LEADER 03399oam 2200505K 450 001 9910150349303321 005 20240501155708.0 010 $a1-317-20562-6 010 $a1-138-67193-2 010 $a1-315-61666-1 024 7 $a10.4324/9781315616667 035 $a(CKB)3710000000932720 035 $a(MiAaPQ)EBC4741408 035 $a970389660 035 $a(OCoLC)962752344 035 $a(OCoLC-P)962752344 035 $a(FlBoTFG)9781315616667 035 $a(EXLCZ)993710000000932720 100 $a20161116d2017 uy 0 101 0 $aeng 135 $aurcnu---unuuu 181 $2rdacontent 182 $2rdamedia 183 $2rdacarrier 200 10$aProgramming behavioral experiments with MATLAB and Psychtoolbox $e9 simple steps for students and researchers /$fErman Misirlisoy 205 $a1st ed. 210 1$aAbingdon, Oxon ;$aNew York, NY :$cRoutledge,$d2017. 215 $a1 online resource (81 pages) $cillustrations 311 08$a1-138-67192-4 311 08$a1-317-20563-4 320 $aIncludes bibliographical references at the end of each chapters and index. 327 $astep 0. Preliminary notes -- step 1. Initialisation -- step 2. Setting parameters and opening up variables to store experimental conditions and data -- step 3. Executing for loops to iterate through trials -- step 4. Using if statements to define trials and present stimuli -- step 5. Presenting stimuli and recording responses -- step 6. Saving data -- step 7. Debugging, optimisation and functions -- step 8. Testing and 'sanity checks' on data -- step 9. The basics of data analysis. 330 $aHuman behavior is fascinating so it's no surprise that psychologists and neuroscientists spend their lives designing rigorous experiments to understand it. MATLAB is one of the most widely used pieces of software for designing and running behavioral experiments, and it opens up a world of quick and flexible experiment programming. This book offers a step-by-step guide to using MATLAB with Psychtoolbox to create customisable experiments. Its pocket size and simple language allow you to get straight to the point and help you to learn fast in order to complete your work in great time. Innine simple steps, it guides you all the way from setting parameters for your experiment to analysing the output. Gone are the daunting days of working through hundreds of irrelevant and complicated documents, as in this handy book, Erman Misirlisoy coaxes you in the right direction with his friendly and encouraging tricks and tips. If you want to learn how to develop your own experiments to collect and analyse behavioral data, then this book is a must-read. Whether you are a student in experimental psychology, a researcher in cognitive neuroscience, or simply someone who wants to run behavioral tasks on your friends for fun, this book will offer you the skills to succeed. 606 $aPsychology$xExperiments$xComputer programs 606 $aPsychology$xExperiments$xData processing 615 0$aPsychology$xExperiments$xComputer programs. 615 0$aPsychology$xExperiments$xData processing. 676 $a150.285/53 700 $aMisirlisoy$b Erman$0896259 801 0$bOCoLC-P 801 1$bOCoLC-P 906 $aBOOK 912 $a9910150349303321 996 $aProgramming behavioral experiments with MATLAB and Psychtoolbox$92002068 997 $aUNINA LEADER 04879nam 22006615 450 001 9910483661103321 005 20251225174925.0 010 $a3-030-73696-2 024 7 $a10.1007/978-3-030-73696-5 035 $a(CKB)4100000011881099 035 $a(MiAaPQ)EBC6543740 035 $a(Au-PeEL)EBL6543740 035 $a(OCoLC)1246482751 035 $a(PPN)255290667 035 $a(BIP)79815095 035 $a(BIP)79431901 035 $a(DE-He213)978-3-030-73696-5 035 $a(EXLCZ)994100000011881099 100 $a20210408d2021 u| 0 101 0 $aeng 135 $aurcnu|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aCombating Online Hostile Posts in Regional Languages during Emergency Situation $eFirst International Workshop, CONSTRAINT 2021, Collocated with AAAI 2021, Virtual Event, February 8, 2021, Revised Selected Papers /$fedited by Tanmoy Chakraborty, Kai Shu, H. Russell Bernard, Huan Liu, Md Shad Akhtar 205 $a1st ed. 2021. 210 1$aCham :$cSpringer International Publishing :$cImprint: Springer,$d2021. 215 $a1 online resource (268 pages) 225 1 $aCommunications in Computer and Information Science,$x1865-0937 ;$v1402 311 08$a3-030-73695-4 327 $aIdentifying Offensive Content in Social Media Posts -- Identification and Classification of Textual Aggression in Social Media: Resource Creation and Evaluation -- Fighting an Infodemic: COVID-19 Fake News Dataset -- Revealing the Blackmarket Retweet Game: A Hybrid Approach -- Overview of CONSTRAINT 2021 Shared Tasks: Detecting English COVID-19 Fake News and Hindi Hostile Posts -- LaDiff ULMFiT: A Layer Differentiated training approach for ULMFiT -- Extracting latent information from datasets in The CONSTRAINT-2020 shared task on the hostile post detection -- Fake news and hostile posts detection using an ensemble learning model -- Transformer-based Language Model Fine-tuning Methods for COVID-19 Fake News Detection -- Tackling the infodemic : Analysis using Transformer based models -- Exploring Text-transformers in AAAI 2021 Shared Task: COVID-19 Fake News Detection in English -- g2tmn at Constraint@AAAI2021: Exploiting CT-BERT and Ensembling Learning for COVID-19 Fake News Detection -- Model Generalization on COVID-19 Fake News Detection -- ECOL: Early Detection of COVID Lies Using Content, Prior Knowledge and Source Information -- Evaluating Deep Learning Approaches for Covid19 Fake News Detection -- A Heuristic-driven Ensemble Framework for COVID-19 Fake News Detection -- Identification of COVID-19 related Fake News via Neural Stacking -- Fake News Detection System using XLNet model with Topic Distributions: CONSTRAINT@AAAI2021 Shared Task -- Coarse and Fine-Grained Hostility Detection in Hindi Posts using Fine Tuned Multilingual Embeddings -- Hostility Detection in Hindi leveraging Pre-Trained Language Models -- Stacked embeddings and multiple fine-tuned XLM-RoBERTa models for Enhanced hostility identification -- Task Adaptive Pretraining of Transformers for Hostility Detection -- Divide and Conquer: An Ensemble Approach for Hostile Post Detection in Hindi. 330 $aThis book constitutes selected and revised papers from the First International Workshop on Combating On line Ho st ile Posts in Regional Languages dur ing Emerge ncy Si tuation, CONSTRAINT 2021, Collocated with AAAI 2021, held as virtual event, in February 2021. The 14 full papers and 9 short papers presented were thoroughly reviewed and selected from 62 qualified submissions. The papers present interdisciplinary approaches on multilingual social media analytics and non-conventional ways of combating online hostile posts. 410 0$aCommunications in Computer and Information Science,$x1865-0937 ;$v1402 606 $aDatabase management 606 $aArtificial intelligence 606 $aSocial sciences$xData processing 606 $aApplication software 606 $aDatabase Management System 606 $aArtificial Intelligence 606 $aComputer Application in Social and Behavioral Sciences 606 $aComputer and Information Systems Applications 615 0$aDatabase management. 615 0$aArtificial intelligence. 615 0$aSocial sciences$xData processing. 615 0$aApplication software. 615 14$aDatabase Management System. 615 24$aArtificial Intelligence. 615 24$aComputer Application in Social and Behavioral Sciences. 615 24$aComputer and Information Systems Applications. 676 $a155.418 702 $aChakraborty$b Tanmoy 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910483661103321 996 $aCombating online hostile posts in regional languages during emergency situation$91901758 997 $aUNINA