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An Automatic Deep Neural Network Model for Fingerprint Classification

Intelligent Automation & Soft Computing 2023年第5期36卷 2007-2023页

作者： Amira tarek Mahmoud Wael AAwad Gamal Behery Mohamed Abouhawwash Mehedi Masud Hanan Aljuaid Ahmed Ismail Ebada Department of Computer Science Faculty of SciencePort Said UniversityPort SaidEgypt Department of Computer Science Faculty of Computers and Artificial IntelligenceDamietta UniversityNew DamiettaEgypt Department of Mathematics Faculty of ScienceMansoura UniversityMansoura35516Egypt Department of Computational Mathematics Scienceand Engineering(CMSE)College of EngineeringMichigan State UniversityEast LansingMI 48824USA Department of Computer Science College of Computers and Information TechnologyTaif UniversityP.O.Box 11099Taif21944Saudi Arabia Computer Sciences Department College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman University(PNU)P.O.Box 84428Riyadh11671Saudi Arabia Department of Information Systems Faculty of Computers and Artificial IntelligenceDamietta UniversityNew DamiettaEgypt

The accuracy ofﬁngerprint recognition model is extremely important due to its usage in forensic and securityﬁ***ﬁngerprint recognition system has particular network architecture whereas many other networks achieve higher *** solve this problem in a uniﬁed model,this paper proposes a model that can automatically specify ***,it is called an automatic deep neural net-work(ADNN).Our algorithm can specify the appropriate architecture of the neur-al network used and some signiﬁcant parameters of this *** parameters are the number ofﬁlters,epochs,and *** guarantees the high-est accuracy by updating itself until achieving 99%accuracy then it stops and out-puts the ***,this paper proposes an end-to-end methodology for recognizing a person’s identity from the inputﬁngerprint image based on a resi-dual convolutional neural *** is a complete system and is fully automated whether in the features extraction stage or the classiﬁcation *** goal is to automate thisﬁngerprint recognition system because the more automatic the sys-tem is,the more time and effort it *** model also allows users to react by inputting the initial values of these ***,the model updates itself until itﬁnds the optimal values for the parameters and achieves the best *** advantage of our algorithm is that it can recognize people from their thumb and otherﬁngers and its ability to recognize distorted *** algo-rithm achieved 99.75%accuracy on the publicﬁngerprint dataset(SOCOFing).This is the best accuracy compared with other models.

关键词： Automatic system ﬁngerprint classiﬁcation residual networks deep learning

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Monitoring and factors affecting levels of airborne and water bromoform in chlorinated seawater swimming pools

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Journal of Environmental Sciences 2017年第8期29卷 262-270页

作者： Jean-Luc Boudenne Julien Parinet Carine Demelas tarek Manasfi Bruno Coulomb Aix Marseille Univ CNRS LCE13331 Marseille France Arises 94700 Maisons-Alfort France

Water and air quality of eight seawater swimming pools using chlorine disinfection was measured during four sampling campaigns, spread on one full-year, and in four thalassotherapy centers located in Southeast of France. Concentrations of trihalomethanes（THMs） in air and in water as well as concentrations of parameters, including nonpurgeable organic carbon（NPOC）, free residual chlorine（Cl_f）, pH, Kjeldhal Nitrogen（KN）, salinity,conductivity, bromide ions and, water and air temperature, were measured. Water and air samples were collected in triplicates morning — at the opening of the pools —, noon and night — at the closing of the pools —, in summer and winter. Data analysis was performed by Principal Component Analysis（PCA） and rotated component matrix, from both data quality and other parameters such as TOC, aromaticity（UV_（254））, pH, hygrometry, and free residual chlorine（Cl_f）. This statistical analysis demonstrates a high correlation between TOC, Cl_fand UV_（254） and THM levels found in air and water, particularly for the major ones（CHBr_3in water：300.0 μg/L mean, 1029.0 μg/L maximum; CHBr_3 in air： 266.1 μg/m^3 mean,1600.0 μg/m^3 maximum, and CHClBr_2 in water： 18.9 μg/L mean, 81.0 μg/L maximum;CHClBr_2 in air： 13.6 μg/m^3 mean, 150.0 μg/m^3maximum）. These high levels of bromoform（CHBr_3） are particularly worrisome in such health institutions, even these levels do not exceed the Permissible Exposure Limit（PEL） of 5 mg/m^3 as an 8 hour time-weighted average currently fixed by various administrations, such as Occupational Safety and Health Administration（OSHA）.

关键词： Trihalomethanes Bromoform Air Seawater Swimming pool Brominated compounds

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Detection and quantifi cation of extracellular microRNAs in medulloblastoma

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Journal of Cancer Metastasis and Treatment 2015年第1期1卷 67-75页

作者： tarek Shalaby Giulio Fiaschetti Sylvain Baulande Nicolas U.Gerber Martin Baumgartner Michael A.Grotzer Department of Oncology University Children’s Hospital Zurich8032 ZurichSwitzerland Department of Biology PartnerChip CEAGénopole Campus 291000ÉvryFrance.

Aim:Medu lloblastoma(MB)is the most common malignant brain tumor in *** crucial role of extracellular-microRNAs(ex-miRNAs)in cancer has been widely recognized;however,their role in MB remains *** study aimed to investigate MB-driven ***:Microarray analysis was used to disclose the identity and quantity of key miRNAs excreted in culture-medium(CM)of 3 human MB cell lines and cere brospinal fl uid(CSF)of brain tumors(including MB)and leukemia *** expression was validated by quantitative reverse transcription polymerase chain ***:We have demonstrated that the 3 MB cell lines tested commonly expressed 1,083 miRNAs in their spent *** them,57 miRNAs were specifi c to the CM of metastasis-related cell lines which represents the aggressive group 3 and group 4 MB subtypes.A signifi cant number(1,254)of ex-miRNAs were identifi ed in the CSF of a MB ***-six of these miRNAs were found to be differentially expressed in this patient’s CSF compared with ***,3 metastasis-associated miRNAs over-represented in CM of metastasis-related MB cell lines were found to be significantly enriched in the CSF of the MB ***:Although more samples are required to fully verify these results,our work provides the first evidence for the presence of a signifi cant amount of miRNAs excreted extracellularly by MB cells and raises the possibility that,in the near future,miRNAs could be probed in CSF of MB patients and serve as novel biological markers.

关键词： Medulloblastoma extracellular-microRNA pediatric cancer

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Performance and calibration of quark/gluon-jet taggers using 140 fb^(-1) of pp collisions at √s=13 TeV with the ATLAS detector

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Chinese Physics C 2024年第2期48卷 1-25页

作者： G. Aad B. Abbott K. Abeling N.J. Abicht S.H. Abidi A. Aboulhorma H. Abramowicz H. Abreu Y. Abulaiti B.S. Acharya C. Adam Bourdarios L. Adamczyk S.V. Addepalli M.J. Addison J. Adelman A. Adiguzel T. Adye A.A. Affolder Y. Afik M.N. Agaras J. Agarwala A. Aggarwal C. Agheorghiesei A. Ahmad F. Ahmadov W.S. Ahmed S. Ahuja X. Ai G. Aielli A. Aikot M. Ait Tamlihat B. Aitbenchikh I. Aizenberg M. Akbiyik T.P.A. Åkesson A.V. Akimov D. Akiyama N.N. Akolkar K. Al Khoury G.L. Alberghi J. Albert P. Albicocco G.L. Albouy S. Alderweireldt M. Aleksa I.N. Aleksandrov C. Alexa T. Alexopoulos F. Alfonsi M. Algren M. Alhroob B. Ali H.M.J. Ali S. Ali S.W. Alibocus M. Aliev G. Alimonti W. Alkakhi C. Allaire B.M.M. Allbrooke J.F. Allen C.A. Allendes Flores P.P. Allport A. Aloisio F. Alonso C. Alpigiani M. Alvarez Estevez A. Alvarez Fernandez M. Alves Cardoso M.G. Alviggi M. Aly Y. Amaral Coutinho A. Ambler C. Amelung M. Amerl C.G. Ames D. Amidei S.P. Amor Dos Santos K.R. Amos V. Ananiev C. Anastopoulos T. Andeen J.K. Anders S.Y. Andrean A. Andreazza S. Angelidakis A. Angerami A.V. Anisenkov A. Annovi C. Antel M.T. Anthony E. Antipov M. Antonelli F. Anulli M. Aoki T. Aoki J.A. Aparisi Pozo M.A. Aparo L. Aperio Bella C. Appelt A. Apyan N. Aranzabal S.J. Arbiol Val C. Arcangeletti A.T.H. Arce E. Arena J-F. Arguin S. Argyropoulos J.-H. Arling O. Arnaez H. Arnold G. Artoni H. Asada K. Asai S. Asai N.A. Asbah J. Assahsah K. Assamagan R. Astalos S. Atashi R.J. Atkin M. Atkinson H. Atmani P.A. Atmasiddha K. Augsten S. Auricchio A.D. Auriol V.A. Austrup G. Avolio K. Axiotis G. Azuelos D. Babal H. Bachacou K. Bachas A. Bachiu F. Backman A. Badea P. Bagnaia M. Bahmani A.J. Bailey V.R. Bailey J.T. Baines L. Baines O.K. Baker E. Bakos D. Bakshi Gupta V. Balakrishnan R. Balasubramanian E.M. Baldin P. Balek E. Ballabene F. Balli L.M. Baltes W.K. Balunas J. Balz E. Banas M. Bandieramonte A. Bandyopadhyay S. Bansal L. Barak M. Barakat E.L. Barberio D. Barberis M. Barbero M.Z. Barel K.N. Barends T. Barillari M-S. Barisits T. Barklow P. Baron D.A. Baron Mo The ATLAS Collaboration

The identification of jets originating from quarks and gluons,often referred to as quark/gluon tagging,plays an important role in various analyses performed at the Large Hadron Collider,as Standard Model measurements and searches for new particles decaying to quarks often rely on suppressing a large gluon-induced *** paper describes the measurement of the efficiencies of quark/gluon taggers developed within the ATLAS Collaboration,using √s=13 TeV proton–proton collision data with an integrated luminosity of 140 fb^(-1) collected by the ATLAS *** taggers with high performances in rejecting jets from gluon over jets from quarks are studied:one tagger is based on requirements on the number of inner-detector tracks associated with the jet,and the other combines several jet substructure observables using a boosted decision tree.A method is established to determine the quark/gluon fraction in data,by using quark/gluon-enriched subsamples defined by the jet *** in tagging efficiency between data and simulation are provided for jets with transverse momentum between 500 GeV and 2 TeV and for multiple tagger working points.

关键词： ATLAS JET QUARK GLUON TAGGING

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