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Methods and Applications for Modeling and Simulation of Complex Systems: 22nd Asia Simulation Conference, AsiaSim 2023, Langkawi, Malaysia, October 25–26, 2023, Proceedings, Part II (Communications in Computer and Information Science #1912)
by Mohamed Sultan Mohamed Ali Fazilah Hassan Noorhazirah Sunar Mohd Ariffanan Mohd Basri Mohd Saiful Azimi Mahmud Mohamad Hafis Izran IshakThis book constitutes the refereed proceedings of the 22nd Asia Simulation Conference on Methods and Applications for Modeling and Simulation of Complex Systems, AsiaSim 2023, held in Langkawi, Malaysia, during October 25–26, 2023.The 77 full papers included in this book were carefully reviewed and selected from 164 submissions. They were organized in topical sections as follows: Modelling and Simulation, Artificial intelligence, Industry 4.0, Digital Twins Modelling, Simulation and Gaming, Simulation for Engineering, Simulation for Sustainable Development, Simulation in Social Sciences.
Methods and Applications for Modeling and Simulation of Complex Systems: 19th Asia Simulation Conference, AsiaSim 2019, Singapore, October 30 – November 1, 2019, Proceedings (Communications in Computer and Information Science #1094)
by Gary Tan Axel Lehmann Yong Meng Teo Wentong CaiThis volume constitutes the proceedings of the 19th Asia Simulation Conference, AsiaSim 2019, held in Singapore, Singapore, in October 2019.The 19 revised full papers and 5 short papers presented in this volume were carefully reviewed and selected from 36 submissions. The papers are organized in topical sections on simulation and modeling methodology; numerical and Monte Carlo simulation; simulation applications: blockchain, deep learning and cloud; simulation and visualization; simulation applications; short papers.
Methods and Applications for Modeling and Simulation of Complex Systems: 21st Asia Simulation Conference, AsiaSim 2022, Changsha, China, December 9-11, 2022, Proceedings, Part I (Communications in Computer and Information Science #1712)
by Lin Zhang Xiao Song Wenhui Fan Ni LiThe two-volume set CCIS 1712 and 1713 constitutes the proceedings of the 21st Asian Simulation Conference, AsiaSim 2022, which took place in Changsha, China, in January 2023. Due to the Covid pandemic AsiaSim 2022 has been postponed to January 2023. The 97 papers presented in the proceedings were carefully reviewed and selected from 218 submissions. The contributions were organized in topical sections as follows: Modeling theory and methodology; Continuous system/discrete event system/hybrid system/intelligent system modeling and simulation; Complex systems and open, complex and giant systems modeling and simulation; Integrated natural environment and virtual reality environment modeling and simulation; Networked Modeling and Simulation; Flight simulation, simulator, simulation support environment, simulation standard and simulation system construction; High performance computing, parallel computing, pervasive computing, embedded computing and simulation; CAD/CAE/CAM/CIMS/VP/VM/VR/SBA; Big data challenges and requirements for simulation and knowledge services of big data ecosystem; Artificial intelligence for simulation; Application of modeling/simulation in science/engineering/society/economy /management/energy/transportation/life/biology/medicine etc; Application of modeling/simulation in energy saving/emission reduction, public safety, disaster prevention/mitigation; Modeling/simulation applications in the military field; Modeling/simulation applications in education and training; Modeling/simulation applications in entertainment and sports.
Methods and Applications of Algorithmic Complexity: Beyond Statistical Lossless Compression (Emergence, Complexity and Computation #44)
by Hector Zenil Fernando Soler Toscano Nicolas GauvritThis book explores a different pragmatic approach to algorithmic complexity rooted or motivated by the theoretical foundations of algorithmic probability and explores the relaxation of necessary and sufficient conditions in the pursuit of numerical applicability, with some of these approaches entailing greater risks than others in exchange for greater relevance and applicability. Some established and also novel techniques in the field of applications of algorithmic (Kolmogorov) complexity currently coexist for the first time, ranging from the dominant ones based upon popular statistical lossless compression algorithms (such as LZW) to newer approaches that advance, complement, and also pose their own limitations. Evidence suggesting that these different methods complement each other for different regimes is presented, and despite their many challenges, some of these methods are better grounded in or motivated by the principles of algorithmic information. The authors propose that the field can make greater contributions to science, causation, scientific discovery, networks, and cognition, to mention a few among many fields, instead of remaining either as a technical curiosity of mathematical interest only or as a statistical tool when collapsed into an application of popular lossless compression algorithms. This book goes, thus, beyond popular statistical lossless compression and introduces a different methodological approach to dealing with algorithmic complexity. For example, graph theory and network science are classic subjects in mathematics widely investigated in the twentieth century, transforming research in many fields of science from economy to medicine. However, it has become increasingly clear that the challenge of analyzing these networks cannot be addressed by tools relying solely on statistical methods. Therefore, model-driven approaches are needed. Recent advances in network science suggest that algorithmic information theory could play an increasingly important role in breaking those limits imposed by traditional statistical analysis (entropy or statistical compression) in modeling evolving complex networks or interacting networks. Further progress on this front calls for new techniques for an improved mechanistic understanding of complex systems, thereby calling out for increased interaction between systems science, network theory, and algorithmic information theory, to which this book contributes.
Methods and Applications of Artificial Intelligence: Dynamic Response, Learning, Random Forest, Linear Regression, Interoperability, Additive Manufacturing and Mechatronics (ISTE Invoiced)
by Abdelkhalak El HamiArtificial Intelligence (AI) is currently one of the most talked-about technologies, both among scientists and in public media. Several factors have contributed to its development in recent years. The first is access to vast quantities of data, such as in the industrial field, the advent of Industry 4.0, which promotes automation and data sharing in several technologies. Another factor is the continuous improvement in computing power thanks to the development of ever more powerful processors and the optimization of algorithms. With these two limitations removed, the focus of most AI developments is on the quality of predictions. The integration of AI into the industrial domain represents an exciting new frontier for innovation. Just as AI has transformed many other sectors, its application to mechanical technologies enables significant improvements in design, manufacturing and quality control processes: from computer-aided design (CAD) to printing parameter optimization, defect detection and real-time monitoring. This type of technology requires computer systems, data with management systems and advanced algorithms which can be used by AIs. In mechanical engineering, AI offers many possibilities in mechanical construction, predictive maintenance, plant monitoring, robotics, additive manufacturing, materials, vibration, etc. Methods and Applications of Artificial Intelligence is dedicated to the methods and applications of AI in mechanical engineering. Each chapter clearly sets out the techniques used and developed and accompanies them with illustrative examples. The book is aimed at students but is also a valuable resource for practicing engineers and research lecturers.
Methods and Applications of Autonomous Experimentation (Chapman & Hall/CRC Computational Science)
by Marcus M. Noack Daniela UshizimaAutonomous Experimentation is poised to revolutionize scientific experiments at advanced experimental facilities. Whereas previously, human experimenters were burdened with the laborious task of overseeing each measurement, recent advances in mathematics, machine learning and algorithms have alleviated this burden by enabling automated and intelligent decision-making, minimizing the need for human interference. Illustrating theoretical foundations and incorporating practitioners’ first-hand experiences, this book is a practical guide to successful Autonomous Experimentation. Despite the field’s growing potential, there exists numerous myths and misconceptions surrounding Autonomous Experimentation. Combining insights from theorists, machine-learning engineers and applied scientists, this book aims to lay the foundation for future research and widespread adoption within the scientific community. This book is particularly useful for members of the scientific community looking to improve their research methods but also contains additional insights for students and industry professionals interested in the future of the field.
Methods and Experimental Techniques in Computer Engineering
by Francesco Amigoni Viola SchiaffonatiComputing and science reveal a synergic relationship. On the one hand, it is widely evident that computing plays an important role in the scientific endeavor. On the other hand, the role of scientific method in computing is getting increasingly important, especially in providing ways to experimentally evaluate the properties of complex computing systems. This book critically presents these issues from a unitary conceptual and methodological perspective by addressing specific case studies at the intersection between computing and science. The book originates from, and collects the experience of, a course for PhD students in Information Engineering held at the Politecnico di Milano. Following the structure of the course, the book features contributions from some researchers who are working at the intersection between computing and science.
Methods and Models in Mathematical Programming
by F. Hooshmand S. A. MirHassaniThis book focuses on mathematical modeling, describes the process of constructing and evaluating models, discusses the challenges and delicacies of the modeling process, and explicitly outlines the required rules and regulations so that the reader will be able to generalize and reuse concepts in other problems by relying on mathematical logic.Undergraduate and postgraduate students of different academic disciplines would find this book a suitable option preparing them for jobs and research fields requiring modeling techniques. Furthermore, this book can be used as a reference book for experts and practitioners requiring advanced skills of model building in their jobs.
Methods and Techniques in Deep Learning: Advancements in mmWave Radar Solutions
by Avik Santra Souvik Hazra Lorenzo Servadei Thomas Stadelmayer Michael Stephan Anand DubeyMethods and Techniques in Deep Learning Introduces multiple state-of-the-art deep learning architectures for mmWave radar in a variety of advanced applications Methods and Techniques in Deep Learning: Advancements in mmWave Radar Solutions provides a timely and authoritative overview of the use of artificial intelligence (AI)-based processing for various mmWave radar applications. Focusing on practical deep learning techniques, this comprehensive volume explains the fundamentals of deep learning, reviews cutting-edge deep metric learning techniques, describes different typologies of reinforcement learning (RL) algorithms, highlights how domain adaptation (DA) can be used for improving the performance of machine learning (ML) algorithms, and more. Throughout the book, readers are exposed to product-ready deep learning solutions while learning skills that are relevant for building any industrial-grade, sensor-based deep learning solution. A team of authors with more than 70 filed patents and 100 published papers on AI and sensor processing illustrates how deep learning is enabling a range of advanced industrial, consumer, and automotive applications of mmWave radars. In-depth chapters cover topics including multi-modal deep learning approaches, the elemental blocks required to formulate Bayesian deep learning, how domain adaptation (DA) can be used for improving the performance of machine learning algorithms, and geometric deep learning are used for processing point clouds. In addition, the book: Discusses various advanced applications and how their respective challenges have been addressed using different deep learning architectures and algorithms Describes deep learning in the context of computer vision, natural language processing, sensor processing, and mmWave radar sensors Demonstrates how deep parametric learning reduces the number of trainable parameters and improves the data flow Presents several human-machine interface (HMI) applications such as gesture recognition, human activity classification, human localization and tracking, in-cabin automotive occupancy sensing Methods and Techniques in Deep Learning: Advancements in mmWave Radar Solutions is an invaluable resource for industry professionals, researchers, and graduate students working in systems engineering, signal processing, sensors, data science, and AI.
Methods andAlgorithms in Navigation: Marine Navigation and Safety of Sea Transportation
by Adam Weintrit Tomasz NeumannThe TransNav 2011 Symposium held at the Gdynia Maritime University, Poland in June 2011 has brought together a wide range of participants from all over the world. The program has offered a variety of contributions, allowing to look at many aspects of the navigational safety from various different points of view. Topics presented and discussed at th
Methods for Analyzing Large Neuroimaging Datasets (Neuromethods #218)
by Robert Whelan Hervé LemaîtreThis Open Access volume explores the latest advancements and challenges in standardized methodologies, efficient code management, and scalable data processing of neuroimaging datasets. The chapters in this book are organized in four parts. Part One shows the researcher how to access and download large datasets, and how to compute at scale. Part Two covers best practices for working with large data, including how to build reproducible pipelines and how to use Git. Part Three looks at how to do structural and functional preprocessing data at scale, and Part Four describes various toolboxes for interrogating large neuroimaging datasets, including machine learning and deep learning approaches. In the Neuromethods series style, chapters include the kind of detail and key advice from the specialists needed to get successful results in your laboratory. Authoritative and comprehensive, Methods for Analyzing Large Neuroimaging Datasets is a valuable resource that will help researchers obtain the practical knowledge necessary for conducting robust and reproducible analyses of large neuroimaging datasets.
Methods for Appearance-based Loop Closure Detection: Applications To Topological Mapping And Image Mosaicking (Springer Tracts In Advanced Robotics #122)
by Emilio Garcia-Fidalgo Alberto OrtizMapping and localization are two essential tasks in autonomous mobile robotics. Due to the unavoidable noise that sensors present, mapping algorithms usually rely on loop closure detection techniques, which entail the correct identification of previously seen places to reduce the uncertainty of the resulting maps. This book deals with the problem of generating topological maps of the environment using efficient appearance-based loop closure detection techniques. Since the quality of a visual loop closure detection algorithm is related to the image description method and its ability to index previously seen images, several methods for loop closure detection adopting different approaches are developed and assessed. Then, these methods are used in three novel topological mapping algorithms. The results obtained indicate that the solutions proposed attain a better performance than several state-of-the-art approaches. To conclude, given that loop closure detection is also a key component in other research areas, a multi-threaded image mosaicing algorithm is proposed. This approach makes use of one of the loop closure detection techniques previously introduced in order to find overlapping pairs between images and finally obtain seamless mosaics of different environments in a reasonable amount of time.
Methods for Multilevel Analysis and Visualisation of Geographical Networks
by Céline Rozenblat Guy MelanconThis leading-edge study focuses on the latest techniques in analysing and representing the complex, multi-layered data now available to geographers studying urban zones and their populations. The volume tracks the successful results of the SPANGEO Project, which was set up in 2005 to standardize, and share, the syncretic, multinational mapping techniques already developed by geographers and computer scientists. SPANGEO sought new and responsive ways of visualising urban geographical and social data that reflected the fine-grained detail of the inputs. It allowed for visual representation of the large and complex networks and flows which are such an integral feature of the dynamism of urban geography. SPANGEO developed through the 'visual analytics loop' in which geographers collaborated with computer scientists by feeding data into the design of visualisations that in turn spawned the urge to incorporate more varied data into the visualisation. This volume covers all the relevant aspects, from conceptual principles to the tools of network analysis and the actual results flowing from their deployment. Detailed case studies set out in this volume include spatial multi-level analyses of flows in airports and sea ports, as well as the fascinating scientific networks in European cities. The volume shows how the primary concern of geography--the interaction of society with physical space--has been revivified by the complexities of new cartographical and statistical methodologies, which allow for highly detailed mapping and far more powerful computer analysis of spatial relationships.
Methods for Solving Complex Problems in Fluids Engineering
by Can Kang Haixia Liu Yongchao Zhang Ning MaoThis book describes recently developed research methods used to study complex problems in fluid engineering, especially optical flow measurement, flow visualization and numerical methods. It includes a wealth of diagrams and images, and the content is presented in a step-by-step manner from beginning to end, helping readers grasp the central points of the book.The book also presents a number of practical cases, illustrating how the research methods covered can be concretely implemented. Lastly, the book offers a valuable point of departure for pursuing further research.
Methods for Studying Video Games and Religion (Routledge Studies in Religion and Digital Culture)
by Vít Šisler Kerstin Radde-Antweiler Xenia ZeilerGame studies has been an understudied area within the emerging field of digital media and religion. Video games can reflect, reject, or reconfigure traditionally held religious ideas and often serve as sources for the production of religious practices and ideas. This collection of essays presents a broad range of influential methodological approaches that illuminate how and why video games shape the construction of religious beliefs and practices, and also situates such research within the wider discourse on how digital media intersect with the religious worlds of the 21st century. Each chapter discusses a particular method and its theoretical background, summarizes existing research, and provides a practical case study that demonstrates how the method specifically contributes to the wider study of video games and religion. Featuring contributions from leading and emerging scholars of religion and digital gaming, this book will be an invaluable resource for scholars in the areas of digital culture, new media, religious studies, and game studies across a wide range of disciplines.
Methods for the Analysis of Asymmetric Proximity Data (Behaviormetrics: Quantitative Approaches to Human Behavior #7)
by Giuseppe Bove Akinori Okada Donatella VicariThis book provides an accessible introduction and practical guidelines to apply asymmetric multidimensional scaling, cluster analysis, and related methods to asymmetric one-mode two-way and three-way asymmetric data. A major objective of this book is to present to applied researchers a set of methods and algorithms for graphical representation and clustering of asymmetric relationships. Data frequently concern measurements of asymmetric relationships between pairs of objects from a given set (e.g., subjects, variables, attributes,…), collected in one or more matrices. Examples abound in many different fields such as psychology, sociology, marketing research, and linguistics and more recently several applications have appeared in technological areas including cybernetics, air traffic control, robotics, and network analysis. The capabilities of the presented algorithms are illustrated by carefully chosen examples and supported by extensive data analyses. A review of the specialized statistical software available for the applications is also provided. This monograph is highly recommended to readers who need a complete and up-to-date reference on methods for asymmetric proximity data analysis.
Methods in Algorithmic Analysis (Chapman & Hall/CRC Computer and Information Science Series)
by null Vladimir A. DobrushkinExplores the Impact of the Analysis of Algorithms on Many Areas within and beyond Computer ScienceA flexible, interactive teaching format enhanced by a large selection of examples and exercisesDeveloped from the author’s own graduate-level course, Methods in Algorithmic Analysis presents numerous theories, techniques, and methods used for analyzing algorithms. It exposes students to mathematical techniques and methods that are practical and relevant to theoretical aspects of computer science.After introducing basic mathematical and combinatorial methods, the text focuses on various aspects of probability, including finite sets, random variables, distributions, Bayes’ theorem, and Chebyshev inequality. It explores the role of recurrences in computer science, numerical analysis, engineering, and discrete mathematics applications. The author then describes the powerful tool of generating functions, which is demonstrated in enumeration problems, such as probabilistic algorithms, compositions and partitions of integers, and shuffling. He also discusses the symbolic method, the principle of inclusion and exclusion, and its applications. The book goes on to show how strings can be manipulated and counted, how the finite state machine and Markov chains can help solve probabilistic and combinatorial problems, how to derive asymptotic results, and how convergence and singularities play leading roles in deducing asymptotic information from generating functions. The final chapter presents the definitions and properties of the mathematical infrastructure needed to accommodate generating functions.Accompanied by more than 1,000 examples and exercises, this comprehensive, classroom-tested text develops students’ understanding of the mathematical methodology behind the analysis of algorithms. It emphasizes the important relation between continuous (classical) mathematics and discrete mathematics, which is the basis of computer science.
Methods of Optimization and Systems Analysis for Problems of Transcomputational Complexity
by Ivan V. SergienkoThis work presents lines of investigation and scientific achievements of the Ukrainian school of optimization theory and adjacent disciplines. These include the development of approaches to mathematical theories, methodologies, methods, and application systems for the solution of applied problems in economy, finances, energy saving, agriculture, biology, genetics, environmental protection, hardware and software engineering, information protection, decision making, pattern recognition, self-adapting control of complicated objects, personnel training, etc. The methods developed include sequential analysis of variants, nondifferential optimization, stochastic optimization, discrete optimization, mathematical modeling, econometric modeling, solution of extremum problems on graphs, construction of discrete images and combinatorial recognition, etc. Some of these methods became well known in the world's mathematical community and are now known as classic methods.
Metoda Lean Analytics. Zbuduj sukces startupu w oparciu o analiz? danych
by Alistair Croll Benjamin YoskovitzLektura obowi?zkowa dla wszystkich zainteresowanych wykorzystaniem analityki w pracach nad nowym produktem i odnoszeniem sukcesów biznesowych bez konieczno?ci wiecznego zgadywania.Peter Yared, dyrektor ds. IT, CBS InteractiveTo nie jest kolejna ksi??ka o liczbach, a rzecz o praktycznych wska?nikach. Alistair i Ben naucz? Ci?, jak przebi? si? przez mg?? danych i skupi? si? na w?a?ciwych, istotnych wska?nikach, które zadecyduj? o Twojej pora?ce lub sukcesie.Ash Maurya, za?o?yciel i dyrektor generalny Spark59 oraz WiredReach, autor ksi??ki Metoda Running LeanOkie?znane dane Jeste? przedsi?biorc?? Masz innowacyjny produkt i chcesz wej?? z nim na rynek? Mo?esz wybra? jedn? z dwóch dróg: tradycyjn?, opart? na odwiecznych m?dro?ciach starych mistrzów, albo nowoczesn?, z u?yciem modelu Lean Startup. Je?li wybra?e? pierwszy sposób - zmie? lektur?, je?li drugi - gratulacje! W tej ksi??ce znajdziesz kompletny proces analityczny, od generowania pomys?ów po przygotowanie zestawienia produktu i rynku. Dowiesz si? z niej, jak zweryfikowa? swój pomys?, znale?? odpowiednich klientów, zdefiniowa? ostateczn? wersj? produktu, zarobi? na swojej dzia?alno?ci i j? wypromowa?. Znajdziesz tu konkretne i przydatne informacje, oparte na ponad trzydziestu analizach przypadku, bez których nie mo?e si? obej?? ?aden przedsi?biorca. Ksi??ka jest skierowana równie? do analityków internetowych i analityków danych, poniewa? pozwala powi?za? efekty ich pracy z rozwa?aniami biznesowymi. Zamieszczone tu tre?ci zainteresuj? te? ludzi zaanga?owanych w rozwój produktu, zarz?dzanie nim, marketing, PR oraz dzia?alno?? inwestycyjn?, poniewa? dzi?ki nim ?atwiej b?dzie im zrozumie? i ocenia? startupy.Rewolucja w sze?ciu prostych krokachStwórz co?, co klienci pokochaj?.Zaanga?uj ludzi, aby znale?li Twój produkt i zacz?li z niego korzysta?.Poznaj model Lean Startup, podstawy analityki oraz mentalno?ci kierowania si? danymi, niezb?dnej do odniesienia sukcesu.Dowiedz si?, na którym etapie rozwoju si? znajdujesz, nad czym powiniene? pracowa? oraz jak zastosowa? model Lean Analytics we w?asnym startupie.Znajd? niez?e punkty odniesienia dla ró?nych wska?ników i naucz si? wyznacza? w?asne warto?ci docelowe.Sprawd?, w jaki sposób mo?esz zastosowa? zasady Lean Analytics w funkcjonuj?cej ju? organizacji, bo przecie? podej?cie oparte na danych sprawdza si? nie tylko w nowo powsta?ych firmach. Alistair Croll od niemal dwudziestu lat jest przedsi?biorc?, autorem ksi??ek i prelegentem. Zajmowa? si? du?ymi zbiorami danych, chmurami obliczeniowymi i startupami. W 2001 roku wspó?uczestniczy? w zak?adaniu firmy Coradiant. Od tamtej pory aktywnie pomaga wielu nowo powstaj?cym firmom i wspiera liczne startupowe imprezy.Benjamin Yoskovitz jest przedsi?biorc? z ponadpi?tnastoletnim do?wiadczeniem w bran?y internetowej. Wspó?za?o?yciel Standout Jobs i Year One Labs, pe?ni funkcj? mentora dla wielu startupów i akceleratorów przedsi?biorczo?ci. Regularnie przemawia podczas licznych konferencji po?wi?conych problematyce startupów.
Metoda Running Lean. Iteracja od planu A do planu, który da Ci sukces. Wydanie II
by Ash MauryaTo jedna z najlepszych technicznych ksi??ek na temat modelu Lean Startup. I tyle. Nic wi?cej nie trzeba dodawa?.Dan Martell, za?o?yciel, Clarity.fm, anio? biznesu Wizja testowana w praktyceWitamy w ?wiecie najnowocze?niejszych praktyk biznesowych i niezmierzonych mo?liwo?ci w dziedzinie innowacji. ?yjemy w dobie Internetu, chmur obliczeniowych i oprogramowania open source, dzi?ki czemu koszty budowania nowych produktów osi?gn??y rekordowo niski poziom. A jednak mimo wszystko szanse na to, by za?o?ony przez nas startup odniós? sukces, nie wzros?y. Dlatego w?a?nie powsta? ten podr?cznik. Jest on znakomitym narz?dziem dla szefów firm, dyrektorów generalnych, w?a?cicieli ma?ych przedsi?biorstw, deweloperów i programistów oraz ka?dego zainteresowanego stworzeniem firmy, która nie tylko przetrwa, ale b?dzie mia?a szanse liczy? si? na rynku.Running Lean to lepsza i szybsza metoda testowania pomys?ów na nowe produkty oraz opracowywania produktów, które odnios? sukces. Dzi?ki niej nauczysz si?:znajdowa? uczestników wczesnego rynku;wybiera? w?a?ciwy moment na pozyskiwanie kapita?u z zewn?trz;testowa? ceny;tworzy? i mierzy? to, czego chc? klienci;maksymalizowa? podejmowane dzia?ania pod k?tem szybko?ci uczenia si? i koncentracji;rozpoznawa? zestawienie produktu i rynku;d??y? w sposób powtarzalny do opracowywania produktów odpowiadaj?cych potrzebom rynku.Przeczytaj równie?: Metoda Lean Startup. Wykorzystaj innowacyjne narz?dzia i stwórz firm?, która zdob?dzie rynek, Eric Ries, Helion 2012.Ash Maurya - za?o?yciel firmy Spark59. Za?o?y? równie? kilka innych startupów, w?ród których znalaz?y si? tak udane przedsi?wzi?cia, jak WiredReach. Dzi?ki prowadzonym przez siebie warsztatom Running Lean blisko wspó?pracuje z wieloma przedsi?biorcami, którym pomaga testowa? i dopracowywa? ich wizj?. Ash pe?ni funkcj? mentora w wielu inkubatorach przedsi?biorczo?ci na ca?ym ?wiecie, w tym w Mozilla Foundation, Year One Labs oraz Capital Factory.
Metodi e Modelli Matematici per le Dinamiche Urbane (UNITEXT #128)
by Sergio Albeverio Paolo Giordano Alberto VancheriIl testo presenta metodi e modelli per lo studio delle città viste come sistemi evolutivi che interagiscono con il territorio circostante. Gli aspetti morfologici, strutturali e dinamici sono sottolineati e analizzati con metodi qualitativi e quantitativi originati dalla matematica e dalla fisica, ma anche ispirati da altre scienze naturali e dallo studio dei sistemi socio-economici. Il libro usa la matematica in vari modi: i concetti e i metodi che vanno oltre quelli della matematica elementare vengono introdotti ed esposti brevemente, con particolare attenzione a quelli attinenti a probabilità e statistica che, non facendo parte dell'educazione di base, vengono presentati sistematicamente tramite capitoli appositi. Contributi più specializzati includono argomenti come la dinamica urbana, l'analisi di progetti architettonici per il territorio, l'uso di automi cellulari stocastici, la sintassi dello spazio urbano, l'influenza del paesaggio e della geografia, e i modelli per la mobilità urbana. Il libro è rivolto agli studenti di corsi avanzati di architettura, urbanistica e ingegneria, e a tutte le persone che studiano il territorio o vi operano.
Metrics at Work: Journalism and the Contested Meaning of Algorithms
by Angele ChristinThe starkly different ways that American and French online news companies respond to audience analytics and what this means for the future of newsWhen the news moved online, journalists suddenly learned what their audiences actually liked, through algorithmic technologies that scrutinize web traffic and activity. Has this advent of audience metrics changed journalists’ work practices and professional identities? In Metrics at Work, Angèle Christin documents the ways that journalists grapple with audience data in the form of clicks, and analyzes how new forms of clickbait journalism travel across national borders.Drawing on four years of fieldwork in web newsrooms in the United States and France, including more than one hundred interviews with journalists, Christin reveals many similarities among the media groups examined—their editorial goals, technological tools, and even office furniture. Yet she uncovers crucial and paradoxical differences in how American and French journalists understand audience analytics and how these affect the news produced in each country. American journalists routinely disregard traffic numbers and primarily rely on the opinion of their peers to define journalistic quality. Meanwhile, French journalists fixate on internet traffic and view these numbers as a sign of their resonance in the public sphere. Christin offers cultural and historical explanations for these disparities, arguing that distinct journalistic traditions structure how journalists make sense of digital measurements in the two countries.Contrary to the popular belief that analytics and algorithms are globally homogenizing forces, Metrics at Work shows that computational technologies can have surprisingly divergent ramifications for work and organizations worldwide.
Metrics for Test Reporting: Analysis and Reporting for Effective Test Management
by Frank WittePart of any software development is to regularly inform management about the progress and any problems of the project. This book presents various test parameters and metrics that can be used to vividly illustrate the progress of a software test and easily identify any need for action. The key parameters and index values that are essential for successful reporting are explained in detail.Starting with the historical development of test reporting, the author explains the fundamental benefits of metrics and provides an overview of the different types of metrics and how they can be used effectively in software testing. He shows how a particular metric can be individually adapted to the software to be tested, starting with the test specification and test execution through to the development of test coverage, and how this can lead to test automation. He also presents the advantages and disadvantages of those test metrics that are based on defects, i.e. that measure the number of defects, the defect density and the development of defects over time.With this detailed examination of test reporting, the author provides an optimal basis for evaluation, which not only allows the assessment of which test metric should be used for which purpose or which individual project situation, but also what the particular problems of an individual metric for test reporting may be and how these problems can best be solved. This practical guide is therefore primarily aimed at employees in IT projects, such as project managers, software testers and developers, but business and technology consultants as well as lecturers at colleges and universities will also find an exciting insight into various software testing methods.
The Metrics Manifesto: Confronting Security with Data
by Richard SeiersenSecurity professionals are trained skeptics. They poke and prod at other people’s digital creations, expecting them to fail in unexpected ways. Shouldn’t that same skeptical power be turned inward? Shouldn’t practitioners ask: “How do I know that my enterprise security capabilities work? Are they scaling, accelerating, or slowing as the business exposes more value to more people and through more channels at higher velocities?” This is the start of the modern measurement mindset—the mindset that seeks to confront security with data. The Metrics Manifesto: Confronting Security with Data delivers an examination of security metrics with R, the popular open-source programming language and software development environment for statistical computing. This insightful and up-to-date guide offers readers a practical focus on applied measurement that can prove or disprove the efficacy of information security measures taken by a firm. The book’s detailed chapters combine topics like security, predictive analytics, and R programming to present an authoritative and innovative approach to security metrics. The author and security professional examines historical and modern methods of measurement with a particular emphasis on Bayesian Data Analysis to shed light on measuring security operations. Readers will learn how processing data with R can help measure security improvements and changes as well as help technology security teams identify and fix gaps in security. The book also includes downloadable code for people who are new to the R programming language. Perfect for security engineers, risk engineers, IT security managers, CISOs, and data scientists comfortable with a bit of code, The Metrics Manifesto offers readers an invaluable collection of information to help professionals prove the efficacy of security measures within their company.
Metrics of Sensory Motor Coordination and Integration in Robots and Animals: How to Measure the Success of Bioinspired Solutions with Respect to their Natural Models, and Against More ‘Artificial’ Solutions? (Cognitive Systems Monographs #36)
by Fabio Bonsignorio Elena Messina Angel P. del Pobil John HallamThis book focuses on a critical issue in the study of physical agents, whether natural or artificial: the quantitative modelling of sensory–motor coordination.Adopting a novel approach, it defines a common scientific framework for both the intelligent systems designed by engineers and those that have evolved naturally. As such it contributes to the widespread adoption of a rigorous quantitative and refutable approach in the scientific study of ‘embodied’ intelligence and cognition. More than 70 years after Norbert Wiener’s famous book Cybernetics: or Control and Communication in the Animal and the Machine (1948), robotics, AI and life sciences seem to be converging towards a common model of what we can call the ‘science of embodied intelligent/cognitive agents’. This book is interesting for an interdisciplinary community of researchers, technologists and entrepreneurs working at the frontiers of robotics and AI, neuroscience and general life and brain sciences.