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Author | Title | Accn# | Year | Item Type | Claims |
| 1 |
Lin, Kang-Ping |
Future Trends and Challenges of Molecular Imaging and AI Innovation |
I12506 |
2022 |
Book |
|
| 2 |
Martin Perez, Cristina |
Search for the Higgs Boson Produced in Association with Top Quarks with the CMS Detector at the LHC |
I12497 |
2022 |
Book |
|
| 3 |
Abaimov, Stanislav |
Machine Learning for Cyber Agents |
I12486 |
2022 |
Book |
|
| 4 |
Guo, Huaqun |
IRC-SET 2021 |
I12441 |
2022 |
Book |
|
| 5 |
Madenci, Erdogan |
Advances in Peridynamics |
I12400 |
2022 |
Book |
|
| 6 |
Moriwaki, Kana |
Large-Scale Structure of the Universe |
I12304 |
2022 |
Book |
|
| 7 |
Andrejevic, Nina |
Machine Learning-Augmented Spectroscopies for Intelligent Materials Design |
I12242 |
2022 |
Book |
|
| 8 |
Banerjee, Santo |
Nonlinear Dynamics and Applications |
I12233 |
2022 |
Book |
|
| 9 |
Jiang, Richard |
Big Data Privacy and Security in Smart Cities |
I12193 |
2022 |
Book |
|
| 10 |
Bhatawdekar, Ramesh M |
Environmental Issues of Blasting |
I11955 |
2021 |
eBook |
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1.
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| Title | Future Trends and Challenges of Molecular Imaging and AI Innovation : Proceedings of FASMI 2020 |
| Author(s) | Lin, Kang-Ping;Liu, Ren-Shyan;Yang, Bang-Hung |
| Publication | Cham, 1. Imprint: Springer
2. Springer International Publishing, 2022. |
| Description | XI, 90 p. 42 illus., 36 illus. in color : online resource |
| Abstract Note | This volumes presents the proceedings of the FASMI 2020 conference, held at Taipei Veterans General Hospital on November 20-22, 2020. It presents contributions on all aspects of molecular imaging, discovered by leading academic scientists and researchers. It also provides a premier interdisciplinary treatment of recent innovations, trend, and concerns as well as practical challenges and solutions in Molecular Imaging and put an emphasis on Artificial Intelligence applied to Imaging Data. FASMI is the annual meeting of the Federation of Asian Societies for Molecular Imaging |
| ISBN,Price | 9783030927868 |
| Keyword(s) | 1. Biology???Research
2. Biomedical engineering
3. Biomedical Engineering and Bioengineering
4. Biomedical Research
5. BIOPHYSICS
6. EBOOK
7. EBOOK - SPRINGER
8. MACHINE LEARNING
9. MEASUREMENT
10. Measurement Science and Instrumentation
11. MEASURING INSTRUMENTS
12. Medicine???Research
|
| Item Type | Book |
Multi-Media Links
Please Click here for eBook
Circulation Data
| Accession# | |
Call# | Status | Issued To | Return Due On | Physical Location |
| I12506 |
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On Shelf |
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2.
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| Title | Search for the Higgs Boson Produced in Association with Top Quarks with the CMS Detector at the LHC |
| Author(s) | Martin Perez, Cristina |
| Publication | Cham, 1. Imprint: Springer
2. Springer International Publishing, 2022. |
| Description | XIII, 283 p. 170 illus., 158 illus. in color : online resource |
| Abstract Note | In this book, the interaction between the Higgs boson and the top quark is studied with the CMS detector at the LHC via the search for the associate production of the Higgs boson with one (tH) or two (ttH) top quarks. These processes are very rare and thus a high particle selection efficiency by the trigger system is essential. The selection of hadronically decaying tau leptons, expected from the Higgs boson decays, is tackled in the first part, where the trigger is optimized for Run 2 and Run 3 and a novel machine-learning based trigger for the High-Luminosity LHC is developed. The second part presents the analysis of tH and ttH where the Higgs boson decays into tau leptons, W or Z bosons with Run 2 data. The presence of multiple particles in the final state leads to the use of multivariant discriminants based on machine learning and the Matrix Element Method. The sophisticated methods used and the unprecedented amount of data result in the most precise cross section measurements to date |
| ISBN,Price | 9783030902063 |
| Keyword(s) | 1. Data Analysis and Big Data
2. EBOOK
3. EBOOK - SPRINGER
4. Elementary particles (Physics)
5. Elementary Particles, Quantum Field Theory
6. MACHINE LEARNING
7. Quantitative research
8. QUANTUM FIELD THEORY
|
| Item Type | Book |
Multi-Media Links
Please Click here for eBook
Circulation Data
| Accession# | |
Call# | Status | Issued To | Return Due On | Physical Location |
| I12497 |
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On Shelf |
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3.
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| Title | Machine Learning for Cyber Agents : Attack and Defence |
| Author(s) | Abaimov, Stanislav;Martellini, Maurizio |
| Publication | Cham, 1. Imprint: Springer
2. Springer International Publishing, 2022. |
| Description | XV, 227 p. 27 illus., 23 illus. in color : online resource |
| Abstract Note | The cyber world has been both enhanced and endangered by AI. On the one hand, the performance of many existing security services has been improved, and new tools created. On the other, it entails new cyber threats both through evolved attacking capacities and through its own imperfections and vulnerabilities. Moreover, quantum computers are further pushing the boundaries of what is possible, by making machine learning cyber agents faster and smarter. With the abundance of often-confusing information and lack of trust in the diverse applications of AI-based technologies, it is essential to have a book that can explain, from a cyber security standpoint, why and at what stage the emerging, powerful technology of machine learning can and should be mistrusted, and how to benefit from it while avoiding potentially disastrous consequences. In addition, this book sheds light on another highly sensitive area ??? the application of machine learning for offensive purposes, an aspect that is widely misunderstood, under-represented in the academic literature and requires immediate expert attention |
| ISBN,Price | 9783030915858 |
| Keyword(s) | 1. Computer networks???Security measures
2. Data and Information Security
3. Data protection
4. EBOOK
5. EBOOK - SPRINGER
6. MACHINE LEARNING
7. Mobile and Network Security
8. Security Science and Technology
9. Security systems
|
| Item Type | Book |
Multi-Media Links
Please Click here for eBook
Circulation Data
| Accession# | |
Call# | Status | Issued To | Return Due On | Physical Location |
| I12486 |
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On Shelf |
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4.
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| Title | IRC-SET 2021 : Proceedings of the 7th IRC Conference on Science, Engineering and Technology, August 2021, Singapore |
| Author(s) | Guo, Huaqun;Ren, Hongliang;Wang, Victor;Chekole, Eyasu Getahun;Lakshmanan, Umayal |
| Publication | Singapore, 1. Imprint: Springer
2. Springer Nature Singapore, 2022. |
| Description | XVII, 693 p. 392 illus., 325 illus. in color : online resource |
| Abstract Note | This book highlights contemporary state of research in multidisciplinary areas in computer science, computer engineering, chemical engineering, mechanical engineering, physics, biomedical sciences, life sciences, medicine, and health care. The accepted submissions to the 7th IRC Conference on Science, Engineering and Technology (IRC-SET 2021) that were presented on August 7, 2021, are published in this conference proceedings. The papers presented here were shortlisted after extensive rounds of rigorous reviews by a panel of esteemed individuals who are pioneers and experts in their respective domains |
| ISBN,Price | 9789811698699 |
| Keyword(s) | 1. Applied and Technical Physics
2. Biomaterials
3. Biomedical Devices and Instrumentation
4. Biomedical engineering
5. Biomedical Engineering and Bioengineering
6. EBOOK
7. EBOOK - SPRINGER
8. MACHINE LEARNING
9. Nanoengineering
10. NANOTECHNOLOGY
11. PHYSICS
|
| Item Type | Book |
Multi-Media Links
Please Click here for eBook
Circulation Data
| Accession# | |
Call# | Status | Issued To | Return Due On | Physical Location |
| I12441 |
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On Shelf |
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5.
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| Title | Advances in Peridynamics |
| Author(s) | Madenci, Erdogan;Roy, Pranesh;Behera, Deepak |
| Publication | Cham, 1. Imprint: Springer
2. Springer International Publishing, 2022. |
| Description | XVI, 421 p. 240 illus., 234 illus. in color : online resource |
| Abstract Note | This book presents recent improvements in peridynamic modeling of structures. It provides sufficient theory and numerical implementation helpful to both new and existing researchers in the field. The main focus of the book is on the non-ordinary state-based (NOSB) peridynamics (PD) and its applications for performing finite deformation. It presents the framework for modeling high stretch polymers, viscoelastic materials, thermoelasticity, plasticity, and creep. It provides a systematic derivation for dimensionally reduced structures such as axisymmetric structures and beams. Also, it presents a novel approach to impose boundary conditions without suffering from displacement kinks near the boundary. Furthermore, it presents refinements to bond-based PD model by including rotation kinematics for modeling isotropic and composite materials. Moreover, it presents a PD ??? FEM coupling framework in ANSYS based on principle for virtual work. Lastly, it presents an application of neural networks in the peridynamic (PINN) framework. Sample codes are provided for readers to develop hands-on experience on peridynamic modeling. Describes new developments in peridynamics and their applications in the presence of material and geometric nonlinearity; Describes an approach to seamlessly couple PD with FE; Introduces the use of the neural network in the PD framework to solve engineering problems; Provides theory and numerical examples for researchers and students to self-study and apply in their research (Codes are provided as supplementary material); Provides theoretical development and numerical examples suitable for graduate courses |
| ISBN,Price | 9783030978587 |
| Keyword(s) | 1. Applied Dynamical Systems
2. DYNAMICS
3. EBOOK
4. EBOOK - SPRINGER
5. ENGINEERING MATHEMATICS
6. ENGINEERING MECHANICS
7. MACHINE LEARNING
8. MATHEMATICAL PHYSICS
9. Mechanics, Applied
10. NONLINEAR THEORIES
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| Item Type | Book |
Multi-Media Links
Please Click here for eBook
Circulation Data
| Accession# | |
Call# | Status | Issued To | Return Due On | Physical Location |
| I12400 |
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On Shelf |
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6.
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| Title | Large-Scale Structure of the Universe : Cosmological Simulations and Machine Learning |
| Author(s) | Moriwaki, Kana |
| Publication | Singapore, 1. Imprint: Springer
2. Springer Nature Singapore, 2022. |
| Description | XII, 120 p. 46 illus., 44 illus. in color : online resource |
| Abstract Note | Line intensity mapping (LIM) is an observational technique that probes the large-scale structure of the Universe by collecting light from a wide field of the sky. This book demonstrates a novel analysis method for LIM using machine learning (ML) technologies. The author develops a conditional generative adversarial network that separates designated emission signals from sources at different epochs. It thus provides, for the first time, an efficient way to extract signals from LIM data with foreground noise. The method is complementary to conventional statistical methods such as cross-correlation analysis. When applied to three-dimensional LIM data with wavelength information, high reproducibility is achieved under realistic conditions. The book further investigates how the trained machine extracts the signals, and discusses the limitation of the ML methods. Lastly an application of the LIM data to a study of cosmic reionization is presented. This book benefits students and researchers who are interested in using machine learning to multi-dimensional data not only in astronomy but also in general applications |
| ISBN,Price | 9789811958809 |
| Keyword(s) | 1. Astronomy, Observations and Techniques
2. Astronomy???Observations
3. ASTROPHYSICS
4. COSMOLOGY
5. EBOOK
6. EBOOK - SPRINGER
7. MACHINE LEARNING
|
| Item Type | Book |
Multi-Media Links
Please Click here for eBook
Circulation Data
| Accession# | |
Call# | Status | Issued To | Return Due On | Physical Location |
| I12304 |
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On Shelf |
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7.
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| Title | Machine Learning-Augmented Spectroscopies for Intelligent Materials Design |
| Author(s) | Andrejevic, Nina |
| Publication | Cham, 1. Imprint: Springer
2. Springer International Publishing, 2022. |
| Description | XII, 97 p. 29 illus., 28 illus. in color : online resource |
| Abstract Note | The thesis contains several pioneering results at the intersection of state-of-the-art materials characterization techniques and machine learning. The use of machine learning empowers the information extraction capability of neutron and photon spectroscopies. In particular, new knowledge and new physics insights to aid spectroscopic analysis may hold great promise for next-generation quantum technology. As a prominent example, the so-called proximity effect at topological material interfaces promises to enable spintronics without energy dissipation and quantum computing with fault tolerance, yet the characteristic spectral features to identify the proximity effect have long been elusive. The work presented within permits a fine resolution of its spectroscopic features and a determination of the proximity effect which could aid further experiments with improved interpretability. A few novel machine learning architectures are proposed in this thesis work which leverage the case when the data is scarce and utilize the internal symmetry of the system to improve the training quality. The work sheds light on future pathways to apply machine learning to augment experiments |
| ISBN,Price | 9783031148088 |
| Keyword(s) | 1. EBOOK
2. EBOOK - SPRINGER
3. ELECTRONIC DEVICES
4. MACHINE LEARNING
5. SOLID STATE PHYSICS
6. SPECTROSCOPY
7. SPECTRUM ANALYSIS
8. Surfaces (Technology)
9. Surfaces, Interfaces and Thin Film
10. THIN FILMS
|
| Item Type | Book |
Multi-Media Links
Please Click here for eBook
Circulation Data
| Accession# | |
Call# | Status | Issued To | Return Due On | Physical Location |
| I12242 |
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On Shelf |
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8.
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| Title | Nonlinear Dynamics and Applications : Proceedings of the ICNDA 2022 |
| Author(s) | Banerjee, Santo;Saha, Asit |
| Publication | Cham, 1. Imprint: Springer
2. Springer International Publishing, 2022. |
| Description | XXXI, 1474 p. 608 illus., 551 illus. in color : online resource |
| Abstract Note | This book covers recent trends and applications of nonlinear dynamics in various branches of society, science, and engineering. The selected peer-reviewed contributions were presented at the International Conference on Nonlinear Dynamics and Applications (ICNDA 2022) at Sikkim Manipal Institute of Technology (SMIT) and cover a broad swath of topics ranging from chaos theory and fractals to quantum systems and the dynamics of the COVID-19 pandemic. Organized by the SMIT Department of Mathematics, this international conference offers an interdisciplinary stage for scientists, researchers, and inventors to present and discuss the latest innovations and trends in all possible areas of nonlinear dynamics |
| ISBN,Price | 9783030997922 |
| Keyword(s) | 1. BIOINFORMATICS
2. COMPLEX SYSTEMS
3. Computational and Systems Biology
4. DYNAMICAL SYSTEMS
5. EBOOK
6. EBOOK - SPRINGER
7. MACHINE LEARNING
8. PLASMA WAVES
9. Stochastic Networks
10. STOCHASTIC PROCESSES
11. SYSTEM THEORY
12. Waves, instabilities and nonlinear plasma dynamics
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| Item Type | Book |
Multi-Media Links
Please Click here for eBook
Circulation Data
| Accession# | |
Call# | Status | Issued To | Return Due On | Physical Location |
| I12233 |
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On Shelf |
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9.
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| Title | Big Data Privacy and Security in Smart Cities |
| Author(s) | Jiang, Richard;Bouridane, Ahmed;Li, Chang-Tsun;Crookes, Danny;Boussakta, Said;Hao, Feng;A. Edirisinghe, Eran |
| Publication | Cham, 1. Imprint: Springer
2. Springer International Publishing, 2022. |
| Description | VI, 248 p. 74 illus., 65 illus. in color : online resource |
| Abstract Note | This book highlights recent advances in smart cities technologies, with a focus on new technologies such as biometrics, blockchains, data encryption, data mining, machine learning, deep learning, cloud security, and mobile security. During the past five years, digital cities have been emerging as a technology reality that will come to dominate the usual life of people, in either developed or developing countries. Particularly, with big data issues from smart cities, privacy and security have been a widely concerned matter due to its relevance and sensitivity extensively present in cybersecurity, healthcare, medical service, e-commercial, e-governance, mobile banking, e-finance, digital twins, and so on. These new topics rises up with the era of smart cities and mostly associate with public sectors, which are vital to the modern life of people. This volume summarizes the recent advances in addressing the challenges on big data privacy and security in smart cities and points out the future research direction around this new challenging topic |
| ISBN,Price | 9783031044243 |
| Keyword(s) | 1. Big data
2. Biometric identification
3. Biometrics
4. Cooperating objects (Computer systems)
5. Cyber-Physical Systems
6. Data protection???Law and legislation
7. EBOOK
8. EBOOK - SPRINGER
9. MACHINE LEARNING
10. Privacy
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| Item Type | Book |
Multi-Media Links
Please Click here for eBook
Circulation Data
| Accession# | |
Call# | Status | Issued To | Return Due On | Physical Location |
| I12193 |
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On Shelf |
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10.
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| Title | Environmental Issues of Blasting : Applications of Artificial Intelligence Techniques |
| Author(s) | Bhatawdekar, Ramesh M;Armaghani, Danial Jahed;Azizi, Aydin |
| Publication | Singapore, Springer Nature Singapore, 2021. |
| Description | IX, 77 p. 9 illus., 8 illus. in color : online resource |
| Abstract Note | This book gives a rigorous and up-to-date study of the various AI and machine learning algorithms for resolving environmental challenges associated with blasting. Blasting is a critical activity in any mining or civil engineering project for breaking down hard rock masses. A small amount of explosive energy is only used during blasting to fracture rock in order to achieve the appropriate fragmentation, throw, and development of muck pile. The surplus energy is transformed into unfavourable environmental effects such as back-break, flyrock, air overpressure, and ground vibration. The advancement of artificial intelligence and machine learning techniques has increased the accuracy of predicting these environmental impacts of blasting. This book discusses the effective application of these strategies in forecasting, mitigating, and regulating the aforementioned blasting environmental hazards |
| ISBN,Price | 9789811682377 |
| Keyword(s) | 1. Computational Intelligence
2. EBOOK
3. EBOOK - SPRINGER
4. Engineering geology
5. ENVIRONMENTAL MANAGEMENT
6. Geoengineering
7. GEOPHYSICS
8. Geotechnical engineering
9. Geotechnical Engineering and Applied Earth Sciences
10. MACHINE LEARNING
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| Item Type | eBook |
Multi-Media Links
Please Click here for eBook
Circulation Data
| Accession# | |
Call# | Status | Issued To | Return Due On | Physical Location |
| I11955 |
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On Shelf |
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