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Dynamic Infection Spread Model Based Group Testing

algorithmS 2023年第1期16卷 25-25页

作者： Arasli, Batuhan Ulukus, Sennur Univ Maryland Dept Elect & Comp Engn College Pk MD 20742 USA

Group testing idea is an efficient approach to detect prevalence of an infection in the test samples taken from a group of individuals. It is based on the idea of pooling the test samples and performing tests to the mixed samples. This approach results in possible reduction in the required number of tests to identify infections. Classical group testing works consider static settings where the infection statuses of the individuals do not change throughout the testing process. In our paper, we study a dynamic infection spread model, inspired by the discrete time SIR model, where infections are spread via non-isolated infected individuals, while infection keeps spreading over time, a limited capacity testing is performed at each time instance as well. In contrast to the classical, static group testing problem, the objective in our setup is not to find the minimum number of required tests to identify the infection status of every individual in the population, but to control the infection spread by detecting and isolating the infections over time by using the given, limited number of tests. In order to analyze the performance of the proposed algorithms, we focus on the average-case analysis of the number of individuals that remain non-infected throughout the process of controlling the infection. We propose two dynamic algorithms that both use given limited number of tests to identify and isolate the infections over time, while the infection spreads, while the first algorithm is a dynamic randomized individual testing algorithm, in the second algorithm we employ the group testing approach similar to the original work of Dorfman. By considering weak versions of our algorithms, we obtain lower bounds for the performance of our algorithms. Finally, we implement our algorithms and run simulations to gather numerical results and compare our algorithms and theoretical approximation results under different sets of system parameters.

关键词： group testing dynamic group testing algorithm design group testing over time pooled testing

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Routing in triple loop circulants: A case of networks-on-chip

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HELIYON 2020年第7期6卷 e04427页

作者： Romanov, Aleksandr Yu Starykh, Vladimir A. Natl Res Univ Higher Sch Econ 34 Tallinskaya Ulitsa Moscow 123458 Russia

In this paper we propose and analyze various approaches to organizing routing in a triple loop circulant topologies as applied to networks-on-chip: static routing based on universal graph search algorithms, such as Dijkstra's algorithm and a possible implementation using Table routing;algorithms created analytically based on an engineering approach with taking into account the structural features of triple loop circulant graphs (Advanced clockwise, Direction selection);an algorithm created on the basis of a mathematical analysis of graph structure and solving the problem of enumerating coefficients at generators (Coefficients finding algorithm). Efficiency, maximum graph paths, occupied memory resources, and calculation time of the algorithms developed are estimated. Comparison of various variants of the algorithms is made and recommendations on their application for the development of networks-on-chip with triple loop circulant topologies are given. It is shown that Advanced clockwise and Direction selection algorithms guarantee that the packet reaches the destination node, but often in more steps than the shortest path. Nevertheless, they themselves are simpler and require less hardware resources than other algorithms. In turn, Coefficients finding algorithm has great computational complexity, but is optimal and, in comparison with Dijkstra's algorithm, is much simpler for RTL implementation which reduces network-on-chip routers resources cost.

关键词： Electrical engineering Topology Computer architecture algorithm design Very-large-scale integration Computer-aided engineering Network-on-chip Dijkstra's algorithm Triple loop circulant Routing algorithm

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A Bayesian Multi-Armed Bandit algorithm for Dynamic End-to-End Routing in SDN-Based Networks with Piecewise-Stationary Rewards

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algorithmS 2023年第5期16卷 233-233页

作者： Santana, Pedro Moura, Jose ISCTE Univ Inst Lisbon ISCTE IUL Av Forcas Armadas P-1649026 Lisbon Portugal ISTAR Informat Sci & Technol & Architecture Res Ct Av Forcas Armadas P-1649026 Lisbon Portugal Inst Telecomunicacoes IT Av Forcas Armadas P-1649026 Lisbon Portugal

To handle the exponential growth of data-intensive network edge services and automatically solve new challenges in routing management, machine learning is steadily being incorporated into software-defined networking solutions. In this line, the article presents the design of a piecewise-stationary Bayesian multi-armed bandit approach for the online optimum end-to-end dynamic routing of data flows in the context of programmable networking systems. This learning-based approach has been analyzed with simulated and emulated data, showing the proposal's ability to sequentially and proactively self-discover the end-to-end routing path with minimal delay among a considerable number of alternatives, even when facing abrupt changes in transmission delay distributions due to both variable congestion levels on path network devices and dynamic delays to transmission links.

关键词： networks routing congestion variable link delay SDN algorithm design multi-armed bandits

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Dynamic SAFFRON: Disease Control Over Time via Group Testing

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algorithmS 2022年第11期15卷 437-437页

作者： Arasli, Batuhan Ulukus, Sennur Univ Maryland Dept Elect & Comp Engn College Pk MD 20742 USA

Group testing is an efficient algorithmic approach to the infection identification problem, based on mixing the test samples and testing the mixed samples instead of individually testing each sample. In this paper, we consider the dynamic infection spread model that is based on the discrete SIR model, which assumes the disease to be spread over time via infected and non-isolated individuals. In our system, the main objective is not to minimize the number of required tests to identify every infection, but instead, to utilize the available, given testing capacity T at each time instance to efficiently control the infection spread. We introduce and study a novel performance metric, which we coin as epsilon-disease control time. This metric can be used to measure how fast a given algorithm can control the spread of a disease. We characterize the performance of the dynamic individual testing algorithm and introduce a novel dynamic SAFFRON-based group testing algorithm. We present theoretical results and implement the proposed algorithms to compare their performances.

关键词： group testing dynamic group testing algorithm design group testing over time pooled testing

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Open source implementations of numerical algorithms for computing the complete elliptic integral of the first kind

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RESULTS IN APPLIED MATHEMATICS 2024年 23卷

作者： Zhang, Hong-Yan Jiang, Wen-Juan Hainan Normal Univ Sch Informat Sci & Technol 99 Rd LongKun South Haikou 571158 Peoples R China

The complete elliptic integral of the first kind (CEI-1) plays a significant role in mathematics, physics and engineering. There is no simple formula for its computation, thus numerical algorithms are essential for coping with the practical problems involved. The commercial implementations for the numerical solutions, such as the functions ellipticK and EllipticK provided by MATLAB and Mathematica respectively, are based on K-cs(m) instead of the usual form K(k) such that K-cs(k(2)) =K(k) and m = k( 2 ). It is necessary to develop open source implementations for the computation of the CEI-1 in order to avoid potential risks of using commercial software and possible limitations due to the unknown factors. In this paper, the infinite series method, arithmetic-geometric mean (AGM) method, Gauss-Chebyshev method and Gauss-Legendre methods are discussed in details with a top-down strategy. The four key algorithms for computing the CEI-1 are designed, verified, validated and tested, which can be utilized in R& D and be reused properly. Numerical results show that our open source implementations based on K(k) are equivalent to the commercial implementation based on K-cs(m) . The general algorithms for computing orthogonal polynomials developed are valuable for the STEM education and scientific computation.

关键词： Complete elliptic integral of the first kind (CEI-1) algorithm design Orthogonal polynomials Verification-validation-testing (VVT) STEM education Computer programming

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LOW-DELAY NONUNIFORM OVERSAMPLED FILTERBANKS FOR ACOUSTIC ECHO CONTROL

LOW-DELAY NONUNIFORM OVERSAMPLED FILTERBANKS FOR ACOUSTIC EC...

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European Signal Processing Conference

作者： Bogdan Dumitrescu Robert Bregovic Tapio Saramaki Riitta Niemisto University of Pisa

We propose an algorithm for designing nonuniform oversampled filterbanks with arbitray delay. The filterbank has uniform sections obtained by generalized DFT modulation;between the uniform sections, there are transition filters. There is no a priori constraint on the widths of transition filters channels, as in previous publications. The design algorithm is composed of three steps, in which a bank (analysis or synthesis) is optimized by solving convex optimization problems for finding the prototypes of uniform sections and the transition filters. In the first step, an orthogonal filterbank is designed, while in the other steps a bank is given and the other is optimized. We present an example of design suitable to subband processing of wideband speech signals.

关键词： Filter banks design algorithm ECHO Filters Uniform Uniforms algorithm design

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Group Testing with a Graph Infection Spread Model

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INFORMATION 2023年第1期14卷 48页

作者： Arasli, Batuhan Ulukus, Sennur Univ Maryland Dept Elect & Comp Engn College Pk MD 20742 USA

The group testing idea is an efficient infection identification approach based on pooling the test samples of a group of individuals, which results in identification with less number of tests than individually testing the population. In our work, we propose a novel infection spread model based on a random connection graph which represents connections between n individuals. Infection spreads via connections between individuals, and this results in a probabilistic cluster formation structure as well as non-i.i.d. (correlated) infection statuses for individuals. We propose a class of two-step sampled group testing algorithms where we exploit the known probabilistic infection spread model. We investigate the metrics associated with two-step sampled group testing algorithms. To demonstrate our results, for analytically tractable exponentially split cluster formation trees, we calculate the required number of tests and the expected number of false classifications in terms of the system parameters, and identify the trade-off between them. For such exponentially split cluster formation trees, for zero-error construction, we prove that the required number of tests is O(log2n). Thus, for such cluster formation trees, our algorithm outperforms any zero-error non-adaptive group test, binary splitting algorithm, and Hwang's generalized binary splitting algorithm. Our results imply that, by exploiting probabilistic information on the connections of individuals, group testing can be used to reduce the number of required tests significantly even when the infection rate is high, contrasting the prevalent belief that group testing is useful only when the infection rate is low.

关键词： group testing dynamic group testing algorithm design group testing over time pooled testing

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designing Reinforcement Learning algorithms for Digital Interventions: Pre-Implementation Guidelines

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algorithmS 2022年第8期15卷 255-255页

作者： Trella, Anna L. Zhang, Kelly W. Nahum-Shani, Inbal Shetty, Vivek Doshi-Velez, Finale Murphy, Susan A. Harvard Univ Sch Engn & Appl Sci Cambridge MA 02420 USA Univ Michigan Inst Social Res Ann Arbor MI 48109 USA Univ Calif Los Angeles Sch Dent Los Angeles CA 90095 USA Univ Calif Los Angeles Sch Engn Los Angeles CA 90095 USA

Online reinforcement learning (RL) algorithms are increasingly used to personalize digital interventions in the fields of mobile health and online education. Common challenges in designing and testing an RL algorithm in these settings include ensuring the RL algorithm can learn and run stably under real-time constraints, and accounting for the complexity of the environment, e.g., a lack of accurate mechanistic models for the user dynamics. To guide how one can tackle these challenges, we extend the PCS (predictability, computability, stability) framework, a data science framework that incorporates best practices from machine learning and statistics in supervised learning to the design of RL algorithms for the digital interventions setting. Furthermore, we provide guidelines on how to design simulation environments, a crucial tool for evaluating RL candidate algorithms using the PCS framework. We show how we used the PCS framework to design an RL algorithm for Oralytics, a mobile health study aiming to improve users' tooth-brushing behaviors through the personalized delivery of intervention messages. Oralytics will go into the field in late 2022.

关键词： reinforcement learning (RL) online learning mobile health algorithm design algorithm evaluation

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Hamiltonian-Based Efficient algorithms for Legalization with Neighbor Diffusion Effect

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INTERNATIONAL JOURNAL OF FOUNDATIONS OF COMPUTER SCIENCE 2023年第0期

作者： Sun, Hao Guo, Longkun Zhang, Xiaoyan Qilu Univ Technol Sch Comp Sci & Technol Jinan 250300 Peoples R China Nanjing Normal Univ Inst Math Sch Math Sci Nanjing 210008 Peoples R China

Neighbor diffusion effect (NDE) is a crucial aspect in advanced technology node that is well-known for its infamous consequence of significant performance decrement of the circuit. In this paper, we observe that NDE is caused by different diffusion heights (the number of fins) between two adjacent cells, and consider reducing the number of height differences in single row to reduce NDE violations. Ignoring the movement of the cells, we first propose a Hamiltonian-completion-based algorithm that reorders the cells in the row such that the number of NDE violations is reduced to a near-optimal value. Then, for a given fixed integer eta > 0, we devise an algorithm to compute the new positions of cells, such that the number of NDE violations is bounded by eta + 1 and the maximum displacement is minimized. Moreover, we extend our algorithm for legalization in multiple rows against mixed-height cells. Experimental results show that our algorithm reduces the NDE violations to a near-optimal minimum without any area overheads while achieving a better practical running time compared to baselines conforming with the theoretical analysis.

关键词： Neighbor diffusion effect legalization Hamiltonian completion algorithm design

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A fuzzy model for automated precision robot assembly of parts

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IFAC Proceedings Volumes 2000年第20期33卷 521-525页

作者： Todor Neshkov Snejana Yordanova Lazar Videnov Technical University of Sofia Bulgaria

The fuzzy logic theory is suitable for solving the vagueness, nonlinearity and complexity problems of an assembly process by implanting ’human reasoning and action’ in the automated devices. The aim of the paper is to develop a simple and fast fuzzy rule-based algorithm and to explore via simulation the possibility of its implementation for precision assembly of chamferless parts. The main contribution is a simple, fast and reliable fuzzy algorithm, ready for imbedding in the PLC of a SCARA type robot.

关键词： fuzzy control algorithm design assembly SCARA type robot simulation Matlab

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