Iris System Research Articles

Results of application of the IRIS dental implants with the surface modified by the method of plasma electrolytic oxidation

Surface modifications of dental implants to provide optimal conditions for osseointegration remains an urgent task in modern dental implantology. A few publications demonstrate that the surface of the dental implants modified by plasma electrolytic oxidation (PEO) possess a combination of several important features that promote osteointegration: optimal micro roughness within 1-7 microns, high chemical purity, and mechanical strength [8,20].The aim. To evaluate the clinical efficacy of IRIS implants with a new surface modified by the PEO method (hereinafter referred to as IRIS PEO).Materials and methods. Based on the Patrice Lumumba RUDN Medical Center and the Center of Medical Care for Dental Diseases, FGBU «Central Clinical Hospital with Polyclinic» of the Presidential Affairs Department of the Russian Federation, 60 patients aged 27 to 52 years with partial tooth loss were examined and treated. The patients received 1 IRIS-PEO implant each on the upper or lower jaw. All implants were placed with the force from 35 to 50 N/cm2, with gingiva shapers. Prosthetics were performed after 2 months on the lower jaw and after 4 months on the upper jaw. Before taking impressions, the stability of implants was measured using the Penguin RFA (Integration Diagnostic Sweden AB, Sweden). One year after prosthetics, the neck resorption of the implants was evaluated.Results. Because of the treatment, all prosthetic constructions met the functional and aesthetic requirements. The stability indices of implants in ISQ units on the upper jaw averaged 75±3.4, on the lower jaw 79±2.4. Bone resorption in the implants’ neck area 1 year after the end of the treatment was not observed. The pilot clinical study of the IRIS-PEO implants allowed to optimize the terms of rehabilitation and to obtain high functional and esthetic result in the treatment of patients with tooth loss.Conclusions. Pilot clinical implementation of the implants of the IRIS system with the surface modified by plasma electrolytic oxidation demonstrated the possibility of open management of the implants with the gingiva shaper, to carry out prosthetics in 2 months on the lower jaw and 4 months on the upper jaw. No neck resorption was observed one year after prosthetics.

Design and Implementation of Novel Hybrid and Multiscale- Assisted CNN and ResNet Using Heuristic Advancement of Adaptive Deep Segmentation for Iris Recognition

Due to its significant applications in security, the iris recognition process has been considered as the most active research area over the last few decades. In general, the iris recognition framework has been crucially utilized for various security applications because it includes a set of features as well as does not alter its character according to the time. In recent times, emerging deep learning techniques have attained huge success, particularly in the field of the iris recognition framework model. Moreover, in considering the field of iris recognition, there is no possibility for the remarkable capability of the deep learning model as well as to attain superior performance. To handle the issues in the conventional model of iris recognition, a novel heuristic-aided deep learning framework has been implemented for recognizing the iris system. Initially, the required source iris images are gathered from the data sources. It is then followed by the pre-processing stage, where the pre-processed image is obtained. Consequently, the image segmentation process is carried out by Adaptive Deeplabv3+layers, in which the parameters are optimized using the Modified Weighted Flow Direction Algorithm (MWFDA). Finally, the iris recognition is accomplished by hybrid Hybridization of Multiscale Dilated-Assisted Learning (MDAL) that will be composed of both a Convolutional Neural Network (CNN) and a Residual Network (ResNet). To achieve optimal recognition results, the parameters in CNN and ResNet are tuned optimally by using MWFDA. The experimental results are estimated with the help of distinct measures. Contrary to conventional methods, the empirical results prove that the recommended model achieves the desired value to enhance the recognition performance.

Simulation research on breakdown diagnosis based on least squares support vector machine optimized by simulated annealing genetic algorithm

The application of support vector machine to the aircraft power supply system breakdown diagnosis is one of the research focuses in the tomorrow. Support vector machine (SVM) belongs a new type of machine learning technique, which uses structural hazard minimization rule to substitute for the conventional empirical hazard minimization according to great specimen. The powerful performance of the least squares support vector machine (LSSVM) needs to be reflected in the optimal selection of appropriate parameters, and the quality of parameters greatly affects the accuracy and efficiency of breakdown diagnosis. The traditional LSSVM parameters selection method is inefficient, the calculation is huge, and it takes expensive time to select the satisfactory solution. Aiming at the problem of parameters selection of LSSVM, the way of optimizing the parameters of LSSVM by apply simulated annealing genetic algorithm (SAGA) is proposed. SAGA uses the parallel sampling process of genetic algorithm to improve the time performance of optimization, and makes use of the simulated annealing algorithm to dominate the constriction of majorization to prevent precocity. On the one hand, genetic algorithm has strong ability to grasp the overall search process, on the other hand, simulated annealing algorithm is used to control the convergence of the algorithm to prevent premature phenomenon. The automatic optimal selection of LSSVM parameters is achieved. The Iris system classification and recognition in the UCI machine learning database and the breakdown diagnosis of the autopilot flight control box are used as experimental platforms to obtain data samples for simulation research. The simulation results show that LSSVM optimized by SAGA improves both the accuracy and efficiency of classification recognition. It not only effectively overcomes the problem of low efficiency caused by searching optimal parameters by experience, but also effectively improves the accuracy of classification recognition. The false alarm rate and redundant breakdowns are effectively reduced.

Imaging Capabilities of the IRIS and IRIS XL-260 PET/CT Systems for High-Throughput Imaging: A Quantification Cross-Validation Study

The concept of imaging several subjects simultaneously is an active preclinical research topic. In the present paper, we assessed the imaging capabilities of two PET/CT systems based on similar detector technology. The IRIS system is a mice/rat imaging system arranged in two rings of eight detectors each, the more recent IRIS XL 260, dedicated to Non-Human Primate (NHP) imaging has a single ring of sixteen detectors. Both systems were equipped with standard animal cells (Minerve) and 3-mice adapters. Our objective is to study which of these systems could be more appropriate to perform quantitative high-throughput imaging on mice. Phantoms and 18FFDG tumor-bearing mice acquisitions have been conducted in single and high-throughput modes using both the IRIS (up to 3 mice) and the IRIS XL-260 PET/CT (up to 6 mice) systems. Image Quality Phantom results obtained in high-throughput mode show some slight degradation of the recovery coefficient for rods of 1, 2 and 3 mm in diameter compared to the single-mode results, as one would normally expect. Similarly, we observed a decrease in image uniformity between the single-and the high-throughput modes for both the IRIS PET and the IRIS XL-260 PET systems. We performed 18FFDG tumor-bearing mice PET acquisitions with both systems. In order to estimate the quantification differences in all the studied configurations, we calculate the ratios between the %ID/g values extracted from the PET images and the ex-vivo values. In single mode acquisitions, ratios of 0.94 ± 0.09 and 0.83 ± 0.08 were obtained for the IRIS and the IRIS XL-260 PET systems, respectively. In high-throughput mode, ratios of 0.78 ± 0.12 and 0.73 ± 0.13 were obtained for the IRIS and the IRIS XL-260 PET systems, respectively. The difference in %ID/g between static acquisitions and ex-vivo value is not statistically significant (p-value > 0.1) for both PET systems in single mode, as well as for the IRIS system in high-throughput mode. We noted a slightly higher statistical difference between static acquisitions and ex-vivo values for the IRIS XL-260 system with a p-value of 0.015. Phantoms and in-vivo studies have made it possible to highlight the capability of the two systems to perform high-throughput acquisitions. Our results suggest that the IRIS system configuration may be the most suitable when aiming for quantitative high-throughput mice imaging. The large transverse field of view of the IRIS XL-260 makes it possible to image a greater number of mice simultaneously, which may be useful in specific cases, such as studies using an expensive radiotracer and/or with a short half-life. However, the IRIS PET/CT offers a full axial coverage of the animals and a higher sensitivity.

Ocular microvasculature in adult Xenopus laevis: Scanning electron microscopy of vascular casts.

The microvascular anatomy of choriocapillaris, iris, ciliary body and superficial vascular hyaloid system of eyes was studied in the permanent aquatic Xenopus laevis by scanning electron microscopy of vascular casts and was compared with that published in two semi-aquatic ranid species (Rana esculenta, Rana temporaria), and the urodelian species Triturus criststus carnifex. Results showed that the choriocapillaris in Xenopus consisted of a dense meshwork of wide capillaries displaying polygonal arrays at the scleral side with venules leaving the centers and arterioles supplied from the periphery. The choriocapillaris lacked the multilayered capillary meshwork described in ranids. Iris and ciliary body were supplied by nasal and temporal branches of the iridial artery, which either originated with a common stem from the hyaloid artery or arose as individual vessels from the proximal portions of the semicircular nasal and temporal branches of the hyaloid artery. These branches ran in the pupillary margin and supplied the two-dimensional capillary network of the iris, as well as the three-dimensional network of the ciliary body. Iris and ciliary body drained via parallel running vasa recta into the choriocapillaris. The superficial vascular hyaloid bed (system) was supplied by the hyaloid artery. This artery coursed along the scleral surface of the ventro-temporal choriocapillaris towards the ora serrata, where it bifurcated into a temporal and a nasal semicircular branch. Seven to ten arterial meridional twigs arose from these branches and supplied the superficial hyaloid capillary bed. Capillaries drained into branches of the hyaloid vein, which ascended towards the ora serrata, where the hyaloid vein joined the temporal branch of the ciliary vein. This article is protected by copyright. All rights reserved.

Dual-Factor WBAN Enhanced Authentication System Based on Iris and ECG Descriptors

At present, COVID-19 is still spreading and affecting millions of people worldwide. Minimizing the need for travel can significantly reduce the probability of infection and improve patients’ quality of life. The wireless body area network (WBAN) transmits the patients’ physiological data to the doctor remotely through the sensors in a way that minimizes physical contact with others. However, existing WBAN security authentication schemes have a core limitation that includes weak authentication performance and overconsumption of resources that precludes their widespread adoption in practical applications. Therefore, in this article, an enhanced dual-factor authentication system that addresses the mentioned drawbacks is proposed for securing WBAN resources. By combining iris and electrocardiogram (ECG) features, users would be required to pass the first-level iris authentication before performing the second-level ECG authentication, thus enhancing the overall security scheme of a WBAN system. Furthermore, we examined the existing inter-pulse-interval (IPI) encoding methods and propose a more efficient ECG IPI encoding algorithm, which can effectively shorten the encoding time without affecting the overall encoding performance. Finally, extensive experiments were performed to verify the performance of the proposed dual-factor iris and ECG-based WBAN authentication system using public iris and ECG databases. The experimental results show that the false acceptance rate (FAR) is close to 0.0%, and the false rejection rate (FRR) is close to 3.2%. Findings from this study suggest that the proposed dual-factor authentication scheme could aid the adequate deployment of security schemes to protect WBAN resources in practical applications.

Evaluating the Use of Action Templates to Create Suspense in Narrative Planning

The IRIS story generation system is a narrative planner that is designed to create suspenseful stories at the story-action level. It uses a set of action templates that are injected into the planning process to create suspense around a given goal. The action templates were evaluated independent of the rest of the IRIS system against a series of other techniques designed to create suspense. Results show that it is possible to use these set of action templates to create localized moments of suspense in a story at the story-action level without the need for discourse-level suspense.

A Modified Chaotic Binary Particle Swarm Optimization Scheme and Its Application in Face-Iris Multimodal Biometric Identification

In order to improve the recognition rate of the biometric identification system, the features of each unimodal biometric are often combined in a certain way. However, there are some mutually exclusive redundant features in those combined features, which will degrade the identification performance. To solve this problem, this paper proposes a novel multimodal biometric identification system for face-iris recognition.It is based on binary particle swarm optimization. The face features are extracted by 2D Log-Gabor and Curvelet transform, while iris features are extracted by Curvelet transform. In order to reduce the complexity of the feature-level fusion, we propose a modified chaotic binary particle swarm optimization (MCBPSO) algorithm to select features. It uses kernel extreme learning machine (KELM) as a fitness function and chaotic binary sequences to initialize particle swarms. After the global optimal position (Gbest) is generated in each iteration, the position of Gbest is varied by using chaotic binary sequences, which is useful to realize chaotic local search and avoid falling into the local optimal position. The experiments are conducted on CASIA multimodal iris and face dataset from Chinese Academy of Sciences.The experimental results demonstrate that the proposed system can not only reduce the number of features to one tenth of its original size, but also improve the recognition rate up to 99.78%. Compared with the unimodal iris and face system, the recognition rate of the proposed system are improved by 11.56% and 2% respectively. The experimental results reveal its performance in the verification mode compared with the existing state-of-the-art systems. The proposed system is satisfactory in addressing face-iris multimodal biometric identification.

Enhancement in iris recognition system using FPGA

The growth of using the iris recognition over the globe for identification and for verification and the problem that faces the iris recognition from noise like eyelash and eyelid. This paper focus on choosing the right pattern to collect the traits. The algorithm of this paper is searching and working on different rectangle iris template to spotting the ultimate traits that lies within rectangle iris templates. The Ridge Energy Direction (RED) is used as algorithm to spot the features that lies within the template. The overall iris system is design, implemented and tested on the Field Programmable gate Area (FPGA).

Malignant spiradenoma in a patient with Recklinghausen syndrome: a potential association

Recklinghausen syndrome or neurofibromatosis type 1(NF1) is a hereditary condition transmitted with a dominant autosomal inheritance pattern. It’s a systemic disorder characterized by involvements of skin, nerves, bone, soft tissues, iris and nervous system. Specifically a mutation of one allele of the oncosoppressor gene NF1 is the cause of the syndrome. Manifestations of neurofibromatosis include: benign tumors like neurofibromas, pheocromocytoma, juvenile xanthogranulomas, Lisch nodules, cafe-au-lait macules and freckles. Neurofibromatosis also correlates with an increased risk for malignant tumors like malignant melanoma, leukemia, brain gliomas. In this manuscript we report the association of NF1 with a malignant spiradenoma. A literature review has been made to investigate a possible correlation between these two entities.

Feature Extraction of Iris and Palmprint Biometric System using Dwt

Much work is done on Iris Recognition, since few years. Many cases discussed about performance in view of image capturing and recognition. Daugman work is the most important related to iris biometric in early research. It is fair to say, it is base model for iris biometric. Almost the available iris systems are based on this work. A palm print is image of the palm area of a hand. It is either an image taken online or offline. It is one of the most familiar and promising biometric model for personal identity verification. It is tough task to differentiate lines and wrinkles without explicit definition. depends on the thickness and position of some key points we can define principal lines. In our work, we are taken the principal line magnitude is less than or equal to 1. we cannot consider broken lines. If it is the case broken point is treat as last point.

Depth Camera Using High-Transmittance Off-Axis Dual Electro-Optical Irises

A depth camera prototype with high-transmittance off-axis dual electro-optical (DEO) irises is proposed. Our DEO irises are switchable through the polymer dispersed liquid crystal, and exhibit the advantages of low cost, easy fabrication, and higher transmittance compared to the traditional liquid crystal shutters. The transmittance of our device is near 75% when the driving voltage reaches about 30 V. The principle of depth measurement of our system is based on a pair of stereo images, which are captured through the left and right irises, respectively. The depth is calculated from the shifts of features between the two images. The DEO iris design, fabrication process, and depth camera prototype are demonstrated, and experimental results using our depth camera verify reliable performance for the depth measurement. Our DEO iris system therefore provides potential applications in depth sensing.

Iris: Deep Reinforcement Learning Driven Shared Spectrum Access Architecture for Indoor Neutral-Host Small Cells

We consider indoor mobile access, a vital use case for current and future mobile networks. For this key use case, we outline a vision that combines a neutral-host based shared small-cell infrastructure with a common pool of spectrum for dynamic sharing as a way forward to proliferate indoor small-cell deployments and open up the mobile operator ecosystem. Towards this vision, we focus on the challenges pertaining to managing access to shared spectrum (e.g., 3.5GHz US CBRS spectrum). We propose Iris, a practical shared spectrum access architecture for indoor neutral-host small-cells. At the core of Iris is a deep reinforcement learning based dynamic pricing mechanism that efficiently mediates access to shared spectrum for diverse operators in a way that provides incentives for operators and the neutral-host alike. We then present the Iris system architecture that embeds this dynamic pricing mechanism alongside cloud-RAN and RAN slicing design principles in a practical neutral-host design tailored for the indoor small-cell environment. Using a prototype implementation of the Iris system, we present extensive experimental evaluation results that not only offer insight into the Iris dynamic pricing process and its superiority over alternative approaches but also demonstrate its deployment feasibility.

Oral Manifestation of Neurofibromatosis Type I: a Case Report

Neurofibromatosis is a hereditary condition with at least 8 identified forms; neurofibromatosis type I is the most common. The type I form is characterized by multiple café-au-lait spots and cutaneous neurofibromas, freckles in the axillary and inguinal regions, a brownish spot on the iris, skeletal dysplasias, benign and malignant nervous system tumor growth, and usually a first-degree relative with the same condition. A 35-year-old woman presented with café-au-lait spots and multiple cutaneous neurofibromas, with the oral manifestation as nodules in the palate, alveolar ridge, buccal mucosa, and tongue. A panoramic radiography analysis did not show any change. The histological evaluation of an incisional biopsy of the palate lesion was compatible with the neurofibromatosis diagnosis. Due to difficulty in swallowing caused by the palate lesion, it was surgically removed and a histological evaluation confirmed the diagnosis. The patient continues to be under follow-up with the oral medicine team.

IRIS

In this work, we present the first scalable distributed information system, that is, a system with low storage overhead, that is provably robust against denial-of-service (DoS) attacks by a current insider. We allow a current insider to have complete knowledge about the information system and to have the power to block any ε-fraction of its servers by a DoS attack, where ε can be chosen up to a constant. The task of the system is to serve any collection of lookup requests with at most one per nonblocked server in an efficient way despite this attack. Previously, scalable solutions were only known for DoS attacks of past insiders, where a past insider only has complete knowledge about some past time point t 0 of the information system. Scheideler et al. [Awerbuch and Scheideler 2007; Baumgart et al. 2009] showed that in this case, it is possible to design an information system so that any information that was inserted or last updated after t 0 is safe against a DoS attack. But their constructions would not work at all for a current insider. The key idea behind our IRIS system is to make extensive use of coding. More precisely, we present two alternative distributed coding strategies with an at most logarithmic storage overhead that can handle up to a constant fraction of blocked servers.

SU‐E‐T‐366: Estimation of Whole Body Dose From Cranial Irradiation From C and Perfexion Series Gamma Knife Units

Purpose:The Leksell Gamma Knife (GK) B & C series contains 201 Cobalt‐60 sources with a helmet. The new model, Perfexion uses 192 Cobalt‐60 sources without a helmet; using IRIS system for collimation and stereotactic guidance to deliver SRS to brain tumors. Relative dose to extracranial organs at risk (OARs) is measured in phantom in this study for Perfexion and C‐series GK.Materials & Methods:Measurements were performed in a Rando anthropomorphic phantom on both systems using a large ion chamber (Keithley‐175) for each collimator. The Keithley‐175 cc ion chamber was sandwiched between phantom slices at various locations in the phantom to correspond to different extracranial OARs (thyroid, heart, kidney, ovary and testis, etc.) The dose measurement was repeated with OSL detectors for each position and collimator.Results:A large variation is observed in the normalized dose between these two systems. The dose beyond the housing falls off exponentially for Perfexion. Dose beyond the C‐series GK housing falls off exponentially from 0–20cm then remains relatively constant from 20–40cm and again falls off with distance but less rapidly. The variation of extracranial dose with distance for each collimator is found to be parallel to each other for both systems.Conclusion:Whole body dose is found to vary significantly between these systems. It is important to measure the extracranial dose, especially for young patients. It is estimated that dose falls off exponentially from the GK housing and is about 1% for large collimators at 75 cm. The dose is two‐orders of magnitude smaller for the 4mm collimator. However, this small dose for patient may be significant radiologically.

Multimodal Biometric Identification System: Fusion of Iris and Fingerprint

This paper proposes a biometric person identification system based on fusion of Iris and Fingerprint images. This paper attempts to improve the performance of iris and fingerprintbased identification system by combining the individual features obtained by implementing Iris and Fingerprint identification system. There exist techniques to provide biometric identification systems based on one or other type of modalities. But usage of multiple modalities has resulted in higher accuracy and reliability as concluded by the experiments conducted.

Multiple local feature representations and their fusion based on an SVR model for iris recognition using optimized Gabor filters

Abstract Gabor descriptors have been widely used in iris texture representations. However, fixed basic Gabor functions cannot match the changing nature of diverse iris datasets. Furthermore, a single form of iris feature cannot overcome difficulties in iris recognition, such as illumination variations, environmental conditions, and device variations. This paper provides multiple local feature representations and their fusion scheme based on a support vector regression (SVR) model for iris recognition using optimized Gabor filters. In our iris system, a particle swarm optimization (PSO)- and a Boolean particle swarm optimization (BPSO)-based algorithm is proposed to provide suitable Gabor filters for each involved test dataset without predefinition or manual modulation. Several comparative experiments on JLUBR-IRIS, CASIA-I, and CASIA-V4-Interval iris datasets are conducted, and the results show that our work can generate improved local Gabor features by using optimized Gabor filters for each dataset. In addition, our SVR fusion strategy may make full use of their discriminative ability to improve accuracy and reliability. Other comparative experiments show that our approach may outperform other popular iris systems.

Biometric template protection with DCT-based watermarking

In this paper we have addressed a solution of two big issues in design of multimodal system: template protection and fusion strategy. A robust biometric watermarking algorithm is proposed for biometric template protection. The fingerprint feature vector and iris features are used as watermark. Proposed DCT-based watermarking technique embeds watermark in low-frequency AC coefficients of selected 8 $$\times $$ × 8 DCT smoother blocks. Blocks are classified based on human visual system. The robustness of the proposed algorithm is compared with the few state-of-art literature when watermarked image is subjected to possible channel attacks. Decision level fusion strategy is used to improve the overall performance of multimodal system. That is achieved by conditionally limiting the threshold of the fingerprint system to a maximum value, obtained by projecting 50 % of the cross over error rate on to the FRR curve of the iris system.

The Weight of the Mission

Two things stand out about Expro’s Ax-s technology—it is capable and it is big. The scale of the device, whose name is pronounced “access,” shows the array of tools that may be called on to deal with production problems. “The seven-year development project, which cost USD 200, produced a device that can be lowered on top of a wellhead with the brains of a remotely operated vehicle (ROV) capable of deploying any one of eight diagnostic and repair tools in minutes with a winch and tanks for glycol or other fluids needed on the job. When fully assembled, it stands at 110 ft high and weighs 237 tons. Its competitors include companies such as Blue Ocean Technologies, whose Iris system is also certified to work in deep water. It weighs 25 tons, but it can only insert one tool at a time into the well. Change outs require pulling one tool to the surface and lowering another. All subsea wireline systems connect to the subsea trees with a well control package using valves and blowout preventers to contain what is inside the well. (The term “tree” was coined when the flow control device consisted of a vertical pipe with hardware branching off of the trunk. Subsea wellheads are complex clusters of pipes, valves, and controls surrounded by a stout metal frame the size of a garage.) The size differences show different design philosophies. Expro designed its device to speed the work by offering a wider range of options, like a surgeon with an array of tools at hand to deal with the unexpected. Inside the pressure housing is a collection of eight tools, which can be altered to suit the job. An Expro illustration showed a diagnostic water tool, a cutting torch, a perforating gun, a plug, and a tractor to pull the strings through a horizontal well. “Once it is on the well, it can change out wireline tools in 10 minutes,” said Matthew Law, technical manager of sales and marketing at Expro Ax-s Technology. “There are eight tools on board. It is more efficient than those with limited functions that must be pulled up to the surface to change out functions.” He said the added speed of the work by the Ax-s, plus a day rate significantly less than drilling rigs, will allow workovers at one third the cost of a drilling rig.