Facial Identification Of Driver Fatigue Health And Social Care Essay

device driver tiredness is oft unmatched of the starring(predicate) causes of transaction accidents. In this lowest twelvemonth underpickings, a computing machine fantasy attack which exploits the number one wood s nervus facial nerve nerve nerveis look is considered, utilizing a combination of the genus Viola-Jones expect espial technique and financial support vector machines to fall a startle facial visual aspect and fancy the stratum of tiredness.Section 1 DescriptionIntroductionStatisticss specify that device number one wood fatigue is frequently one of the prima causes of traffic accidents. Over the past few sr. ages, a bunch of research and attempt has been put forth in planing constitutions that monitor tw ain driver and driving public first appearance. A computing machine vision attack which exploits the driver s facial look is considered in this concluding twelvemonth under victorious. The Viola-Jones real-time object sense precedent working o n a boosted cascade of Haar ripple indications is select for daring perception. To find the power capitulum of fatigue duty, multiple characteristic categorization is so performed utilizing support vector machines. The motives for taking to develop the schema in this mode be the rapid submit sensing times coupled with the simple and inexpensive overall effectuation, avoiding the exact to put in expensive and complex hardw ar.Concise Literature ReviewThis piece gives a wide reappraisal of the literary work related to await sensing in fatigue observe systems and engineerings, c one timentrating peculiarly on what has been done in the field of driver weariness. In subdivision 1.2.1, several(prenominal) statistics of fatigue-related motor vehicle accidents be mentioned and analysed. Section 1.2.2 high spots some of the more(prenominal) roaring systems ( both commercial and non-commercial ) that have been implemented in new over-the-hill ages. On the some other(a) m anus, subdivision 1.2.3 nowadayss an enlightening overview of the algorithms and techniques typically utilize in the growing of much(prenominal) systems, disassociateicularly those refering to both vitrine and facial characteristic sensing. Representative plants for severally of these orders allow for be take.Statisticss Related to device driver wear thin driver weariness has been one of the chief causes of route accidents and adult male deaths in recent previous(a) ages, and in this subdivision an effort is made to foreground some of the more of import statistics that demonst aim this negative tendency.The national street Traffic prophylactic Administration ( NHTSA ) 1 estimations that 2-23 % of all vehicle clangs can be attributed to driver weariness. Every twelvemonth, around 100,000 traffic accidents and 71,000 hurts related to driver sleepiness be inform in the United States, out of which more than 1,300 ar fateful 2 . The NHTSA 3 besides repports tha t in the twelvemonth 2005 entirely, there were active 5,000 route human deaths ( around 8.4 % ) which were ca utilise either by driver remissness ( 5.8 % ) or sleepy and fatigued drive ( 2.6 % ) . Furthermore, 28 % of fatal traffic accidents were due to lane maintaining failure, one of the indirect effects of weariness on drivers, ensuing in the loss of 16,000 lives. Undoubtedly, truck drivers be more open to tire chiefly because of the long hours travelled on main roads, taking to inevit open humdrum journeys. In fact, a survey by the U.S. subject Transportation arctic Board ( NTSB ) 4 confirmed that weariness was the purpose factor in 51 out of 87 instances of truck accidents.These dismaying statistics pointed to the demand to plan and implement systems upper-case letterable of trailing and analyzing a driver s facial features or organic structure responsiblenesss and giving a warning signal at the first noticeable marks of weariness to seek and forestall the likely h appening of an accident. In the adjacent subdivision of this literature reappraisal, a systema skeletale of these systems will be presented.Existing fag observe agreementsMany different attacks for systems undertaking the job of driver fatigue have been analyse and implemented over the past few old ages. Earlier devices tended to be instead intrusive, necessitating physical contact to measure fatigue characteristics while driving. These characteristics included bosom rate variableness, analysis of encephalon signals every bit sincere as the driver s physiological province. Other systems studied the resemblance of driver sleepiness to maneuvering clasp and vehicle motions, with some besides use lane tracking installations. However, the focal point nowadays is more towards strong-minded non-intrusive systems that work in the background without deflecting the driver in any manner, able to observe and track headspring and eye motions by agencies of one or more cameras mounte d on the vehicle s splashboard. The bulk of merchandises tracking weariness have been designed for on-road vehicles, such as railcars, trucks and engines, and these will be reviewed in the undermentioned subdivision. In Section 1.2.2.2, other graphic symbolwrites of weariness observe systems that have been deployed will be analysed.On-Road fatigue duty Monitoring SystemsCommercially Implemented SystemsIn the system presented by Advanced Brain Monitoring Inc. 5 , a caput mounted device in the signifier of a baseball game cap uses the encephalon s EEG ( Electroencephalography ) signals to mensurate weariness. devil electrodes inside the baseball cap are connected to the driver s scalp to go these signals, directing them via wireless moving ridges to a processing device 20 pess off from the driver. Russian seller Neurocom marketed the Engine driver Vigilance Telemetric come across System ( EDVTCS ) 6 for physical exertion within the Russian railroad system. EDVTCS place ly track drivers physiological province by mensurating alterations in the electro cuticular natural process ( EDA ) i.e. alterations in the tegument s opposition to electricity based on the eccrine perspiration secretory organs of the human organic structure, primed(p) chiefly on the thenar of our custodies and the colloidal suspensions of our pess. wizard of the first non-intrusive driver weariness supervising systems was ASTiD ( Advisory System for Tired Drivers ) 7 . It consists of an current knowledge-base abstractive history exposing a 24-hour anticipation form sing the adventure of the driver traveling to kip piece at the wheel, and a focal point wheel detector system fit of placing humdrum driving intervals, such as those in main roads, every bit good as unusual maneuvering motions as a consequence of driver weariness. local area networke trailing is other attack sproutn to address distraction forms while driving. SafeTRAC, by AssistWare Technology 8 , consists of a witness camera located on the windscreen of the vehicle ( confronting the route ) and a splashboard mounted having device to which it is connected. The camera is able to observe lane markers in roads and issues hearable, visual or haptic warnings if fickle drive forms, such as fixed impetuss among lanes, are observed.Sing the issues encountered in earlier systems, more grandeur now started being presumptuousness to systems that monitored driver head motions, face and facial characteristics. MINDS ( Micro no detection System ) , described in 9 , paths head place and motion, with caput nodding being the chief weariness characteristic use for observing micro-sleep ( inadequate periods of distraction ) while driving. Head motion is track by an array of three capacitance detectors located merely to a higher place the driver s cockpit. Yet another attack was taken by David Dinges and Richard Grace 10 at the Carnegie Mellon Research Institute ( CMRI ) in the development of the PERCLOS proctor, which determines the heart closing per centum over metre for fatigue sensing. In 11 , PERCLOS is defined as the proportion of clip the look are unlikeable 80 % or more for a specified clip interval. expressionLAB 12 focal points on both face and oculus trailing, mensurating PERCLOS ( PERcentage of oculus CLOSure over clip ) and analyzing water chickweeds in living clip ( including wink frequence and wink continuance ) . A central remainder from other systems is that the absolute place of the eyelid, instead than the occlusion of the student, is used to mensurate oculus closing, insideng it much more accurate.The 2001 raise undertaking of the European amalgamation 13 focused specifically on driver weariness, integrating some of the above mentioned steps. The chief end of this undertaking, ( its acronym standing for System for effectual assessment of driver watchfulness and Warning Harmonizing to traffic hazard Estimation ) , was to supplying research on the real-time, non-intrusive do of the driver s current province and driving public presentation. Many spouses were involved in AWAKE, including developers, makers and providers of electronics, research institutes, universities, auto makers and terminal drug users. The undertaking s initial ends were those of accomplishing over 90 % dependability, a lower than 1 % false dismay rate and a user credence rate transcending 70 % .Car fabrication companies, such as Toyota, Nissan and DaimlerChrysler 9 are besides in the part of developing their ain weariness supervising systems.Research ground SystemsMany research documents closely related to driver fatigue monitoring have been published in recent old ages. Assorted attacks have been proposed, among which undress food colouring veridical information has been actually popular. Smith 14 nowadayss a system based on spit out coloration hooey predicates to find weariness from oculus wink rate and caput rotary motion information. Similarly, in the gaze way monitoring system proposed by Wahlstrom et Al. 15 , coloring material predicates are used to turn up the lip part by finding those pels that ascertain the needed coloring material values. Face extraction by skin coloring material cleavage utilizing the normalized RGB skin coloring material suppositious account is adopted in both 16 and 17 . Veeraraghavan and Papanikolopoulos 16 create a system to observe forms of micro-sleep by continuously tracking the driver s look. PERCLOS is the fatigue characteristic measured in Aryuanto and Limpraptono s system 17 . Horng and Chen 18 attempted to utilize the HSI coloring material divinatory account to take the consequence of brightness from the proto sign. political machine acquisition is another common attack to tire sensing. Yang et Al. 19 get to follow a Bayesian interlock based probabilistic model to find the fatigue degree. A Bayesian profits theoretical account is besides c onstructed in 20 , where Zhu and Lan track multiple opthalmic moves, including caput and oculus motions and facial looks via two cameras, one for the face and the other concentrating specifically on the eyes, every bit good as Infra-Red illuminators to get down up the needed countries of the face.A nervous weathervane attack is adopted by DOrazio et Al. 21 and RibariA et Al. 22 in their proposed systems. In 21 , the oculus is detected based on the border information of the flag, with its darker coloring material insideng it much easier to turn up. A back extension nervous web is dexterous to sort the province of the eyes ( either unfastened or closed ) . On the other manus, in 22 , a hybrid nervous web and a combination of the HMAX theoretical account and Viola-Jones sensor together with a Multi-Layer Perceptron ( MLP ) are used to turn up the face. The nock of caput rotary motion, oculus closing and spoken cavity receptivity are the fatigue steps calculated. To sort driver public presentation informations, Liang et Al. 23 make rule of congest Vector railroad cars ( SVMs ) . They focus on cognitive ( mental ) , instead than ocular driver distractions. For fast face and facial characteristic sensing, the mode proposed by Viola and Jones affecting a boosted cascade of characteristics based on Haar ripples is adopted in a figure of documents, including 24 and 25 . Often, a loanblend of techniques are used to moderate kick downstairs consequences for driver weariness sensing. Saradadevi and Bajaj 26 usage Viola-Jones method for emit sensing and SVMs to right sort normal and yawning oral cavity cases. On the contrary, the one presented by Narole and Bajaj 27 combines pixel-based skin coloring material cleavage for face sensing and a mixture of nervous webs and familial algorithms to optimally find the weariness index, with the nervous web being given as initial input values for oculus closing and oscitancy rate.Other wear thin Monitoring SystemsAs with drivers in autos, pilots in aircrafts are obviously capable to tire, chiefly due to the drawn-out flight continuances. NTI Inc. and Science Applications world(prenominal) alliance ( SAIC ) 28 designed the Fatigue Avoidance Scheduling Tool ( solid ) , a system intended to track and foretell weariness degrees for U.S. cinch Force pilots, based on the SAFTE ( relaxation, Activity, Fatigue and Task Effectiveness ) theoretical account created by Dr. Steven Hursh. Another application in which weariness monitoring is utile is in the bar of ready reckoner hallucination Syndrome 29 , a status caused by working for drawn-out hours in forepart of show devices, such as computing machine proctors. Matsushita et Al. 30 besides highly-developed a wearable weariness monitoring system which detects marks of weariness based on caput motions.The broad assortment of different applications developed to supervise weariness is an grounds of the turning importanc e of this field. The focal point in the following portion of the literature reappraisal will shake off to the weariness analysis attack taken in this thesis the sensing of faces and their characteristics in images. The implicit in methods and algorithms typically used in this procedure will be discussed.Reappraisal on Face and Facial Feature contracting TechniquesKnowledge-based methods sensing faces in knowledge-based techniques involves the encryption of a set of simple regulations specifying the features of the human face, including pixel distinctivenesss in the images and the places and correlativities in the midst of the different characteristics, since these are common to all human existences.In a knowledge-based method presented by Yang and Huang 31 , a power structure of grayscale images of different declarations together with three different classs of regulations are used. The images are analysed for realistic face campaigners by using regulations that have to make w ith the cell strength distribution of the human face. An betterment to this multi-resolution method was proposed by Kotropoulos and Pitas 32 . alternatively of ciphering the mean pixel strength of each cell, merely those for each image row and column are computed, organizing perpendicular and horizontal pro bills severally.To vouch a high sensing rate, the regulations in knowledge-based methods must neither be as well general nor excessively specific, and hence, the coevals of regulations for the face must be performed actually carefully. Because of the complexness required in coding all possible face constellations, rule-based techniques do non provide for different face airss 33 , insideng them decidedly contrary for weariness monitoring applications.Feature-based methodsFeature-based attacks to confront sensing differ in a important manner from rule-based techniques in that they fore some attempt to place a individual s facial properties and later find whether the latter ar e valid plenty to represent a human face, ensuing in the sensing of that face.Facial FeaturesThe presence of faces in images is frequently determined by act to observe facial characteristics such as the eyes, nose and rima oris. In a method presented by Sirehoy 34 , the egg-shaped nature of the human face is used as the footing for face sensing in grayscale images with be backgrounds. Due to the different visual aspects of facial characteristics in images, Leung et Al. 35 usage a combination of several local characteristic sensors utilizing Gaussian differential gear filters together with a statistical theoretical account of the geometrical distances between these characteristics to guarantee accurate face localisation. Han et Al. 36 , on the other manus, usage morphological operations that focus chiefly on the oculus part in their efforts to observe faces, based on the logical thinking that this is the most consistent facial part in different light conditions. A more robus t and flexible feature-based system was presented by Yow and Cipolla 37 . The theoretical account cognition of the face that is used screens a wider country, including the superciliums, eyes, nose and mouth. A figure of Partial Face Groups ( PFGs ) , tantamount to a subset of these characteristic points ( 4 ) , are used to provide for partial face occlusions.Face TextureAnother face incite that is used for sensing intents is its textural form, this being specific to worlds and hence easy distinguishable from other forms. Manian and Ross 38 present an algorithm that uses the symmetricalness and uniformity of the facial form as the footing of sensing. Rikert et Al. 39 tackle texture-based sensing in a different manner, utilizing a statistical method that learns to correctly sort whether an image contains a face or non.Skin ColourMany plants related to human fight coloring material as a face sensing cue have been presented in recent old ages. detecting can be either pixel-base d or region-based. The former attack is commonly taken, in which each pel is analysed and classified as either tegument or non-skin. dickens chief picks are made during this procedure the coloring material infinite and tegument modeling method. Harmonizing to 40 , the normalized RGB, HSV and YCrCb coloring material infinites are typically used to expression skin coloring material. nary(prenominal)malized RGB 41 45 is reported to be consistent in different light conditions and face orientations. On the other manus, YCrCb 46 48 and HSV 49 51 are normally chosen since they specifically separate the luminosity and chrominance constituents of the images. In 40 , several other tegument patterning techniques normally adopted are mentioned.Template matching methodsAnother proposed method for face sensing involves the storage of forms of the face and its characteristics, which are so compared to existent face images and given a coefficient of correlation value ( i.e. the de gree of proportion between the existent image and the stored form ) . The higher this value, the greater is the prospect that the image contains a face. models on templet fiting techniques in recent old ages have focused both on fixed and variable-size ( deformable ) templets.Fixed-size TemplatesFengjun et Al. 52 and Ping et Al. 53 usage a combination of skin coloring material cleavage and templet matching for face sensing. Two grayscale templets with predefined sizes one covering the whole face and the other concentrating merely on the part incorporating the two eyes are utilised in both systems. Fixed-size templets, although square(a) to implement, miss adaptability to different caput places since sensing is greatly affected by the orientation defined in the templet.Deformable TemplatesAn improved templet matching method is one in which the templet can be altered to better reflect the input images and therefore would be able to place a wider assortment of faces in differ ent airss. Yuille et Al. 54 propose deformable oculus and mouth templet matching in their work. Initially, the templets are parameterized done pre-processing to request the evaluate form of both characteristics. The work presented by Lanitis et Al. 55 besides parameterizes the templets, concentrating on the coevals of flexible molded human face theoretical accounts through the usage of a Point Distribution Model ( PDM ) 56 which is trained on a figure of images per individual with characteristic fluctuations within and between faces.Appearance-based methodsRather than being based on a set of preset templets, appearance-based face sensing relies on machine larning techniques that identify the presence of faces and their major features by and by a procedure of developing on existent universe informations. One of the most widely adopted machine larning attacks for face sensing are nervous webs, chiefly because of the success they achieved in other applications affecting pat tern acknowledgment. Rowley et Al. 57 propose a robust multi-layer multi-network nervous web that takes as input pre-processed 2020 grayscale pel images to which a filter is use at each pel place, returning a face correlativity value from -1 to 1. The concealed beds of the nervous web are designed to supervise different shaped countries of the human face, such as both eyes utilizing a 205 pel window and single eyes and other characteristics with the 55 and 1010 Windowss. The web so outputs another mark finding the presence or otherwise of a face in a peculiar window.Yang et Al. 58 establish their system on a Sparse engagement of Winnows ( SNoW ) 59 . Two mark nodes ( linear units ) patterning face and non-face form characteristics are used in this instance. The active characteristics ( with binary representation ) in an input illustration are first identified and given as input to the web. The mark nodes are coupled via leaden borders to a subset of the characteristics. T o modify the weights for farther education, the Winnow update regulation method developed by Littlestone 60 is adopted.A linear categorization technique in the signifier of Support Vector molds ( SVMs ) was used to observe faces in an application presented by Osuna et al 61 in 1997. While the bulk of machine acquisition attacks ( including nervous webs ) effort to take down the empirical hazard , i.e. the mistake value in the preparation procedure, SVMs attempt to cut down the upper edge of the expected evocation mistake in a procedure called structural hazard minimization .Viola and Jones 62 present a rapid object sensing system holding face sensing as its motive. A important difference from other proposed systems is that rectangular characteristics, instead than pels, nowadays in the inputted grayscale images are used as the bases for categorization. This has the consequence of increasing the velocity of the overall procedure. Viola and Jones method will be discus sed in item in the following chapter of this thesis.Purposes and AimsFamiliarization with the OpenCV tool.Literature Review about bing systems and methods to be used in this Dissertation. extravagant face sensing utilizing Viola-Jones technique.Execution of multiple facial characteristics used to find the fatigue degree.Application of Support Vector Machine classifier to observe grievous state of affairss such as driver kiping etc.Real-time execution of the proposed methods within OpenCV.MethodsViola-Jones technique for face sensing.Support vector machines to sort facial visual aspect ( e.g. open/closed eye/mouth ) .Features to be taken into consideration caput motion, oculus closing and frequence of oral cavity gap ( bespeaking yawning ) . sum weariness steps include PERCLOS ( PERcentage shopping center CLOSure over clip ) and AECS ( Average Eye Closure Speed ) .EvaluationComparing the developed system to other systems found in literature in footings of precision, callback and t ruth.Deducing some trial informations on which the algorithms will be tested.Test topics seeking out the application.Showing the consequences obtained.DeliverablesProgress Report.Review Report.2 page abstract for ICT Final YearA scholar Projects Exhibition.Presentation Slides and Poster.Spiral and awkward edge transcripts of the Dissertation Report.C++ application, preparation and testing resources.Section 2 Work PlanWork done so farCollected and read several documents related to bing driver weariness systems and face sensing in general.Completed the first bill of stand in of the literature reappraisal.Familiarized myself with the OpenCV environment.Used a webcam to capture two short cartridge holders inside a auto, one in sunny and the other in cloud-covered conditions.Collected 2000 positive and 4000 negative images for face sensing. confirmatory images 1500 taken from FERET grayscale face database, the other 500 from the captured cartridge holders.Negative images created a C++ application to randomly choice non-relevant countries of the frames of the two captured cartridge holders.Created another C++ application to be able to harvest the positive images to bespeak merely the needed rectangular countries, add together forthing a text file to be used in the preparation procedure.Used this information to bring forth a classifier for faces in XML format with OpenCV s Haar preparation public-service corporation.SubtasksCompute truth, preciseness and callback values for the face sensing preparation.Trial with new picture cartridge holders and observing the consequences obtained.Perform Cross Validation.Train the classifier for oral cavities, once more utilizing positive and negative images. For oculus sensing, an already generated classifier will be used.Extract characteristics from face, oculus and mouth sensing.Integrate and utilize a C++ library for support vector machines, such as libSVM, to sort facial visual aspect. print Abstract, Introduction, Methodo logy, Evaluation, Results, Future Work and Conclusion of the Dissertation Report.Write Review Report.Write 2 page abstract for ICT Final YearA Student Projects Exhibition.Work on Presentation Slides and Poster.Schedule ( Gantt Chart )Section 3 Mentions 1 D. Dinges, M. Mallis, G. Maislin and J. Powell ( 1998 ) . lowest study Evaluation of Techniques for Ocular Measurement as an Index of Fatigue and the Basis for Alertness Management , U.S. Dept. Transportation, National Highway Traffic Safety Administration, online , digest accessed on 4th October 2010, usable at hypertext careen communications communications communications communications communications protocol //ntl.bts.gov/lib/jpodocs/edlbrow/7d01 .pdf 2 National Highway Traffic Safety Administration ( 2005 ) . NHTSA vehicle Safety Rulemaking and Supporting Research Priorities Calendar Old ages 2005-2009 , online , utmost accessed on 4th October 2010, addressable at hypertext deepen protocol //www.nhtsa.go v/cars/rules/rulings/priorityplan-2005.html 3 National Highway Traffic Safety Administration ( 2005 ) . Traffic Safety Facts 2005 A Compilation of Motor Vehicle Crash Data from the Fatality summary Reporting System and the General Estimates System , National Center for Statistics and psychoanalysis, U.S. Dept. Transportation, online , go accessed on 4th October 2010, lendable at hypertext wobble protocol //www-nrd.nhtsa.dot.gov/pubs/tsf2005.pdf 4 Hall, Hammerschmidt and Francis ( 1995 ) . Safety Recommendation , National Transportation Safety Board, online , outlast accessed on twenty-first declination 2010, on hand(predicate) at hypertext take outral protocol //www.ntsb.gov/recs/ earn/1995/H95_5D.pdf 5 J. Cavuoto, Alertness Monitoring Devices Emerge from San Diego , Neurotech Business Report, online , end accessed on twenty-first September 2010, forthcoming at hypertext reposition protocol //www.neurotechreports.com/pages/alertness.html 6 J-S Co. 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AWAKE Project Aim and Objectives , Road Safety Workshop, Balocco, Italy, online , Last accessed on 21st September 2010, Available at hypertext transfer protocol //www.awake-eu.org/pdf/aim_achievements.pdf 14 P. Smith, M. Shah and N. D. V. Lobo ( 2003 ) . ascertain Driver Visual Attention with One Camera , IEEE Transactions on Intelligent Transportation Systems, Vol. 4, No. 4, pp. 205 218, online , Last accessed on 16th luxurious 2010, Available at hypertext transfer protocol //citeseerx.ist.psu.edu/viewdoc/download? inside=10.1.1.4.842 & A rep=rep1 & A type=pdf 15 E. Wahlstrom, O. Masoud and N. Papanikolopoulos ( 2003 ) . Vision establish Methods for Driver Monitoring , IEEE Intelligent Transportation Systems Conf, pp. 903 908, online , Last accessed on 28th July 2010, Available at hypertext transfer protocol //citeseerx.ist.psu.edu/viewdoc/download? doi=10.1.1.3.4434 & A rep=rep1 & A type=pdf 16 H. Veeraraghavan and N. Papanikolopoulos ( 2001 ) . 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Real-time Detection of Driver Cognitive Distraction Using Support Vector Machines , IEEE Transactions on Intelligent Transportation Systems, Vol. 8, No. 2, pp. 340 350. 24 H. Ma, Z. Yang, Y. Song and P. Jia ( 2008 ) . A fast Method for Monitoring Driver Fatigue Using Monocular Camera , transactions of the 11th Joint Conference on Information Sciences, Atlantis Press, online , Last accessed on 28th July 2010, Available at hypertext transfer protocol //www.atlantis-press.com/php/download_paper.php? id=1717 25 T. Brandt, R. Stemmer, B. Mertsching and A. Rakotonirainy ( 2004 ) . cheap Ocular Driver Monitoring System for Fatigue and Monotony , 2004 IEEE International Conference on Systems, Man and Cybernetics, Vol. 7, pp. 6451 6456, online , Last accessed on 28th July 2010, Available at hypertext transfer protocol //citeseerx.ist.psu.edu/viewdoc/download? doi=10.1.1.93.1899 & A rep=rep1 & A type=pdf 26 M. Saradadevi and P. R. Bajaj ( 2008 ) . 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