58 research outputs found

    Selected Papers from the First International Symposium on Future ICT (Future-ICT 2019) in Conjunction with 4th International Symposium on Mobile Internet Security (MobiSec 2019)

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    The International Symposium on Future ICT (Future-ICT 2019) in conjunction with the 4th International Symposium on Mobile Internet Security (MobiSec 2019) was held on 17–19 October 2019 in Taichung, Taiwan. The symposium provided academic and industry professionals an opportunity to discuss the latest issues and progress in advancing smart applications based on future ICT and its relative security. The symposium aimed to publish high-quality papers strictly related to the various theories and practical applications concerning advanced smart applications, future ICT, and related communications and networks. It was expected that the symposium and its publications would be a trigger for further related research and technology improvements in this field

    Automatic machine learning:methods, systems, challenges

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    Automatic machine learning:methods, systems, challenges

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    This open access book presents the first comprehensive overview of general methods in Automatic Machine Learning (AutoML), collects descriptions of existing systems based on these methods, and discusses the first international challenge of AutoML systems. The book serves as a point of entry into this quickly-developing field for researchers and advanced students alike, as well as providing a reference for practitioners aiming to use AutoML in their work. The recent success of commercial ML applications and the rapid growth of the field has created a high demand for off-the-shelf ML methods that can be used easily and without expert knowledge. Many of the recent machine learning successes crucially rely on human experts, who select appropriate ML architectures (deep learning architectures or more traditional ML workflows) and their hyperparameters; however the field of AutoML targets a progressive automation of machine learning, based on principles from optimization and machine learning itself

    Navigation/traffic control satellite mission study. Volume 3 - System concepts

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    Satellite network for air traffic control, solar flare warning, and collision avoidanc

    A deep generative model framework for creating high quality synthetic transaction sequences

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    Synthetic data are artificially generated data that closely model real-world measurements, and can be a valuable substitute for real data in domains where it is costly to obtain real data, or privacy concerns exist. Synthetic data has traditionally been generated using computational simulations, but deep generative models (DGMs) are increasingly used to generate high-quality synthetic data. In this thesis, we create a framework which employs DGMs for generating highquality synthetic transaction sequences. Transaction sequences, such as we may see in an online banking platform, or credit card statement, are important type of financial data for gaining insight into financial systems. However, research involving this type of data is typically limited to large financial institutions, as privacy concerns often prevent academic researchers from accessing this kind of data. Our work represents a step towards creating shareable synthetic transaction sequence datasets, containing data not connected to any actual humans. To achieve this goal, we begin by developing Banksformer, a DGM based on the transformer architecture, which is able to generate high-quality synthetic transaction sequences. Throughout the remainder of the thesis, we develop extensions to Banksformer that further improve the quality of data we generate. Additionally, we perform extensively examination of the quality synthetic data produced by our method, both with qualitative visualizations and quantitative metrics

    Tools and Algorithms for the Construction and Analysis of Systems

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    This open access two-volume set constitutes the proceedings of the 26th International Conference on Tools and Algorithms for the Construction and Analysis of Systems, TACAS 2020, which took place in Dublin, Ireland, in April 2020, and was held as Part of the European Joint Conferences on Theory and Practice of Software, ETAPS 2020. The total of 60 regular papers presented in these volumes was carefully reviewed and selected from 155 submissions. The papers are organized in topical sections as follows: Part I: Program verification; SAT and SMT; Timed and Dynamical Systems; Verifying Concurrent Systems; Probabilistic Systems; Model Checking and Reachability; and Timed and Probabilistic Systems. Part II: Bisimulation; Verification and Efficiency; Logic and Proof; Tools and Case Studies; Games and Automata; and SV-COMP 2020

    Preliminary proceedings of the 2001 ACM SIGPLAN Haskell workshop

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    This volume contains the preliminary proceedings of the 2001 ACM SIGPLAN Haskell Workshop, which was held on 2nd September 2001 in Firenze, Italy. The final proceedings will published by Elsevier Science as an issue of Electronic Notes in Theoretical Computer Science (Volume 59). The HaskellWorkshop was sponsored by ACM SIGPLAN and formed part of the PLI 2001 colloquium on Principles, Logics, and Implementations of high-level programming languages, which comprised the ICFP/PPDP conferences and associated workshops. Previous Haskell Workshops have been held in La Jolla (1995), Amsterdam (1997), Paris (1999), and Montr´eal (2000). The purpose of the Haskell Workshop was to discuss experience with Haskell, and possible future developments for the language. The scope of the workshop included all aspects of the design, semantics, theory, application, implementation, and teaching of Haskell. Submissions that discussed limitations of Haskell at present and/or proposed new ideas for future versions of Haskell were particularly encouraged. Adopting an idea from ICFP 2000, the workshop also solicited two special classes of submissions, application letters and functional pearls, described below

    The verification of MDG algorithms in the HOL theorem prover

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    Formal verification of digital systems is achieved, today, using one of two main approaches: states exploration (mainly model checking and equivalence checking) or deductive reasoning (theorem proving). Indeed, the combination of the two approaches, states exploration and deductive reasoning promises to overcome the limitation and to enhance the capabilities of each. Our research is motivated by this goal. In this thesis, we provide the entire necessary infrastructure (data structure + algorithms) to define high level states exploration in the HOL theorem prover named as MDG-HOL platform. While related work has tackled the same problem by representing primitive Binary Decision Diagram (BDD) operations as inference rules added to the core of the theorem prover, we have based our approach on the Multiway Decision Graphs (MDGs). MDG generalizes ROBDD to represent and manipulate a subset of first-order logic formulae. With MDGs, a data value is represented by a single variable of an abstract type and operations on data are represented in terms of uninterpreted function. Considering MDGs instead of BDDs will raise the abstraction level of what can be verified using a state exploration within a theorem prover. The MDGs embedding is based on the logical formulation of an MDG as a Directed Formulae (DF). The DF syntax is defined as HOL built-in data types. We formalize the basic MDG operations using this syntax within HOL following a deep embedding approach. Such approach ensures the consistency of our embedding. Then, we derive the correctness proof for each MDG basic operator. Based on this platform, the MDG reachability analysis is defined in HOL as a conversion that uses the MDG theory within HOL. Then, we demonstrate the effectiveness of our platform by considering four case studies. Our obtained results show that this verification framework offers a considerable gain in terms of automation without sacrificing CPU time and memory usage compared to automatic model checker tools. Finally, we propose a reduction technique to improve MDGs model checking based on the MDG-HOL platform. The idea is to prune the transition relation of the circuits using pre-proved theorems and lemmas from the specification given at system level. We also use the consistency of the specifications to verify if the reduced model is faithful to the original one. We provide two case studies, the first one is the reduction using SAT-MDG of an Island Tunnel Controller and the second one is the MDG-HOL assume-guarantee reduction of the Look-Aside Interface. The obtained results of our approach offers a considerable gain in terms of heuristics and reduction techniques correctness as to commercial model checking; however a small penalty is paid in terms of CPU time and memory usag

    Goddard Conference on Mass Storage Systems and Technologies, Volume 1

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    Copies of nearly all of the technical papers and viewgraphs presented at the Goddard Conference on Mass Storage Systems and Technologies held in Sep. 1992 are included. The conference served as an informational exchange forum for topics primarily relating to the ingestion and management of massive amounts of data and the attendant problems (data ingestion rates now approach the order of terabytes per day). Discussion topics include the IEEE Mass Storage System Reference Model, data archiving standards, high-performance storage devices, magnetic and magneto-optic storage systems, magnetic and optical recording technologies, high-performance helical scan recording systems, and low end helical scan tape drives. Additional topics addressed the evolution of the identifiable unit for processing purposes as data ingestion rates increase dramatically, and the present state of the art in mass storage technology
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