based on Mapping Database

Information hiding one of the important field of security which provide secure level for the information. Achieving multi levels of security system often researchers used cryptography side by side with steganography. Utilizing message digest algorithm to play the role of crypto which is extracted from secret created database. Message digest algorithm (MD5) used two times as one-way function to provide data integrity. The implemented system evaluated based on peak signal to noise ratio (PSNR) metric and the best value reaches 62.46. the proposed system works in adaptive behavior due to the different use of images as well as the selected point could be used to generate the hash code as well. The implemented system reaches up to sufficient level of security through using both steganography and cryptography

Human Gender and Age Detection Based on Attributes of Face

The main target of the work in this paper is to detect the gender and oldness of a person with an accurate decision and efficient time based on the number of facial outward attributes extracted using Linear-Discriminate Analysis to classify a person within a certain category according to his(her) gender and age. This work was deal with color facial images via the Iterative Dichotomiser3 algorithm as a classifier to detect the oldness of a person after gender detected. This paper used the Face-Gesture-Recognition-Research-Network aging dataset. All facial images in the dataset were categorizing into binary categories using k-means. This is followed by the process of dividing all samples according to age classes that belonging to each specific sex category. Thus, this division process enabled us to reach a quick and accurate decision.  The results showed that the accuracy of the proposal was 90.93%,  and F-measure was 89.4

Identification Based on Iris Detection Technique

Iris-biometrics are an alternative way of authenticating and identifying a person because biometric identifiers are unique to people. This paper introduces a method aims to efficient human identification by enhanced iris detection method within acceptable time. After preparing various type of images, then perform a series of pre-processing steps and standardize them, after that use Uni-Net learning, so identify the human by Navie-Bays method is the last step based on the output of Uni-Net which is role as feature extractor for the iris part and another sub-net for non-iris part that may involve identification-outcome. The outcome of this method looked good compared to some high-level methods, so, was accuracy-rate 9855, 99.25, and 99.81 for CASIA-v4, ITT-Delhi, and MMU-database respectively. Also, this paper introduces a method of iris recognition using CNN model which is improved the preprocessed patterns that together from dataset applied some procedures to develop them based on techniques of equalization and acclimate contrast ones. After that characteristic extracted and classified using CNN that comprises of 10 layers with back-propagation schema and adjusted moment evaluation Adam-optimizer for modernize weights. The overall accuracy was 95.31% with utilization time 17.58 (mints) for training-model

Anomaly Detection from Crowded Video by Convolutional Neural Network and Descriptors Algorithm: Survey

Depending on the context of interest, an anomaly is defined differently. In the case when a video event isn't expected to take place in the video, it is seen as anomaly. It can be difficult to describe uncommon events in complicated scenes, but this problem is frequently resolved by using high-dimensional features as well as descriptors. There is a difficulty in creating reliable model to be trained with these descriptors because it needs a huge number of training samples and is computationally complex. Spatiotemporal changes or trajectories are typically represented by features that are extracted. The presented work presents numerous investigations to address the issue of abnormal video detection from crowded video and its methodology. Through the use of low-level features, like global features, local features, and feature features. For the most accurate detection and identification of anomalous behavior in videos, and attempting to compare the various techniques, this work uses a more crowded and difficult dataset and require light weight for diagnosing anomalies in objects through recording and tracking movements as well as extracting features; thus, these features should be strong and differentiate objects. After reviewing previous works, this work noticed that there is more need for accuracy in video modeling and decreased time, and since attempted to work on real-time and outdoor scenes

Localization of Strangeness for Real Time Video in Crowd Activity Using Optical Flow and Entropy

Anomaly detection, which is also referred to as novelty detection or outlier detection, is process of identifying unusual occurrences, observations, or events which considerably differ from the bulk of data and do not fit a predetermined definition of typical behavior. Medicine, cybersecurity, statistics, machine vision, law enforcement, neurology, and financial fraud are just a handful of the industries where anomaly detection is used. In the presented study, an online tool is utilized to identify crowd distortions, which could be brought on by panic. An activity map is produced with the use of numerous frames to show the continuity regarding the flow over time following the global optical flow has been calculated in the quickest time and with the highest precision possible utilizing the Farneback approach to calculate the magnitudes. Utilizing a specific threshold, the oddity in the video will be picked up by the activity map's generation of an entropy. The results indicate that the maximum entropy level for indoor video is <0.16 and the maximum entropy level for outdoor video is >0.45. A threshold of 0.04 is used to determine whether a frame is abnormal or normal

Global economic burden of unmet surgical need for appendicitis

Background There is a substantial gap in provision of adequate surgical care in many low- and middle-income countries. This study aimed to identify the economic burden of unmet surgical need for the common condition of appendicitis. Methods Data on the incidence of appendicitis from 170 countries and two different approaches were used to estimate numbers of patients who do not receive surgery: as a fixed proportion of the total unmet surgical need per country (approach 1); and based on country income status (approach 2). Indirect costs with current levels of access and local quality, and those if quality were at the standards of high-income countries, were estimated. A human capital approach was applied, focusing on the economic burden resulting from premature death and absenteeism. Results Excess mortality was 4185 per 100 000 cases of appendicitis using approach 1 and 3448 per 100 000 using approach 2. The economic burden of continuing current levels of access and local quality was US $92 492 million using approach 1 and$73 141 million using approach 2. The economic burden of not providing surgical care to the standards of high-income countries was $95 004 million using approach 1 and$75 666 million using approach 2. The largest share of these costs resulted from premature death (97.7 per cent) and lack of access (97.0 per cent) in contrast to lack of quality. Conclusion For a comparatively non-complex emergency condition such as appendicitis, increasing access to care should be prioritized. Although improving quality of care should not be neglected, increasing provision of care at current standards could reduce societal costs substantially

Cohort profile: the ESC EURObservational Research Programme Non-ST-segment elevation myocardial infraction (NSTEMI) Registry

Aims The European Society of Cardiology (ESC) EURObservational Research Programme (EORP) Non-ST-segment elevation myocardial infarction (NSTEMI) Registry aims to identify international patterns in NSTEMI management in clinical practice and outcomes against the 2015 ESC Guidelines for the management of acute coronary syndromes in patients presenting without ST-segment-elevation. Methods and results Consecutively hospitalised adult NSTEMI patients (n = 3620) were enrolled between 11 March 2019 and 6 March 2021, and individual patient data prospectively collected at 287 centres in 59 participating countries during a two-week enrolment period per centre. The registry collected data relating to baseline characteristics, major outcomes (inhospital death, acute heart failure, cardiogenic shock, bleeding, stroke/transient ischaemic attack, and 30-day mortality) and guideline-recommended NSTEMI care interventions: electrocardiogram pre- or in-hospital, prehospitalization receipt of aspirin, echocardiography, coronary angiography, referral to cardiac rehabilitation, smoking cessation advice, dietary advice, and prescription on discharge of aspirin, P2Y12 inhibition, angiotensin converting enzyme inhibitor (ACEi)/angiotensin receptor blocker (ARB), beta-blocker, and statin. Conclusion The EORP NSTEMI Registry is an international, prospective registry of care and outcomes of patients treated for NSTEMI, which will provide unique insights into the contemporary management of hospitalised NSTEMI patients, compliance with ESC 2015 NSTEMI Guidelines, and identify potential barriers to optimal management of this common clinical presentation associated with significant morbidity and mortality