Unrestricted Environments Research Articles

HDN-Net: A Hybrid Deep Neural Network to Improve Iris Recognition in Unconstrained Environments with Eyeglasses

Recently, the use of iris recognition technology for biometric authentication has gained widespread acceptance due to the rich texture of the iris region, which provides a reliable standard for recognising individuals, as well as the non-intrusive nature of this method. However, the presence of eyeglasses poses a significant challenge to the accuracy of such systems. In unrestricted environments, current iris recognition techniques cannot effectively extract distinguishing features of the iris. Eyeglasses introduce scratches, specular reflections, dirt, blurriness, and other noise factors over the image of the iris, resulting in low recognition accuracy. To tackle this challenge, researchers have proposed the HDN-Net architecture. This architecture employs a multi-CNN model to combine the features of both the right and left iris images, extracting more distinguishing features to improve the accuracy of the classification task in the presence of challenges caused by eyeglasses. Experiment results show that the proposed iris recognition system achieves more promising performance compared to previous methods used in this field. The overall performance of our suggested HDN-Net method on the UBIRIS.V2 and CASIA-Iris.V4-1000 databases achieved 97.89% and 98.79% accuracy, respectively. Thus, the proposed HDN-Net method consistently outperforms other traditional and deep learning approaches and has the possibility to improve the accuracy of iris recognition systems (IRS) in real-world scenarios.

Low-cost, portable, easy-to-use kiosks to facilitate home-cage testing of nonhuman primates during vision-based behavioral tasks.

Nonhuman primates (NHPs), especially rhesus macaques, have significantly contributed to our understanding of the neural computations underlying human vision. Besides the established homologies in the visual brain areas between these species and our ability to probe detailed neural mechanisms in monkeys at multiple scales, NHPs' ability to perform human-like visual behavior makes them an extremely appealing animal model of human vision. Traditionally, such behavioral studies have been conducted in controlled laboratory settings, offering experimenters tight control over variables like luminance, eye movements, and auditory interference. However, in-lab experiments have several constraints, including limited experimental time, the need for dedicated human experimenters, additional lab space requirements, invasive surgeries for headpost implants, and extra time and training for chairing and head restraints. To overcome these limitations, we propose adopting home-cage behavioral training and testing of NHPs, enabling the administration of many vision-based behavioral tasks simultaneously across multiple monkeys with reduced human personnel requirements, no NHP head restraint, and monkeys' unrestricted access to experiments. In this article, we present a portable, low-cost, easy-to-use kiosk system developed to conduct home-cage vision-based behavioral tasks in NHPs. We provide details of its operation and build to enable more open-source development of this technology. Furthermore, we present validation results using behavioral measurements performed in the lab and in NHP home cages, demonstrating the system's reliability and potential to enhance the efficiency and flexibility of NHP behavioral research.NEW & NOTEWORTHY Training nonhuman primates (NHPs) for vision-based behavioral tasks in a laboratory setting is a time-consuming process and comes with many limitations. To overcome these challenges, we have developed an affordable, open-source, wireless, touchscreen training system that can be placed in the NHPs' housing environment. This system enables NHPs to work at their own pace. It provides a platform to implement continuous behavioral training protocols without major experimenter intervention and eliminates the need for other standard practices like NHP chair training, collar placement, and head restraints. Hence, these kiosks ultimately contribute to animal welfare and therefore better-quality neuroscience in the long run. In addition, NHPs quickly learn complex behavioral tasks using this system, making it a promising tool for wireless electrophysiological research in naturalistic, unrestricted environments to probe the relation between brain and behavior.

A solar-powered self-clean gas-sensing neural modulator for behavioral intervention with spatiotemporal flexibility

The amalgamation of high-sensitivity gas sensors with neural electrical stimulation technology stands as a compelling solution for eliciting behavioral responses in the presence of low-level hazardous gases. The utilization of battery-powered or coil-based configurations introduces spatiotemporal limitations, encompassing constrained experimental durations due to battery life or the necessity to confine subjects to specific locales for wireless power transmission. In this study, we present an advanced wireless neural modulator, meticulously engineered for behavioral intervention in unrestricted environments. This device integrates a solar-powered unit, gas sensor, brain stimulation signal management system, and a neurostimulation electrode. The solar energy utilization eliminates the necessity for battery replacements and local range limitations. The surface of the solar cells is treated with a superhydrophobic coating, enhancing performance in outdoor settings by mitigating surface contamination issues inherent in traditional solar cells. This innovation guarantees continuous, long-term, on-demand operational capacity, ensuring uninterrupted power supply to the system. Experimentation revealed shortened locomotor activity in mice, induced by stimulation of the periaqueductal gray (PAG) brain region, for up to thirty minutes. These results underscore the significant potential of our technology for spatially and temporally unrestricted neuromodulatory applications, offering a viable strategy to alleviate the detrimental effects of hazardous gas exposure on physiological functions.

A cross-sectional study of knowledge and practices related to sexual and reproductive health among adolescents in 'unrestricted environments' in Ghana: A policy implementation context view

Background: Sexual and reproductive health (SRH) is key to the growth and development of adolescents. Inadequate information exposes adolescents to some challenges. This becomes more pronounced as they move from restricted unrestricted environments such as pertains universities where there is virtually no control. It is importantto assess their knowledge of issues related to adolescent sexual and reproductive health (ASRH) needs and how that knowledge influences their sexual practices. Objective: To assess the knowledge and practice of adolescents in public universities across Ghana on their SRH needs. Study Participants: 672 adolescents from the three selected public institutions who met the inclusion criteria and consented to the study. Study Setting: The Study Setting was the University of Professional Studies Accra (UPSA); Kwame Nkrumah University of Science and Technology (KNUST), Kumasi; and the University for Development Studies (UDS) in Tamale, all in Ghana. Study Design: A cross-sectional study of adolescents in public universities across Ghana. Results: The study found that over 80% of university respondentshad high knowledge of ASRH issues. However, more than two-thirds (67%) of the respondents indicated that they had no knowledge that sexually transmitted infections (STIs) could be transmitted through unprotected sex. Regarding their sexual practices, the study found that 70% of the respondents were sexually active however, the prevalence of contraceptive use among them was extremely low (7%). Conclusion: A high level of knowledge on SRH issues among a large proportion of sexually active adolescents does not correspond to levels of practising safe sex making themsusceptible to STIsand unplanned pregnancies. Knowledge was thus disproportionally associated with safe sexual practices among adolescents in the unrestricted environments surveyed. Implementing behavioural change interventions through sexual education and improved access to ASRH services could improve the situation. These findings are thus relevant for SRH policy reforms and implementation programmes.

Unrestricted Face Recognition Algorithm Based on Improved Residual Network IR-ResNet-SE

<p>To solve the problem of poor face recognition performance in unrestricted environments. A face recognition algorithm based on improved residual IR-ResNet-SE is designed. Firstly, the IR structure is added to the 34-layer residual network to reduce the variability of different features; Secondly, we add the channel attention module to increase the weight of important channel features; Finally, the Arcface loss function is used to improve the classification ability of the model. The LFW, AgeDB, and AR datasets reflect unrestricted factors such as pose, age, expression, occlusion, and illumination. The algorithm proposed in this paper is experimented on these three datasets. The experimental results show that the IR-ResNet-SE algorithm proposed in this paper can achieve 99.74% accuracy in the dataset LFW. And it has excellent robustness in face recognition under unrestricted conditions.</p> <p> </p>

Anomaly Detection for Solder Joints Using β-VAE

In the assembly process of printed circuit boards (PCB), most of the errors are caused by solder joints in Surface Mount Devices (SMD). In the literature, traditional feature extraction based methods require designing hand-crafted features and rely on the tiered RGB illumination to detect solder joint errors, whereas the supervised Convolutional Neural Network (CNN) based approaches require a lot of labelled abnormal samples (defective solder joints) to achieve high accuracy. To solve the optical inspection problem in unrestricted environments with no special lighting and without the existence of error-free reference boards, we propose a new beta-Variational Autoencoders (beta-VAE) architecture for anomaly detection that can work on both IC and non-IC components. We show that the proposed model learns disentangled representation of data, leading to more independent features and improved latent space representations. We compare the activation and gradient-based representations that are used to characterize anomalies; and observe the effect of different beta parameters on accuracy and on untwining the feature representations in beta-VAE. Finally, we show that anomalies on solder joints can be detected with high accuracy via a model trained on directly normal samples without designated hardware or feature engineering.

Unrestricted Face Recognition Algorithm Based on Transfer Learning on Self-Pickup Cabinet

In the contactless delivery scenario, the self-pickup cabinet is an important terminal delivery device, and face recognition is one of the efficient ways to achieve contactless access express delivery. In order to effectively recognize face images under unrestricted environments, an unrestricted face recognition algorithm based on transfer learning is proposed in this study. First, the region extraction network of the faster RCNN algorithm is improved to improve the recognition speed of the algorithm. Then, the first transfer learning is applied between the large ImageNet dataset and the face image dataset under restricted conditions. The second transfer learning is applied between face image under restricted conditions and unrestricted face image datasets. Finally, the unrestricted face image is processed by the image enhancement algorithm to increase its similarity with the restricted face image, so that the second transfer learning can be carried out effectively. Experimental results show that the proposed algorithm has better recognition rate and recognition speed on the CASIA-WebFace dataset, FLW dataset, and MegaFace dataset.

Emergency Remote Teaching in Higher Education During Covid-19: Challenges and Opportunities

The third quarter of 2020 marks the closure of on-campus face-to-face pedagogies in South Africa’s institutions of higher learning due to Coronavirus disease (COVID-19). The need to maintain social distancing necessitated the transition to emergency remote teaching. A few institutions of higher learnings could move their classes effectively to online and distance education platforms because of their pre-existing experience and some grapple with managing the ‘new normal’. This article reflects on the challenges and opportunities of an emergency remote teaching in institutions of higher learnings during the COVID-19 pandemic. The article adopted a qualitative approach through relevant literature and policy reviews to critically analyse emergency remote teaching during the era of COVID-19. The findings indicate that some staff and students experience challenges related to the lack of resources and exposure to remotely use information and communication technology. The article acclaims that institutions of higher learnings should acquire suitable information and communication technology equipment and develop the requisite facilities, implement rules and regulations for their availability, and adequate maintenance. This recommends promoting technologically compliant ethics within the institution, provide easy access to teaching and learning by both students and academic staff at an affordable and fixed (secure) cost in safe, conducive, and unrestricted environments for students.

Image-Based Goat Breed Identification and Localization Using Deep Learning

In this paper an attempt has been made to identify six different goat breeds from pure breed goat images. The images of goat breeds have been captured from different organized registered goat farms in India, and almost two thousand digital images of individual goats were captured in restricted (to get similar image background) and unrestricted (natural) environments without imposing stress to animals. A pre-trained deep learning-based object detection model called Faster R-CNN has been fine-tuned by using transfer-learning on the acquired images for automatic classification and localization of goat breeds. This fine-tuned model is able to locate the goat (localize) and classify (identify) its breed in the image. The Pascal VOC object detection evaluation metrics have been used to evaluate this model. Finally, comparison has been made with prediction accuracies of different technologies used for different animal breed identification.

Synopsis of IEEE Std C95.1™-2019 “IEEE Standard for Safety Levels With Respect to Human Exposure to Electric, Magnetic, and Electromagnetic Fields, 0 Hz to 300 GHz”

The newly released IEEE Std C95.1™-2019 defines exposure criteria and associated limits for the protection of persons against established adverse health effects from exposures to electric, magnetic, and electromagnetic fields, in the frequency range 0 Hz to 300 GHz. The exposure limits apply to persons permitted in restricted environments and to the general public in unrestricted environments. These limits are not intended to apply to the exposure of patients by or under the direction of physicians and care professionals, as well as to the exposure of informed volunteers in scientific research studies, or to the use of medical devices or implants. IEEE Std C95.1™-2019 can be obtained at no cost from the IEEE Get Program https://ieeexplore.ieee.org/document/8859679.

Validation and Reliability of a Classification Method to Measure the Time Spent Performing Different Activities.

The aim of this study was to validate the performance and reliability of results obtained from a classification model that measures time spent performing activities in confined (CE) and unrestricted (UE) environments. In CE, participants wore a pair of biaxial and/or triaxial accelerometers while performing pre-determined training activities classified as variants of lying down, dynamic standing, sitting, walking and running on two separate days. A classification model trained with activities performed in a specific order during the first day was developed to validate the activities performed in a random order on the second day (CE) and over 24 hours on a separate day (UE). The performance of the classification model was validated against triaxial accelerometers using six (x, y and step counts for arm and thigh) or eight (same as six features plus z axis) features. The reliability of the classification model was tested in both environments using six features. Results revealed an overall accuracy of 94% in CE and 90% in UE. The sensitivity in CE and UE was 94% and 95% for lying down, 88% and 80% for dynamic standing, 97% and 89% for sitting, 96% and 78% for walking and 90% and 64% for running, respectively. No significant differences were noted between performances obtained with six or eight features. Results were highly reproducible in both environments. The results obtained from the classification model were accurate and reproducible, and highlight the potential use of this approach in research to quantify the time spent performing different activities.

Searching to maximize revenue in unrestricted and less-restricted competitive fare environments: Combining hybrid forecasting and fare adjustment with various unconstraining methods

In their competitive environment, airlines are always searching for ways to maximize revenues. This article considers both less-restricted and fully unrestricted fare environments. We use the sophisticated Passenger Origin–Destination Simulator (PODS) to examine the revenue impact of four implementations of hybrid forecasting (HF) and fare adjustment (FA) in combination with three different methods of unconstraining – Expectation Maximization (EM), Projection Detruncation (PD) and Booking Curve (BC). Owing to the competitive nature of PODS (two airlines competing head-to-head for customers) and its allowance for customer choice, we are able to assess all the implications of these HF and FA implementations in combination with unconstraining, including the impact of spill, upgrades and recapture. We find that in the less-restricted fare environment, under either EM or PD, the optimal combination is HF with FA equal to 0.5, and that under BC unconstraining the optimal combination is HF with FA equal to 1.0, independent of optimization technique (leg or network) or demand level (medium or high). For the unrestricted fare environment, we find that under leg optimization, generally it is best to use HF with FA equal to 0.5 combined with willingness-to-pay estimate curves of either Frat5c (EM/PD) or Frat5a (BC). Under network optimization, it is best to use HF with FA equal to 1.0, combined with WTP estimate curve Frat5c for all three unconstraining methods. When using realistic booking data from major global airlines to calibrate the PODS D6 network, we show that becoming more aggressive with HF and FA can lead to significant revenue gains of 1.6–5.8 per cent (less-restricted environment) or 3–15.9 per cent (fully unrestricted environment).

PROMETHEUS: heterogeneous sensor database in support of research on human behavioral patterns in unrestricted environments

The multi-modal multi-sensor PROMETHEUS database was created in support of research and development activities [PROMETHEUS (FP7-ICT-214901): http://www.prometheus-FP7.eu] aiming at the creation of a framework for monitoring and interpretation of human behaviors in unrestricted indoor and outdoor environments. The distinctiveness of the PROMETHEUS database comes from the unique sensor sets, used in the various recording scenarios, but also from the database design, which covers a range of real-world applications, correlated to smart-home automation and indoors/outdoors surveillance of public areas. Numerous single-person and multi-person scenarios, but also scenarios with interactions between groups of people, motivated by these applications were implemented with the help of skilled actors and supernumerary personnel. In these scenarios, the actors and personnel were instructed to implement a range of typical and atypical behaviors, and simulations of emergency and crisis situations. In summary, the database contains more than 4 h of synchronized recordings from heterogeneous sensors (an infrared motion detection sensor, thermal imaging cameras, overview/surveillance video cameras, close-view video cameras, a 3D camera, a stereoscopic camera, a general-purpose camcoder, microphone arrays, and motion capture equipment) collected in common setups, simulating smart-home environment, airport, and ATM security environment. Selected scenes of the database were annotated for the needs of human detection and tracking. The entire audio part of the database was annotated for the needs of sound event detection, sound source enumeration, emotion recognition, etc.

Heuristic algorithm for visual tracking of deformable objects

Many vision problems require fast and accurate tracking of objects in dynamic scenes. These problems can be formulated as exploration problems and thus can be expressed as a search into a state space based approach. However, these problems are hard to solve because they involve search through a space of transformations corresponding to all the possible motion and deformation. In this paper, we propose a heuristic algorithm through the space of transformations for computing target 2D motion. Three features are combined in order to compute efficient motion: (1) a quality of function match based on a holistic similarity measurement, (2) Kullback–Leibler measure as heuristic to guide the search process and (3) incorporation of target dynamics into the search process for computing the most promising search alternatives. Once 2D motion has been calculated, the result value of the quality of function match computed is used with the purpose of verifying template updates. A template will be updated only when the target object has evolved to a transformed shape dissimilar with respect to the actual shape. Also, a short-term memory subsystem is included with the purpose of recovering previous views of the target object. The paper includes experimental evaluations with video streams that illustrate the efficiency and suitability for real-time vision based tasks in unrestricted environments.

A WALKING GUIDANCE SYSTEM FOR THE VISUALLY IMPAIRED

In this paper, we present a walking guidance system for the visually impaired pedestrians. The system has been designed to help the visually impaired by responding intelligently to various situations that can occur in unrestricted natural outdoor environments when walking and finding the destinations. It involves the main functions of people detection, text recognition, face recognition. In addition, added sophisticated functions of walking path guidance using Differential Global Positioning System, obstacle detection using a stereo camera and voice user, interface are included. In order to operate all functions concurrently, we develop approaches in real situations and integrate them. Finally, we experiment on a prototype system under natural environments in order to verify our approaches. The results show that our approaches are applicable to real situations.

Models and motion planning

We study the complexity of the motion planning problem for a bounded-reach robot in the situation where the n obstacles in its workspace satisfy two of the realistic models proposed in the literature, namely unclutteredness and small simple-cover complexity. We show that the maximum complexity of the free space of a robot with f degrees of freedom in the plane is Θ( n f/2 + n) for uncluttered environments as well as environments with small simple-cover complexity. The maximum complexity of the free space of a robot moving in a three-dimensional uncluttered environment is Θ( n 2 f/3 + n). All these bounds fit nicely between the Θ( n) bound for the maximum free-space complexity for low-density environments and the Θ( n f ) bound for unrestricted environments. Surprisingly—because contrary to the situation in the plane—the maximum free-space complexity is Θ( n f ) for a three-dimensional environment with small simple-cover complexity.

National security and scientific communication.

Is science facing a new environment triggered by the alleged successful espionage by foreign parties, in particular China, aimed at the nation's nuclear weapons secrets? Several much publicized reports, in particular that of the Cox Commission of the Congress†, the Rudman report by the President's Foreign Intelligence Advisory Board, and the review of the findings of the intelligence community, have alleged security deficiencies within the U.S. defense establishment and in particular U.S. nuclear weapons laboratories. None of these reports have claimed that the presence of foreigners at U.S. academic research institutes or universities has in any way been involved in the alleged security breeches. Yet, remedial measures instituted by the U.S. government are far ranging and affect not only weapons-related activities but the U.S. scientific establishment in general. National security has many aspects, including economic strength, the morale and well-being of the people, as well as military prowess. In respect to the latter, some emphasize restrictions aimed at preventing information developed in the past from reaching unfriendly nations or parties. But then there are those, this author included, who conclude that national security in the past has been predominantly advanced by achievements in a free environment and that such achievements are endangered if undue security measures by restrictions are allowed to dominate. Both are needed, but to use the phrase coined by journalist Alan Barth, the “utility of freedom” is essential in advancing national security. During the “hot” and “cold” wars the spectacular achievements of United States science and technology were accomplished in unusually unrestricted environments. Mistakes and false starts were made but, just because the open nature of such errors drew criticism, corrections were readily taken. U.S. openness compared favorably with that of the United States' opponent nations, in particular the …

The evolution of aging: a new approach to an old problem of biology

Most gerontologists believe aging did not evolve, is accidental, and is unrelated to development. The opposite viewpoint is most likely correct. Genetic drift occurs in finite populations and leads to homozygosity in multiple-alleled traits. Episodic selection events will alter random drift towards homozygosity in alleles that increase fitness with respect to the selection event. Aging increases population turnover, which accelerates the benefit of genetic drift. This advantage of aging led to the evolution of aging systems (ASs). Periodic predation was the most prevalent episodic selection pressure in evolution. Effective defenses to predation that allow exceptionally long lifespans to evolve are shells, extreme intelligence, isolation, and flight. Without episodic predation, aging provides no advantage and aging systems will be deactivated to increase reproductive potential in unrestricted environments. The periodic advantage of aging led to the periodic evolution of aging systems. Newer aging systems co-opted and added to prior aging systems. Aging organisms should have one dominant, aging system that co-opts vestiges of earlier-evolved systems as well as vestiges of prior systems. In human evolution, aging systems chronologically emerged as follows: telomere shortening, mitochondrial aging, mutation accumulation, senescent gene expression (AS#4), targeted somatic tissue apoptotic-atrophy (AS#5), and female reproductive tissue apoptotic-atrophy (AS#6). During famine or drought, to avoid extinction, reproduction is curtailed and aging is slowed or somewhat reversed to postpone or reverse reproductive senescence. AS#4-AS#6 are gradual and reversible aging systems. The life-extending/rejuvenating effects of caloric restriction support the idea of aging reversibility. Development and aging are timed by the gradual loss of cytosine methylation in the genome. Methylated cytosines (5mC) inhibit gene transcription, and deoxyribonucleic acid (DNA) cleavage by restriction enzymes. Cleavage inhibition prevents apoptosis, which requires DNA fragmentation. Free radicals catalyze the demethylation of 5mC while antioxidants catalyze the remethylation of cytosine by altering the activity of DNA methyltransferases. Hormones act as either surrogate free radicals by stimulating the cyclic adenosine monophosphate (cAMP) pathway or as surrogate antioxidants through cyclic guanosine monophosphate (cGMP) pathway stimulation. Access to DNA containing 5mC inhibited developmental and aging genes and restriction sites is allowed by DNA helicase strand separation. Tightly wound DNA does not allow this access. The DNA helicase generates free radicals during strand separation; hormones either amplify or counteract this effect. Caloric restriction slows or reverses the aging process by increasing melatonin levels, which suppresses reproductive and free radical hormones, while increasing antioxidant hormone levels. Cell apoptosis during CR leads to somatic wasting and a release of DNA, which increases bioavailable cGMP. The rapid aging diseases of progeria, the three diseases: (xeroderma pigmentosum (XP), Cockayne syndrome(CS), and ataxia telangiectasia (AT)), and Werner's syndrome are related to or caused by defects in three separate DNA helicases. The rapid aging diseases caused by mitochondrial malfunctions mirror those seen in XP, CS, and AT. Comparing these diseases allows for assignment of the different symptoms of aging to their respective aging systems. Follicle-stimulating hormone (FSH) demethylates the genes of AS#4, luteinizing hormone (LH) of AS#5, and estrogen of AS#6 while cortisol may act cooperatively with FSH and LH, and 5-alpha dihydrotestosterone (DHT) with FSH in these role. The Werner's DNA helicase links timing of the age of puberty, menopause, and maximum lifespan in one mechanism. Telomerase is under hormonal control. Most cancers likely result from malfunctions in the programmed apoptosis of AS#5 and AS#6. The Hayflick limit is reached primarily through loss of cytosine methylation of genes that inhibit replication. Men suffer the diseases of AS#4 at a higher rate than women who suffer from AS#5 more often. Adult mammal cloning suggests aging-related cellular demethylation, and thus aging, is reversible. This theory suggests that the protective effect of smoking and ibuprofen for Alzheimer's disease is caused through LH suppression.

Carving: a novel method of visibility preprocess- ing for un-restricted three-dimensional environments

, for visibility preprocessing of unrestricted (nonaxial) models. It is different from visibility preprocessing applied directly to nonaxial data. As a sculptor carves a statue, carving splits the nonaxial portion of a model, and results in a model with only axial polygons and a set of cuttings. The visibility information of the carved axial model can then be computed with the cuttings as detail objects.

Dog training, reinforcement, and behavior in unrestricted environments.

Dog training, reinforcement, and behavior in unrestricted environments.