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8th International Conference on Universal Access in Human-computer Interaction, UAHCI 2014 - Held as Part of 16th International Conference on Human-computer Interaction, HCI International 2014

作者： Cuttone, Andrea Petersen, Michael Kai Larsen, Jakob Eg Department of Applied Mathematics and Computer Science Cognitive Systems Section Matematiktorvet 303B 2800 Kgs Lyngby Denmark

ISBN: (纸本)9783319075082

In this paper we discuss how to facilitate the process of reflection in Personal Informatics and Quantified Self systems through interactive data visualizations. Four heuristics for the design and evaluation of such systems have been identified through analysis of self-tracking devices and apps. Dashboard interface paradigms in specific self-tracking devices (Fitbit and Basis) are discussed as representative examples of state of the art in feedback and reflection support. By relating to existing work in other domains, such as event related representation of time series multivariate data in financial analytics, it is discussed how the heuristics could guide designs that would further facilitate reflection in self-tracking personal informatics systems. © 2014 Springer International Publishing.

关键词： Data visualization

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Slow Retrial Asymptotics for a Single Server Queue with Two-Way Communication and Markov Modulated Poisson

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Journal of systems science and systems Engineering 2019年第2期28卷 181-193页

作者： Anatoly Nazarov Tuan Phung-Duc Svetlana Paul Institute of Applied Mathematics and Computer Science National Research Tomsk State University 36 Lenina ave. 634050 Tomsk Russian Federation Faculty of Engineering Information and Systems University of Tsukuba 1-1-1 Tennodai Tsukuba Ibaraki 305-8573 Japan

In this paper, we consider an MMPP/M/1/1 retrial queue where incoming fresh calls arrive at the server according to a Markov modulated Poisson process (MMPP). Upon arrival, an incoming call either occupies the server if it is idle or joins a virtual waiting room called orbit if the server is busy. From the orbit, incoming calls retry to occupy the server in an exponentially distributed time and behave the same as a fresh incoming call. After an exponentially distributed idle time, the server makes an outgoing call whose duration is also exponentially distributed but with a different parameter from that of incoming calls. Our contribution is to derive the first order (law of large numbers) and the second order (central lim让 theorem) asymptotics for the distribution of the number of calls in the orb计 under the condition that the retrial rate is extremely low. The asymptotic results are used to obtain the Gaussian approximation for the distribution of the number of calls in the orbit. Our result generalizes earlier results where Poisson input was assumed.

关键词： Retrial queueing system incoming calls and outgoing calls MMPP-process asymptotic analysismethod gaussian approximation

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A Learnheuristic Approach to A Constrained Multi-Objective Portfolio Optimisation Problem 23

A Learnheuristic Approach to A Constrained Multi-Objective P...

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7th International Conference on Intelligent systems, Metaheuristics and Swarm Intelligence, ISMSI 2023

作者： Bullah, Sonia van Zyl, Terence L. Computer Science and Applied Mathematics University of the Witwatersrand Johannesburg South Africa Institute for Intelligent Systems University of Johannesburg Johannesburg South Africa

ISBN: (纸本)9781450399920

Multi-objective portfolio optimisation is a critical problem researched across various fields of study as it achieves the objective of maximising the expected return while minimising the risk of a given portfolio at the same time. However, many studies fail to include realistic constraints in the model, which limits practical trading strategies. This study introduces realistic constraints, such as transaction and holding costs, into an optimisation model. Due to the non-convex nature of this problem, metaheuristic algorithms, such as NSGA-II, R-NSGA-II, NSGA-III and U-NSGA-III, will play a vital role in solving the problem. Furthermore, a learnheuristic approach is taken as surrogate models enhance the metaheuristics employed. These algorithms are then compared to the baseline metaheuristic algorithms, which solve a constrained, multi-objective optimisation problem without using learnheuristics. The results of this study show that, despite taking significantly longer to run to completion, the learnheuristic algorithms outperform the baseline algorithms in terms of hypervolume and rate of convergence. Furthermore, the backtesting results indicate that utilising learnheuristics to generate weights for asset allocation leads to a lower risk percentage, higher expected return and higher Sharpe ratio than backtesting without using learnheuristics. This leads us to conclude that using learnheuristics to solve a constrained, multi-objective portfolio optimisation problem produces superior and preferable results than solving the problem without using learnheuristics. © 2023 Copyright held by the owner/author(s). Publication rights licensed to ACM.

关键词： Genetic algorithms

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A partial equilibrium view on security and privacy

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Information Management and computer Security 2008年第1期16卷 74-83页

作者： Katos, Vasilios Patel, Ahmed School of Computing University of Portsmouth Portsmouth United Kingdom School of Computing Information Systems and Mathematics Centre for Applied Research in Information Systems Kingston University Kingston upon Thames United Kingdom Department of Computer Science Faculty of Information Science and Technology University Kebangsaan Malaysia Bangi Malaysia

Purpose - This paper aims to propose a tool to help policy makers understand the dynamic relationships between security and privacy on a strategic (macro) level. Design/methodology/approach - The methodology is ported from the discipline of Macroeconomics, and applied to the information security and privacy domain. The methodology adopted is the so-called "cross methodology" which claims ownership of the well-known supply/demand market equilibrium exercise. Findings - Early evaluation reveals that this is a potentially very effective tool in understanding societal behaviour and position towards information security and privacy and therefore makes this a suitable tool for investigating and exploring scenarios that can assist in policy making. Originality/value - Up to date, research on the economics of security and privacy has been primarily focusing on a micro level. The main contribution of this paper is a methodology for investigating privacy and security on a macro level. We believe that our approach in undertaking this research is new and looking at the issues and relationships between security and privacy at a macro level, gives a better understanding of the problems at hand and how to resolve them. Practical implications - The proposed tool may increase the efficiency of policy making and planning as it enables the policy makers on a governmental and strategic level to run scenarios in order to investigate the effect of their decisions (for example, an introduction of a stricter law relating to computer misuse) to the delicate balance of security and privacy.

关键词： Public policy

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Explainable machine learning for movement disorders - Classification of tremor and myoclonus

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computers in Biology and Medicine 2025年第Pt B期192卷 110180-110180页

作者： van den Brandhof, Elina L. Tuitert, Inge Madelein van der Stouwe, A.M. Elting, Jan W.J. Dalenberg, Jelle R. Svorenova, Tatiana Klamer, Marrit R. Marapin, Ramesh S. Biehl, Michael Tijssen, Marina A.J. Expertise Center Movement Disorders Groningen University Medical Center Groningen Groningen Netherlands Department of Neurology University Medical Center Groningen University of Groningen Groningen Netherlands Bernoulli Institute for Mathematics Computer Science and Artificial Intelligence University of Groningen Groningen Netherlands NHL Stenden University of Applied Sciences Leeuwarden Netherlands Department of Neurology P.J. Safarik University Kosice Slovakia Department of Neurology University Hospital of L. Pasteur Kosice Slovakia SMQB Institute of Metabolism and Systems Research College of Medical and Dental Sciences University of Birmingham Birmingham United Kingdom

Background: Treatment for essential tremor (ET) and cortical myoclonus (CM) differs. As their clinical distinction can be difficult, with large inter- and intra-observer variability, there is a need for additional diagnostic tools. Objectives: We aim to develop a machine learning based approach using accelerometry data to support clinicians in their diagnosis of ET versus CM. Methods: We recorded the upper body movements of 19 ET and 19 CM patients performing 21 tasks using eight accelerometry sensors. The phenotype was classified by applying an explainable machine learning method called generalized matrix learning vector quantization (GMLVQ) to the power spectrum derived from the accelerometry recordings. In addition to the general classification performance, GMLVQ provides context for the decisions made. This includes the relevance of frequencies and thus the identification of distinct patterns in the phenotypes. Results: For all postures and dynamic tasks, excellent classification results were reached with AUROC approaching 1,0. For the classification, GMLVQ considers the overall shape of the power spectrum, whereby the frequencies 5–7 Hz as well as 3–4 and 9–10 Hz are of particular importance. These frequencies correspond to the tremor peak and local minima that are also observed as characteristics in the literature. Conclusion: The excellent classification results provide a proof of concept for the discrimination of ET and CM by applying a GMLVQ machine learning analysis to power spectra derived from accelerometry recordings. Such a system could support clinicians to improve the diagnostic accuracy. © 2025 The Authors

关键词： Accelerometers

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Indoor sign recognition for the blind

Indoor sign recognition for the blind

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2016 Annual Research Conference of the South African Institute of computer Scientists and Information Technologists, SAICSIT 2016

作者： Kunene, Dumisani Vadapalli, Hima Cronje, Jaco Optronic Sensor Systems Council of Science and Industrial Research Pretoria South Africa School of Computer Science and Applied Mathematics University of the Witwatersrand Johannesburg South Africa

ISBN: (纸本)9781450348058

Blind people face diculties when navigating unfamiliar environments. The information displayed on indoor signs and notice boards is of no use to them. In order to assist them with this challenge, we propose a real time system that can recognise a selection of indoor navigational signs placed over clear backgrounds. The selection of signs will consist of common samples from several di erent types of indoor signs. Given a captured image, the approach is to use image processing techniques to find the region of interest(ROI) that contains the sign and then extract this region for classification. Using sliding windows for searching the ROI can be time consuming and can lead to many false classifications, hence we used a more explicit approach that is faster and more reliable. We first segment the signs by colour, and then by shape recognition. The sign-type classification is done using a tree search structure that enables the use of iterative contour descriptors like the speeded-up-robustfeatures( SURF). Once a sign has been detected, this information is communicated to the user via stereo headsets. To evaluate the system's performance, several random pictures with and without signs were used to determine the system's detection rate. The user-feedback performance was evaluated by testing the system's usability score with volunteers. ©2016 ACM.

关键词： Real time systems

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Pruning techniques for the SAT-based bounded model checking problem 11th

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11th IFIP WG 10.5 Advanced Research Working Conference on Correct Hardware Design and Verification Methods, CHARME 2001 held jointly with the 14th International Conference on Theorem Proving in Higher Order Logics, TPHOLs 2009

作者： Shtrichman, Ofer The Minerva Center for Verification of Reactive Systems Dep. of Computer Science and Applied Mathematics The Weizmann Institute of Science Israel IBM Haifa Research Lab Israel

ISBN: (纸本)3540425411

Bounded Model Checking (BMC) is the problem of checking if a model satisfies a temporal property in paths with bounded length k. Propositional SAT-based BMC is conducted in a gradual manner, by solving a series of SAT instances corresponding to formulations of the problem with increasing k. We show how the gradual nature can be exploited for shortening the overall verification time. The concept is to reuse constraints on the search space which are deduced while checking a k instance, for speeding up the SAT checking of the consecutive k+1 instance. This technique can be seen as a generalization of ‘pervasive clauses’, a technique introduced by Silva and Sakallah in the context of Automatic Test Pattern Generation (ATPG). We define the general conditions for reusability of constraints, and define a simple procedure for evaluating them. This technique can theoretically be used in any solution that is based on solving a series of closely related SAT instances (instances with non-empty intersection between their set of clauses). We then continue by showing how a similar procedure can be used for restricting the search space of individual SAT instances corresponding to BMC invariant formulas. Experiments demonstrated that both techniques have consistent and significant positive effect. © Springer-Verlag Berlin Heidelberg 2001.

关键词： Reusability

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Tuning SAT checkers for bounded model checking 12th

Tuning SAT checkers for bounded model checking

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12th International Conference on computer Aided Verification, CAV 2000

ISBN: (纸本)3540677704

Bounded Model Checking based on SAT methods has recently been introduced as a complementary technique to BDD-based Symbolic Model Checking. The basic idea is to search for a counter ex- ample in executions whose length is bounded by some integer k. The BMC problem can be efficiently reduced to a propositional satisfiability problem, and can therefore be solved by SAT methods rather than BDDs. SAT procedures are based on general-purpose heuristics that are designed for any propositional formula. We show that the unique characteristics of BMC formulas can be exploited for a variety of optimizations in the SAT checking procedure. Experiments with these optimizations on real designs proved their efficiency in many of the hard test cases, comparing to both the standard SAT procedure and a BDD-based model checker. © Springer-Verlag Berlin Heidelberg 2000.

关键词： Optimization

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Lyapunov function as potential function: A dynamical equivalence

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Chinese Physics B 2014年第1期23卷 136-141页

作者：袁若石马易安苑波敖平 School of Biomedical Engineering Shanghai Jiao Tong University Shanghai Center for Systems Biomedicine Shanghai Jiao Tong University Department of Applied Mathematics University of Washington Department of Computer Science and Engineering Shanghai Jiao Tong University Department of Physics Shanghai Jiao Tong University

For a physical system, regardless of time reversal symmetry, a potential function serves also as a Lyapunov function, providing convergence and stability information. In this paper, the converse is constructively proved that any dynamics with a Lyapunov function has a corresponding physical realization： a friction force, a Lorentz force, and a potential function. Such construction establishes a set of equations with physical meaning for Lyapunov function and suggests new approaches on the significant unsolved problem namely to construct Lyapunov functions for general nonlinear systems. In addition, a connection is found that the Lyapunov equation is a reduced form of a generalized Einstein relation for linear systems, revealing further insights of the construction.

关键词： Lyapunov function potential function stochastic process generalized Einstein relation

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A stochastic perturbed augmented Lagrangian method for smooth convex constrained minimization

arXiv

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arXiv 2025年

作者： Singh, Nitesh Kumar Necoara, Ion School of Computer Science University of Petroleum and Energy Studies Uttarakhand Dehradun248007 India Automatic Control and Systems Engineering Department University Politehnica Bucharest Bucharest060042 Romania Gheorghe Mihoc-Caius Iacob Institute of Mathematical Statistics and Applied Mathematics of the Romanian Academy Bucharest050711 Romania

This paper considers smooth convex optimization problems with many functional constraints. To solve this general class of problems we propose a new stochastic perturbed augmented Lagrangian method, called SGDPA, where a perturbation is introduced in the augmented Lagrangian function by multiplying the dual variables with a subunitary parameter. Essentially, we linearize the objective and one randomly chosen functional constraint within the perturbed augmented Lagrangian at the current iterate and add a quadratic regularization that leads to a stochastic gradient descent update for the primal variables, followed by a perturbed random coordinate ascent step to update the dual variables. We provide a convergence analysis in both optimality and feasibility criteria for the iterates of SGDPA algorithm using basic assumptions on the problem. In particular, when the dual updates are assumed to be bounded, we prove sublinear rates of convergence for the iterates of algorithm SGDPA of order O(k−1/2) when the objective is convex and of order O(k−1) when the objective is strongly convex, where k is the iteration counter. Under some additional assumptions, we prove that the dual iterates are bounded and in this case we obtain convergence rates of order O(k−1/4) and O(k−1/2) when the objective is convex and strongly convex, respectively. Preliminary numerical experiments on problems with many quadratic constraints demonstrate the viability and performance of our method when compared to some existing state-of-the-art optimization methods and software. © 2025, CC BY.

关键词： Lagrange multipliers

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