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Automated Leukemia Screening and Sub-types Classification Using Deep Learning

computer systems science & Engineering 2023年第9期46卷 3541-3558页

作者： Chaudhary Hassan Abbas Gondal Muhammad Irfan Sarmad Shafique Muhammad Salman Bashir Mansoor Ahmed Osama M.Alshehri Hassan H.Almasoudi Samar M.Alqhtani Mohammed M.Jalal Malik A.Altayar Khalaf F.Alsharif department of computer science COMSATS University Islamabad44000Pakistan Electrical Engineering department College of EngineeringNajran UniversityNajran61441Saudi Arabia Control Automotive and Robotics LabNational Center of Robotics and Automation(NCRA HEC)MirpurPakistan Mirpur University of Science and Technology(MUST)MirpurPakistan department of computer science Virtual University of PakistanLahore54000Pakistan department of Clinical Laboratory sciences College of Applied Medical SciencesNajran UniversityNajran61441Saudi Arabia department of information systems College of Computer Science and Information SystemsNajran UniversityNajran61441Saudi Arabia department of Medical Laboratory Technology Faculty of Applied Medical SciencesUniversity of TabukTabukSaudi Arabia department of Clinical Laboratory sciences College of Applied Medical SciencesTaif UniversityP.O.Box 11099Taif21944Saudi Arabia

Leukemia is a kind of blood cancer that damages the cells in the blood and bone marrow of the human *** produces cancerous blood cells that disturb the human’s immune system and significantly affect bone marrow’s production ability to effectively create different types of blood cells like red blood cells(RBCs)and white blood cells(WBC),and *** can be diagnosed manually by taking a complete blood count test of the patient’s blood,from which medical professionals can investigate the signs of leukemia ***,two other methods,microscopic inspection of blood smears and bone marrow aspiration,are also utilized while examining the patient for ***,all these methods are labor-intensive,slow,inaccurate,and require a lot of human experience and *** authors have proposed automated detection systems for leukemia diagnosis to overcome these *** have deployed digital image processing and machine learning algorithms to classify the cells into normal and blast ***,these systems are more efficient,reliable,and fast than previous manual diagnosing ***,more work is required to classify leukemia-affected cells due to the complex characteristics of blood images and leukemia cells having much intra-class variability and inter-class *** this paper,we have proposed a robust automated system to diagnose leukemia and its *** have classified ALL into its sub-types based on FAB classification,i.e.,L1,L2,and L3 types with better *** have achieved 96.06%accuracy for subtypes classification,which is better when compared with the state-of-the-art methodologies.

关键词： Healthcare cancer detection deep learning convolutional neural network

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Single-step-fabricated disordered metasurfaces for enhanced light extraction from LEDs

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Light(science & Applications) 2021年第10期10卷 1840-1848页

作者： Peng Mao Changxu Liu Xiyan Li Mengxia Liu Qiang Chen Min Han Stefan A.Maier Edward H.Sargent Shuang Zhang School of Physics and Astronomy University of BirminghamB152TT BirminghamUK National Laboratory of Solid state Microstructures College of Engineering and Applied Sciencesand Collaborative Innovation Centre of Advanced MicrostructuresNanjing UniversityNanjing 210093China Chair in Hybrid Nanosystems Nanoinstitute MunichFaculty of PhysicsLudwigMaximilians-Universitaet Muenchen80539 MuenchenGermany department of Electrical and computer Engineering University of Toronto35 St.George StreetTorontoON M5S 1A4Canada Key Laboratory of Intelligent Optical Sensing and Manipulation(Nanjing university) Ministry of EducationNanjingChina department of Physics Imperial College LondonLondon SW72AZUK department of Physics University of Hong KongHong Kong 999077China department of Electrical and Electronic Engineering University of Hong KongHong Kong 999077China

While total internal reflection(TIR)lays the foundation for many important applications,foremost fibre optics that revolutionised information technologies,it is undesirable in some other applications such as light-emitting diodes(LEDs),which are a backbone for energy-efficient light *** the case of LEDs,TIR prevents photons from escaping the constituent high-index *** in material science have led to good efficiencies in generating photons from electron–hole pairs,making light extraction the bottleneck of the overall efficiency of *** recent years,the extraction efficiency has been improved,using nanostructures at the semiconductor/air interface that outcouple trapped photons to the outside ***,the design of geometrical features for light extraction with sizes comparable to or smaller than the optical wavelength always requires sophisticated and timeconsuming fabrication,which causes a gap between lab demonstration and industrial-level *** by lightning bugs,we propose and realise a disordered metasurface for light extraction throughout the visible spectrum,achieved with single-step *** applying such a cost-effective light extraction layer,we improve the external quantum efficiency by a factor of 1.65 for commercialised GaN LEDs,demonstrating a substantial potential for global energy-saving and sustainability.

关键词： light backbone consuming

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Search for the doubly charmed baryon ■

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science China(Physics,Mechanics & Astronomy) 2020年第2期63卷 8-22页

作者： R.Aaij C.Abellán Beteta T.Ackernley B.Adeva M.Adinolfi H.Afsharnia C.A.Aidala S.Aiola Z.Ajaltouni S.Akar P.Albicocco J.Albrecht F.Alessio M.Alexander A.Alfonso Albero G.Alkhazov P.Alvarez Cartelle A.A.Alves Jr S.Amato Y.Amhis L.An L.Anderlini G.Andreassi M.Andreotti F.Archilli J.Arnau Romeu A.Artamonov M.Artuso K.Arzymatov E.Aslanides M.Atzeni B.Audurier S.Bachmann J.J.Back S.Baker V.Balagura W.Baldini A.Baranov R.J.Barlow S.Barsuk W.Barter M.Bartolini F.Baryshnikov G.Bassi V.Batozskaya B.Batsukh A.Battig V.Battista A.Bay M.Becker F.Bedeschi I.Bediaga A.Beiter L.J.Bel V.Belavin S.Belin N.Beliy V.Bellee K.Belous I.Belyaev G.Bencivenni E.Ben-Haim S.Benson S.Beranek A.Berezhnoy *** D.Berninghoff H.C.Bernstein E.Bertholet A.Bertolin C.Betancourt F.Betti M.O.Bettler Ia.Bezshyiko S.Bhasin J.Bhom M.S.Bieker S.Bifani P.Billoir A.Birnkraut A.Bizzeti M.Bjφrn M.P.Blago T.Blake F.Blanc S.Blusk D.Bobulska V.Bocci O.Boente Garcia T.Boettcher A.Boldyrev A.Bondar N.Bondar S.Borghi M.Borisyak M.Borsato J.T.Borsuk T.J.V.Bowcock C.Bozzi S.Braun A.Brea Rodriguez M.Brodski J.Brodzicka A.Brossa Gonzalo D.Brundu E.Buchanan A.Buonaura C.Burr A.Bursche J.S.Butter J.Buytaert W.Byczynski S.Cadeddu H.Cai R.Calabrese S.Cali R.Calladine M.Calvi M.Calvo Gomez A.Camboni P.Campana D.H.Campora Perez L.Capriotti A.Carbone G.Carboni R.Cardinale A.Cardini P.Carniti K.Carvalho Akiba A.Casais Vidal G.Casse M.Cattaneo G.Cavallero R.Cenci J.Cerasoli M.G.Chapman M.Charles Ph.Charpentier G.Chatzikonstantinidis M.Chefdeville V.Chekalina C.Chen S.Chen A.Chernov S.-G.Chitic V.Chobanova M.Chrzaszcz A.Chubykin P.Ciambrone M.F.Cicala X.Cid Vidal G.Ciezarek F.Cindolo P.E.L.Clarke M.Clemencic H.V.Cliff J.Closier J.L.Cobbledick V.Coco J.A.B.Coelho J.Cogan E.Cogneras L.Cojocariu P.Collins T.Colombo A.Comerma-Montells A.Contu N.Cooke G.Coombs S.Coquereau G.Corti C.M.Costa Sobral B.Couturier D.C.Craik J.Crkovska A.Crocombe M.Cruz Torres R.Currie C.L.Da Silva E.Dall'Occo J.Dalseno C.D'Ambrosio A.Danilina P.d'Argent A.Davis O.De Aguiar Francisco K.De Bruyn S.De Capua M Centro Brasileiro de Pesquisas Fisicas(CBPF) Rio de JaneiroBrazil Universidade Federal do Rio de Janeiro(UFRJ) Rio de JaneiroBrazil Center for High Energy Physics Tsinghua UniversityBeijingChina School of Physics state Key Laboratory of Nuclear Physics and Technology Peking UniversityBeijingChina university of Chinese Academy of sciences BeijingChina Institute Of High Energy Physics(IHEP) BeijingChina Institute of Particle Physics Central China Normal UniversityWuhanHubeiChina Univ.Grenoble Alpes Univ.Savoie Mont BlancCNRSIN2P3-LAPPAnnecyFrance Universite Clermont Auvergne CNRS/IN2P3LPCClermont-FerrandFrance Aix Marseille Univ CNRS/IN2P3CPPMMarseilleFrance LAL Univ.Paris-SudCNRS/IN2P3Universite Paris-SaclayOrsayFrance LPNHE Sorbonne Universite Paris Diderot Sorbonne Paris Cite CNRS/IN2P3ParisFrance I.Physikalisches Institut RWTH Aachen UniversityAachenGermany Fakultat Physik Technische Universitat DortmundDortmundGermany Max-Planck-Institut für Kernphysik(MPIK) HeidelbergGermany Physikalisches Institut Ruprecht-Karls-Universitat HeidelbergHeidelbergGermany School of Physics University College DublinDublinIreland INFN Sezione di Bari BariItaly INFN Sezione di Bologna BolognaItaly INFN Sezione di Ferrara FerraraItaly INFN Sezione di Firenze FirenzeItaly INFN Laboratori Nazionali di Frascati FrascatiItaly INFN Sezione di Genova GenovaItaly INFN Sezione di Milano-Bicocca MilanoItaly INFN Sezione di Milano MilanoItaly INFN Sezione di Cagliari MonserratoItaly INFN Sezione di Padova PadovaItaly INFN Sezione di Pisa PisaItaly INFN Sezione di Roma Tor Vergata RomaItaly INFN Sezione di Roma La Sapienza RomaItaly Nikhef National Institute for Subatomic Physics AmsterdamNetherlands Nikhef National Institute for Subatomic Physics and VU university Amsterdam AmsterdamNetherlands Henryk Niewodniczanski Institute of Nuclear Physics Polish Academy of sciences KrakowPoland AGH-university of science and Technology Faculty of Physics and Applied Computer ScienceKrakowPoland Natio

A search for the doubly charmed baryon ■^+cc is performed through its decay to theΛ^+c K^-π^+ final state,using proton-proton collision data collected with the LHCb detector at centre-of-mass energies of 7,8 and 13 *** data correspond to a total integrated luminosity of 9 fb^-*** significant signal is observed in the mass range from 3.4 to 3.8 GeV/c^*** limits are set at 95%credibility level on the ratio of the ■^+cc production cross-section times the branching fraction to that ofΛ^+c and ■^++cc *** limits are determined as functions of the ■^+cc mass for different lifetime hypotheses,in the rapidity range from 2.0 to 4.5 and the transverse momentum range from 4 to 15 GeV/c.

关键词： charmed baryons limits on production of particles charmed quarks experimental tests

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Measurement of Ξcc++ production in pp collisions at s1/2=13 TeV

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Chinese Physics C 2020年第2期44卷 13-23页

作者： R.Aaij C.Abellán Beteta T.Ackernley B.Adeva M.Adinolfi H.Afsharnia C.A.Aidala S.Aiola Z.Ajaltouni S.Akar P.Albicocco J.Albrecht F.Alessio M.Alexander A.Alfonso Albero G.Alkhazov P.Alvarez Cartelle A.A.Alves Jr S.Amato Y.Amhis L.An L.Anderlini G.Andreassi M.Andreotti F.Archilli A.Artamonov M.Artuso K.Arzymatov E.Aslanides M.Atzeni B.Audurier S.Bachmann J.J.Back S.Baker V.Balagura W.Baldini A.Baranov R.J.Barlow S.Barsuk W.Barter M.Bartolini F.Baryshnikov J.M.Basels G.Bassi V.Batozskaya B.Batsukh A.Battig A.Bay M.Becker F.Bedeschi I.Bediaga A.Beiter L.J.Bel V.Belavin S.Belin V.Bellee K.Belous I.Belyaev G.Bencivenni E.Ben-Haim S.Benson S.Beranek A.Berezhnoy *** D.Berninghoff H.C.Bernstein C.Bertella E.Bertholet A.Bertolin C.Betancourt F.Betti M.O.Bettler Ia.Bezshyiko S.Bhasin J.Bhom M.S.Bieker S.Bifani P.Billoir A.Bizzeti M.Bjørn M.P.Blago T.Blake F.Blanc S.Blusk D.Bobulska V.Bocci O.Boente Garcia T.Boettcher A.Boldyrev A.Bondar N.Bondar S.Borghi M.Borisyak M.Borsato J.T.Borsuk T.J.V.Bowcock C.Bozzi M.J.Bradley S.Braun A.Brea Rodriguez M.Brodski J.Brodzicka A.Brossa Gonzalo D.Brundu E.Buchanan A.Buonaura C.Burr A.Bursche A.Butkevich J.S.Butter J.Buytaert W.Byczynski S.Cadeddu H.Cai R.Calabrese L.Calero Diaz S.Cali R.Calladine M.Calvi M.Calvo Gomez P.Camargo Magalhaes A.Camboni P.Campana D.H.Campora Perez A.F.Campoverde Quezada L.Capriotti A.Carbone G.Carboni R.Cardinale A.Cardini I.Carli P.Carniti K.Carvalho Akiba A.Casais Vidal G.Casse M.Cattaneo G.Cavallero S.Celani R.Cenci J.Cerasoli M.G.Chapman M.Charles Ph.Charpentier G.Chatzikonstantinidis M.Chefdeville V.Chekalina C.Chen S.Chen A.Chernov S.-G.Chitic V.Chobanova S.Cholak M.Chrzaszcz A.Chubykin P.Ciambrone M.F.Cicala X.Cid Vidal G.Ciezarek F.Cindolo P.E.L.Clarke M.Clemencic H.V.Cliff J.Closier J.L.Cobbledick V.Coco J.A.B.Coelho J.Cogan E.Cogneras L.Cojocariu P.Collins T.Colombo A.Comerma-Montells A.Contu N.Cooke G.Coombs S.Coquereau G.Corti C.M.Costa Sobral B.Couturier D.C.Craik J.Crkovska A.Crocombe M.Cruz Torres R.Currie C.L.Da Silva E.Dall'Occo J.Dalseno C.D' Centro Brasileiro de Pesquisas Físicas(CBPF) Rio de JaneiroBrazil Universidade Federal do Rio de Janeiro(UFRJ) Rio de JaneiroBrazil Center for High Energy Physics Tsinghua UniversityBeijingChina School of Physics state Key Laboratory of Nuclear Physics and Technology Peking UniversityBeijingChina university of Chinese Academy of sciences BeijingChina Institute Of High Energy Physics(IHEP) BeijingChina Institute of Particle Physics Central China Normal UniversityWuhanHubeiChina Univ.Grenoble Alpes Univ.Savoie Mont BlancCNRSIN2P3-LAPPAnnecyFrance UniversitéClermont Auvergne CNRS/IN2P3LPCClermont-FerrandFrance Aix Marseille Univ CNRS/IN2P3CPPMMarseilleFrance LAL Univ.Paris-SudCNRS/IN2P3UniversitéParis-SaclayOrsayFrance LPNHE Sorbonne UniversitéParis Diderot Sorbonne Paris CitéCNRS/IN2P3ParisFrance I.Physikalisches Institut RWTH Aachen UniversityAachenGermany Fakultät Physik Technische Universität DortmundDortmundGermany Max-Planck-Institut für Kernphysik(MPIK) HeidelbergGermany Physikalisches Institut Ruprecht-Karls-Universität HeidelbergHeidelbergGermany School of Physics University College DublinDublinIreland INFN Sezione di Bari BariItaly INFN Sezione di Bologna BolognaItaly INFN Sezione di Ferrara FerraraItaly INFN Sezione di Firenze FirenzeItaly INFN Laboratori Nazionali di Frascati FrascatiItaly INFN Sezione di Genova GenovaItaly INFN Sezione di Milano-Bicocca MilanoItaly INFN Sezione di Milano MilanoItaly INFN Sezione di Cagliari MonserratoItaly INFN Sezione di Padova PadovaItaly INFN Sezione di Pisa PisaItaly INFN Sezione di Roma Tor Vergata RomaItaly INFN Sezione di Roma La Sapienza RomaItaly Nikhef National Institute for Subatomic Physics AmsterdamNetherlands Nikhef National Institute for Subatomic Physics and VU university Amsterdam AmsterdamNetherlands Henryk Niewodniczanski Institute of Nuclear Physics Polish Academy of sciences KrakówPoland AGH-university of science and Technology Faculty of Physics and Applied Computer ScienceKrakówPoland Nationa

The production of ■baryons in proton-proton collisions at a centre-of-mass energy of √s = 13 TeV is measured in the transverse-momentum range 4 详细信息

The production of ■baryons in proton-proton collisions at a centre-of-mass energy of √s = 13 TeV is measured in the transverse-momentum range 4

关键词： doubly charmed baryons hadron production QCD

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Spectral Matching Classification Method of Multi-state Similar Pigments Based on Feature Differences

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computer Modeling in Engineering & sciences 2022年第4期131卷 513-527页

作者： Meng Da Huiqin Wang Ke Wang Zhan Wang Xi’an university of Architecture and Technology Xi’an710055China Shaanxi Provincial Institute of Cultural Relics Protection Xi’an710075China

The properties of the same pigments in murals are affected by different concentrations and particle diameters,which cause the shape of the spectral reflectance data curve to vary,thus influencing the outcome of matching *** paper proposes a spectral matching classification method of multi-state similar pigments based on feature *** principal component analysis(FPCA)was used to calculate the eigenvalue variance of pigment spectral reflectance,then applied to the original reflectance values for parameter *** first projected the original spectral reflectance from the spectral space to the characteristic variance space to identify the spectral ***,the relative distance between the eigenvalues in the eigen variance space is combined with the JS(Jensen-Shannon)divergence to express the difference between the two spectral *** JS information divergence calculates the relative distance between the *** results showthat our classification method can be used to identify the spectral curves of the same pigment under different *** value of the root means square error(RMSE)decreased by 12.0817,while the mean values of the mean absolute percentage error(MAPE)and R2 increased by 0.0965 and 0.2849,*** with the traditional spectral matching algorithm,the recognition error was effectively reduced.

关键词： Fast principal component analysis paint samples reflectivity information divergence feature variance

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