LEADER 03648nam 2200625 450 001 9910828100003321 005 20230807210329.0 024 7 $a10.1515/9781618111067 035 $a(CKB)2670000000612666 035 $a(EBL)3110577 035 $a(SSID)ssj0001559140 035 $a(PQKBManifestationID)16185830 035 $a(PQKBTitleCode)TC0001559140 035 $a(PQKBWorkID)14820014 035 $a(PQKB)10571075 035 $a(MiAaPQ)EBC3110577 035 $a(DE-B1597)541089 035 $a(OCoLC)1058753229 035 $a(DE-B1597)9781618111067 035 $a(Au-PeEL)EBL3110577 035 $a(CaPaEBR)ebr11052461 035 $a(CaONFJC)MIL777113 035 $a(OCoLC)908243758 035 $a(EXLCZ)992670000000612666 100 $a20150515h20152015 uy 0 101 0 $aeng 135 $aurun#---|u||u 181 $ctxt 182 $cc 183 $acr 200 10$aVygotsky & Bernstein in the light of Jewish tradition /$fAntonella Castelnuovo, Bella Kotik-Friedgut ; preface by Clotilde Pontecorvo 210 1$aBoston, [Massachusetts] :$cAcademic Studies Press,$d2015. 210 4$d©2015 215 $a1 online resource (225 p.) 225 1 $aJudaism and Jewish Life 300 $aDescription based upon print version of record. 311 $a1-61811-106-X 311 $a1-936235-58-7 320 $aIncludes bibliographical references and index. 327 $tFront matter --$tContents --$tList of Illustrations --$tAcknowledgements --$tIntroduction /$rPontecorvo, Clotilde --$tPrelude to the Inquiry /$rCastelnuovo, Antonella --$tPart I. Jews and Judaism in Diaspora --$tChapter 1. Jews in Scientific Professions: A Quest for a Methodological Inquiry /$rCastelnuovo, Antonella / Kotik-Friedgut, Bella --$tChapter 2. The Conditions of Jews in Diaspora /$rCastelnuovo, Antonella --$tChapter 3. Judaism: The Unifying Principles /$rCastelnuovo, Antonella --$tPart II. Biographies of Life and Ideas --$tChapter 4. The Jewish Influence in Vygotsky's Life and Ideas /$rKotik-Friedgut, Bella --$tChapter 5. Vygotsky's Creative Work /$rKotik-Friedgut, Bella --$tChapter 6. Bernstein's Life and Work in the Light of Jewish Tradition /$rCastelnuovo, Antonella --$t7. Bernstein: Toward the Unifying Principle /$rCastelnuovo, Antonella --$tPart III. Implementation and Epilogue --$tChapter 8. Bernstein and Biblical Discourse /$rCastelnuovo, Antonella --$tChapter 9. Epilogue /$rCastelnuovo, Antonella / Kotik-Friedgut, Bella --$tBibliography --$tIndex 330 $aVygotsky & Bernstein in the Light of Jewish Tradition examines the role that Jewish cultural tradition played in the work of the Russian psychologist Lev S. Vygotsky and the British sociologist Basil Bernstein by highlighting aspects of their respective lives and theories revealing significant influences of Jewish thoughts and beliefs. The authors demonstrate that theories and human life are dialectically interconnected: what research can reveal about a man can also provide a better understanding of the very nature of his theory. This book is a valuable resource for psychologists, sociologists and students interested in the sociocultural formation of mind. 410 0$aJudaism and Jewish life. 606 $aJews$xCivilization 615 0$aJews$xCivilization. 676 $a150.92 700 $aCastelnuovo$b Antonella$0734907 702 $aKotik-Friedgut$b Bella 702 $aPontecorvo$b Clotilde 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910828100003321 996 $aVygotsky & Bernstein in the light of Jewish tradition$94011845 997 $aUNINA LEADER 10922nam 22004693 450 001 9910861045203321 005 20240407090434.0 010 $a0-7503-4545-4 035 $a(MiAaPQ)EBC31253048 035 $a(Au-PeEL)EBL31253048 035 $a(CKB)31356169900041 035 $a(EXLCZ)9931356169900041 100 $a20240407d2021 uy 0 101 0 $aeng 135 $aurcnu|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aHigh Performance Computing for Intelligent Medical Systems 205 $a1st ed. 210 1$aBristol :$cInstitute of Physics Publishing,$d2021. 210 4$d©2021. 215 $a1 online resource (323 pages) 225 1 $aIOP Ebooks Series 311 $a0-7503-3816-4 327 $aIntro -- Preface -- Acknowledgements -- Editors biographies -- Varun Bajaj -- Irshad Ahmad Ansari -- Contributors biographies -- Ms Athena Abrishamchi -- Fatame Bafande -- Hussain Ahmed Choudhury -- Sengul Dogan -- Vandana Dubey -- Fatih Ertam -- Jamal Esmaelpoor -- Harsh Goud -- Kapil Gupta -- Lalita Gupta -- Smith K Khare -- Rajesh Kumar -- Wahengbam Kanan Kumar -- Gaurav Makwana -- Miguel Ángel Mañanas -- Hamid Reza Marateb -- Arezoo Mirshamsi -- Mohammad Reza Mohebbian -- Mohammad Hassan Moradi -- Kishorjit Nongmeikapam -- Saurabh Pal -- Antti Rissanen -- Marjo Rissanen -- Kalle Saastamoinen -- Zahra Momayez Sanat -- Prakash Chandra Sharma -- Mehdi Shirzadi -- Aheibam Dinamani Singh -- Mithlesh Prasad Singh -- Nidul Sinha -- Abdulhamit Subasi -- Turker Tuncer -- Amit Kumar Verma -- Dhyan Chandra Yadav -- Ram Narayan Yadav -- Shadi Zamani -- Chapter 1 Automatic detection of hypertension by flexible analytic wavelet transform using electrocardiogram signals -- 1.1 Introduction -- 1.1.1 Various intervals of ECG -- 1.1.2 Related work -- 1.2 Methodology -- 1.2.1 Dataset -- 1.2.2 Flexible analytic wavelet transform -- 1.2.3 Feature extraction -- 1.2.4 Classification techniques -- 1.2.5 Performance parameters -- 1.3 Results -- 1.4 Conclusion -- References -- Chapter 2 Computational intelligence in surface electromyogram signal classification -- 2.1 Introduction -- 2.2 Computational intelligence in biomedical signal processing -- 2.3 Background -- 2.3.1 Discrete cosine transform -- 2.3.2 Fast Fourier transform -- 2.3.3 Singular value decomposition -- 2.3.4 Ternary pattern -- 2.3.5 Support vector machine -- 2.3.6 Linear discriminant analysis -- 2.3.7 KNN -- 2.3.8 Artificial neural network -- 2.4 Spider network -- 2.4.1 Pre-processing -- 2.4.2 Feature extraction -- 2.4.3 Feature reduction -- 2.4.4 Feature concatenation -- 2.4.5 Classification. 327 $a2.5 Results and discussions -- 2.5.1 Dataset -- 2.5.2 Experimental results -- 2.5.3 Discussion -- 2.6 Conclusions and suggestions -- References -- Chapter 3 Analysis of IoT interventions to solve voice pathologies challenges -- 3.1 Introduction -- 3.1.1 Pathology assessment -- 3.1.2 Internet of things in voice pathology -- 3.2 Electroglottography -- 3.2.1 Quantitative analysis -- 3.3 Voice pathology datasets -- 3.3.1 Voice ICar fEDerico II (VOICED) -- 3.3.2 Massachusetts eye and ear infirmary -- 3.3.3 Saarbruecken Voice Database -- 3.3.4 Arabic voice pathology database -- 3.4 Acoustic speech features with machine learning for voice pathology classification -- 3.4.1 Feature extraction techniques -- 3.4.2 Voice pathology analysis and detection techniques -- 3.5 Discussion and conclusion -- References -- Chapter 4 Deep learning for cuffless blood pressure monitoring -- 4.1 Introduction -- 4.2 Physiological models -- 4.3 Data source -- 4.3.1 Preprocessing procedures -- 4.4 Deep learning models for blood pressure monitoring -- 4.4.1 LSTM model -- 4.4.2 PCA-LSTM model -- 4.4.3 Convolutional neural network model -- 4.4.4 CNN-LSTM model -- 4.5 Discussion -- 4.5.1 Comparison with other methods -- 4.6 Conclusion -- References -- Chapter 5 Reliability of machine learning methods for diagnosis and prognosis during the COVID-19 pandemic: a comprehensive critical review -- 5.1 Introduction -- 5.2 Methods -- 5.2.1 January-March -- 5.2.2 April-June -- 5.2.3 July-September -- 5.2.4 October 2020 to February 2021 -- 5.2.5 Machine learning methods -- 5.2.6 Critical issues -- 5.3 Conclusion and future scope -- References -- Chapter 6 Forecasting confirmed cases of Corona patients in India using regression and Gaussian analysis -- 6.1 Introduction -- 6.2 Regression analysis in machine learning -- 6.3 Related work -- 6.4 Methodology -- 6.4.1 Data description -- 6.5 Results. 327 $a6.6 Discussion -- 6.7 Conclusion -- Acknowledgments -- References -- Chapter 7 A model for advanced patient feedback procedures in diagnostics -- 7.1 Introduction -- 7.2 Focus on diagnostics -- 7.2.1 Diagnostic error as a concept -- 7.2.2 Diagnostic errors in healthcare -- 7.2.3 Common reasons for diagnostic failures -- 7.2.4 Preventing diagnostic errors in cooperation with patients -- 7.3 Diagnostics and safety challenges in healthcare -- 7.3.1 Patient safety and equity challenges -- 7.3.2 Enhanced patient safety with rational cost control policy -- 7.4 Importance of patient feedback in the diagnostics phase -- 7.4.1 Need for timely feedback -- 7.4.2 The role of timely feedback -- 7.5 The challenges of diagnostics-centered clients' feedback -- 7.6 Enhancing technology acceptance in system development -- 7.7 Phases of diagnostics and the requirements for doctors -- 7.7.1 Requirements for competence and compassion -- 7.7.2 Diagnostic process from the view of doctors -- 7.7.3 Diagnostic process from the view of patients -- 7.8 A model for instant patient feedback -- 7.8.1 General principles -- 7.8.2 Structure of the model -- 7.8.3 Patient management with the model -- 7.8.4 Meaning of the fixed format phase of the model-phase 1 -- 7.8.5 Meaning and management of the free format phase-phase 2 -- 7.8.6 Clients' opinions of the feedback delivery system-phase 3 -- 7.9 Client feedback as a translational development challenge -- 7.9.1 Enhancing process synergy in organizations -- 7.9.2 Maturing and validating patient-targeted feedback systems -- 7.10 Conclusion -- References -- Chapter 8 Soft computing techniques for efficient processing of large medical data -- 8.1 Introduction -- 8.2 Understanding the concept: video compression -- 8.3 Image compression standards -- 8.3.1 JPEG -- 8.3.2 JPEG2000 -- 8.3.3 JPEG-LS -- 8.3.4 JPEG-XR -- 8.3.5 H.265. 327 $a8.3.6 Types of coding and frames -- 8.4 Motion estimation and the necessity of it in video coding? -- 8.4.1 Forward and backward motion estimation -- 8.4.2 Block matching concept -- 8.5 What is soft computing: techniques and differences -- 8.6 Standard techniques for motion estimation -- 8.7 Soft computing techniques for motion estimation -- 8.8 Conceptual terms used in different SC techniques -- 8.8.1 Chromosomes and genes -- 8.8.2 Chromosome representation -- 8.8.3 Cross-over -- 8.8.4 Mutation -- 8.8.5 Weighting function and PBME -- 8.9 Some well-established soft computing based BMA -- 8.9.1 Genetic algorithm-BMA -- 8.9.2 Inter-block/inter-frame fuzzy search algorithm -- 8.9.3 Basic block-matching using particle swarm optimization -- 8.9.4 Harmony search block matching algorithm -- 8.9.5 Cat swarm optimization (CSO-BMA) -- 8.9.6 CUCKOO search based BMA (CS-BMA) -- 8.9.7 The ABC-BM algorithm -- 8.9.8 ABC-DE -- 8.9.9 HS-DE based BMA -- 8.9.10 'Deterministically starting-GA' (GADet) -- 8.9.11 Enhanced Grey-wolf optimizer-BMA (EGWO-BMA) -- 8.9.12 Chessboard search pattern strategy -- 8.10 Results and discussion -- Acknowledgment -- References -- Chapter 9 A comparison of Parkinson's disease prediction using ensemble data mining techniques with features selection methods -- 9.1 Introduction -- 9.2 Related work -- 9.3 Methodology -- 9.3.1 Data description -- 9.3.2 Whisker plotting -- 9.3.3 Histogram plotting -- 9.4 Algorithms description -- 9.4.1 Decision tree -- 9.4.2 Naïve Bayes -- 9.4.3 Random forest -- 9.4.4 Extra tree -- 9.4.5 Bagging ensemble method -- 9.4.6 Features selection method in Parkinson's disease -- 9.5 Results -- 9.5.1 Evaluation of result after prediction on Parkinson's dataset -- 9.5.2 Result of features importance methods -- 9.5.3 Chi-square test -- 9.5.4 Extra tree -- 9.5.5 Heat map. 327 $a9.5.6 Evaluation of results after features selection -- 9.6 Discussion -- 9.7 Conclusion -- Acknowledgments -- References -- Chapter 10 A comparative analysis of image enhancement techniques for detection of microcalcification in screening mammogram -- 10.1 Introduction -- 10.2 Image enhancement in spatial domain -- 10.2.1 Histogram modeling -- 10.2.2 Histogram equalization -- 10.2.3 Histogram matching -- 10.2.4 Averaging filter -- 10.2.5 Gaussian filter -- 10.2.6 Median filter -- 10.3 Image enhancement in frequency domain -- 10.3.1 Butterworth filtering -- 10.3.2 Gaussian low-pass filter -- 10.3.3 Homomorphic filtering -- 10.3.4 Discrete wavelet transform -- 10.4 Convolutional neural network -- 10.5 Evaluation criteria -- 10.5.1 Mean square error -- 10.5.2 Peak signal-to-noise ratio -- 10.5.3 SNR -- 10.5.4 Mean -- 10.5.5 Variance -- 10.6 Results and discussion -- 10.7 Conclusion -- References -- Chapter 11 Computational intelligence for eye disease detection -- 11.1 Introduction -- 11.2 Anatomy of the eye -- 11.2.1 The cornea -- 11.2.2 The human retina -- 11.3 Retinal diseases -- 11.3.1 Retinal tear -- 11.3.2 Diabetic retinopathy -- 11.3.3 Macula hole -- 11.3.4 Degeneration of the macula -- 11.3.5 Disorders of the optic nerve -- 11.3.6 Glaucoma -- 11.3.7 Diabetic macular edema -- 11.3.8 Retinopathy of prematurity -- 11.4 History of retinal imaging -- 11.5 Current status of retinal analysis -- 11.5.1 Fundus imaging -- 11.5.2 Optical coherence tomography -- 11.6 Disease specific analysis of retinal images -- 11.6.1 Early detection of retinal disease from fundus photography -- 11.6.2 Early detection of systemic disease from fundus photography -- 11.6.3 3-Dimensional OCT and retinal diseases-image guided therapy -- 11.7 Fundus image analysis -- 11.7.1 Glaucoma detection using retinal imaging -- 11.7.2 Dementia detection using retinal imaging. 327 $a11.7.3 Heart diseases detection using retinal imaging. 330 $aThe interface of high-performance computing, computational intelligence and medical science creates intelligent medical systems which offer significant improvements in the quality of life and efficacy of clinical treatment. This book reviews advances and applications of high-performance computing for medical applications. 410 0$aIOP Ebooks Series 700 $aBajaj$b Varun$01741363 701 $aAnsari$b Irshad Ahmad$01741364 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910861045203321 996 $aHigh Performance Computing for Intelligent Medical Systems$94167368 997 $aUNINA LEADER 01473nam 22004333 450 001 9911021969803321 005 20250901121911.0 010 $a3-031-96138-2 035 $a(MiAaPQ)EBC32274335 035 $a(Au-PeEL)EBL32274335 035 $a(CKB)40630388200041 035 $a(OCoLC)1535402942 035 $a(EXLCZ)9940630388200041 100 $a20250901d2025 uy 0 101 0 $aita 135 $aurcnu|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aRiattivazione Dell'Ambiente Costruito $eDalla Teoria Alla Pratica 205 $a1st ed. 210 1$aCham :$cSpringer,$d2025. 210 4$d©2025. 215 $a1 online resource (163 pages) 311 08$a3-031-96137-4 330 $aIl libro si occupa di riattivazione urbana, una particolare forma di intervento sul costruito, che oltre alla dimensione fisico-spaziale dei luoghi considera anche e soprattutto le dinamiche sociali e relazionali che l'intervento è in grado di attivare. 700 $aFanzini$b Daniele$0732701 701 $aVenturini$b Gianpiero$01845300 701 $aZreika$b Nour$01845301 701 $aCelaschi$b Flaviano$011096 701 $aZannoni$b Michele$01831012 701 $aCattabriga$b Andrea$01845302 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9911021969803321 996 $aRiattivazione Dell'Ambiente Costruito$94429170 997 $aUNINA